From 4a116d83e3c8ce439040b0741d9d51105370c74e Mon Sep 17 00:00:00 2001 From: avahoffman Date: Tue, 26 Jul 2022 15:48:53 -0600 Subject: [PATCH 1/7] render --- lecture_notes/Data_Cleaning.R | 86 ++++++++++++++++------------- lecture_notes/Data_Cleaning.Rmd | 1 - lecture_notes/Data_Cleaning.html | 92 ++++++++++++++----------------- lecture_notes/Data_Cleaning.pdf | Bin 182462 -> 434362 bytes 4 files changed, 89 insertions(+), 90 deletions(-) diff --git a/lecture_notes/Data_Cleaning.R b/lecture_notes/Data_Cleaning.R index 42759bb..719a621 100644 --- a/lecture_notes/Data_Cleaning.R +++ b/lecture_notes/Data_Cleaning.R @@ -1,45 +1,54 @@ -## ---- include = FALSE--------------------------------------------------------- +## ---- include = FALSE-------------------------------------------------------------------------------------------------- library(knitr) library(tidyverse) library(janitor) opts_chunk$set(comment = "") -## ---- importUfo--------------------------------------------------------------- -ufo = read_csv("../data/ufo/ufo_data_complete.csv") +## ---------------------------------------------------------------------------------------------------------------------- +ufo <- read_delim("../data/ufo/ufo_data_complete.txt") -## ----------------------------------------------------------------------------- -colnames(ufo) -ufo = clean_names(ufo) -colnames(ufo) - -## ----------------------------------------------------------------------------- -p = problems(ufo) +## ---------------------------------------------------------------------------------------------------------------------- +p <-problems(ufo) p -## ----------------------------------------------------------------------------- -ufo = ufo[-p$row,] # brackets can also be used for subsetting +## ---------------------------------------------------------------------------------------------------------------------- +ufo[(p$row-1),] %>% glimpse() + + +## ---- echo = FALSE----------------------------------------------------------------------------------------------------- +knitr::include_graphics(here::here("lecture_notes", "media", "problems.png")) + -## ----isna--------------------------------------------------------------------- -any(is.na(ufo$state)) # are there any NAs? -all(is.na(ufo$state)) # are the values all NAs? +## ---------------------------------------------------------------------------------------------------------------------- +ufo <- read_delim("../data/ufo/ufo_data_complete.txt", + col_types = cols("duration (seconds)" = col_character())) + +ufo[(p$row-1),] %>% glimpse() + + + +## ---------------------------------------------------------------------------------------------------------------------- +colnames(ufo) +ufo = clean_names(ufo) +colnames(ufo) -## ----gender, echo=FALSE------------------------------------------------------- +## ----gender, echo=FALSE------------------------------------------------------------------------------------------------ set.seed(4) # random sample below - make sure same every time gender <- sample(c("Male", "mAle", "MaLe", "M", "MALE", "Ma", "FeMAle", "F", "Woman", "Man", "Fm", "FEMALE"), 1000, replace = TRUE) data_gen = tibble(gender) -## ----gentab------------------------------------------------------------------- +## ----gentab------------------------------------------------------------------------------------------------------------ table(gender) -## ----------------------------------------------------------------------------- +## ---------------------------------------------------------------------------------------------------------------------- #case_when way: data_gen <-data_gen %>% mutate(gender = case_when(gender %in% c("Male", "M", "m", "Man") @@ -48,7 +57,7 @@ data_gen <-data_gen %>% mutate(gender = head(data_gen) -## ----------------------------------------------------------------------------- +## ---------------------------------------------------------------------------------------------------------------------- #case_when way: data_gen <-data_gen %>% mutate(gender = str_to_sentence(gender)) %>% @@ -59,65 +68,66 @@ data_gen <-data_gen %>% head(data_gen) -## ----Paste-------------------------------------------------------------------- -paste("Visit", 1:5, sep = "_") -paste("Visit", 1:5, sep = "_", collapse = " ") -# and paste0 can be even simpler see ?paste0 -paste0("Visit", 1:5) +## ---------------------------------------------------------------------------------------------------------------------- +ufo <- ufo %>% mutate(duration_seconds = str_remove(string = duration_seconds, + pattern = "`")) +ufo <- ufo %>% mutate(duration_seconds = as.numeric(duration_seconds)) +ufo[(p$row-1),] -## ----Paste2------------------------------------------------------------------- +## ---------------------------------------------------------------------------------------------------------------------- +head(Orange) +Orange %>% mutate(Tree = paste(Tree, "Tree", sep = "_")) -paste("Visit", 1:5, sep = "_") %>% length() -paste("Visit", 1:5, sep = "_", collapse = " ") %>% length() -## ----------------------------------------------------------------------------- -paste("To", "is going be the ", "we go to the store!", sep = "day ") +## ---------------------------------------------------------------------------------------------------------------------- +head(Orange) +Orange %>% mutate(Tree = paste0(Tree, "Tree")) -## ----------------------------------------------------------------------------- +## ---------------------------------------------------------------------------------------------------------------------- str_sub("I like friesian horses", 8,12) #123456789101112 #I like fries str_sub(c("Site A", "Site B", "Site C"), 6,6) -## ----alienMatch--------------------------------------------------------------- +## ----alienMatch-------------------------------------------------------------------------------------------------------- str_detect(ufo$comments, "two aliens") %>% head() str_detect(ufo$comments, "two aliens") %>% table() which(str_detect(ufo$comments, "two aliens")) -## ----------------------------------------------------------------------------- +## ---------------------------------------------------------------------------------------------------------------------- filter(ufo, str_detect(comments, "two aliens")) filter(ufo, str_detect(comments, "two aliens")) %>% select(comments) -## ----ggrep-------------------------------------------------------------------- +## ----ggrep------------------------------------------------------------------------------------------------------------- str_subset(ufo$comments, "two aliens") -## ----ggrep2------------------------------------------------------------------- +## ----ggrep2------------------------------------------------------------------------------------------------------------ ss = str_extract(ufo$comments, "two aliens") head(ss) ss[ !is.na(ss)] -## ----grepstar----------------------------------------------------------------- +## ----grepstar---------------------------------------------------------------------------------------------------------- str_subset(ufo$comments, "^aliens.*") -## ----grepstar2---------------------------------------------------------------- +## ----grepstar2--------------------------------------------------------------------------------------------------------- str_subset(ufo$comments, "space.?ship") %>% head(4) # gets "spaceship" or "space ship" or... str_subset(ufo$comments, "space.ship") %>% head(4) # no "spaceship" must have character in bw -## ----classSal----------------------------------------------------------------- +## ----classSal---------------------------------------------------------------------------------------------------------- head(ufo$duration_hours_min, 8) ufo %>% mutate(duration_hours_min = @@ -129,7 +139,7 @@ ufo %>% mutate(duration_hours_min = -## ---- message = FALSE--------------------------------------------------------- +## ---- message = FALSE-------------------------------------------------------------------------------------------------- library(lubridate)#need to load this one! head(ufo$datetime) ufo$date_posted = mdy(ufo$date_posted) diff --git a/lecture_notes/Data_Cleaning.Rmd b/lecture_notes/Data_Cleaning.Rmd index 4fef64e..4291efd 100644 --- a/lecture_notes/Data_Cleaning.Rmd +++ b/lecture_notes/Data_Cleaning.Rmd @@ -5,7 +5,6 @@ output: ioslides_presentation: css: styles.css widescreen: yes - beamer_presentation: default --- diff --git a/lecture_notes/Data_Cleaning.html b/lecture_notes/Data_Cleaning.html index 02b5493..b9f22e0 100644 --- a/lecture_notes/Data_Cleaning.html +++ b/lecture_notes/Data_Cleaning.html @@ -3272,9 +3272,9 @@ 

Warning: One or more parsing issues, see `problems()` for details
Rows: 88875 Columns: 12
-── Column specification ────────────────────────────────────────────────────────
+── Column specification ─────────────────────────────────────────────────────────────────────────────────────────────────
 Delimiter: "\t"
-chr (9): datetime, city, state, country, shape, duration (hours/min), commen...
+chr (9): datetime, city, state, country, shape, duration (hours/min), comments, date posted, latitude
 dbl (3): duration (seconds), longitude, ...12
 
 ℹ Use `spec()` to retrieve the full column specification for this data.
@@ -3288,11 +3288,11 @@ 

 p
# A tibble: 3 × 5
-    row   col expected actual file                                              
-  <int> <int> <chr>    <chr>  <chr>                                             
-1 30894     6 a double 2`     /Users/carriewright/Documents/GitHub/Teaching/Dat…
-2 39616     6 a double 8`     /Users/carriewright/Documents/GitHub/Teaching/Dat…
-3 65125     6 a double 0.5`   /Users/carriewright/Documents/GitHub/Teaching/Dat…
+ row col expected actual file + <int> <int> <chr> <chr> <chr> +1 30894 6 a double 2` /Users/avahoffman/Dropbox/JHSPH/Data-Wrangling_SISBID/data/ufo/ufo_data_complete.txt +2 39616 6 a double 8` /Users/avahoffman/Dropbox/JHSPH/Data-Wrangling_SISBID/data/ufo/ufo_data_complete.txt +3 65125 6 a double 0.5` /Users/avahoffman/Dropbox/JHSPH/Data-Wrangling_SISBID/data/ufo/ufo_data_complete.txt

The “problems”

@@ -3302,14 +3302,14 @@ 

Rows: 3
 Columns: 12
-$ datetime               <chr> "2/2/2000 19:33", "4/10/2005 22:52", "7/21/2006…
+$ datetime               <chr> "2/2/2000 19:33", "4/10/2005 22:52", "7/21/2006 13:00"
 $ city                   <chr> "bouse", "santa cruz", "ibague (colombia)"
 $ state                  <chr> "az", "ca", NA
 $ country                <chr> "us", "us", NA
 $ shape                  <chr> NA, NA, "circle"
 $ `duration (seconds)`   <dbl> NA, NA, NA
-$ `duration (hours/min)` <chr> "each a few seconds", "eight seconds", "1/2 seg…
-$ comments               <chr> "Driving through Plomosa Pass towards Bouse Loo…
+$ `duration (hours/min)` <chr> "each a few seconds", "eight seconds", "1/2 segundo"
+$ comments               <chr> "Driving through Plomosa Pass towards Bouse Looking NE towards Prescott about 60 degrees…
 $ `date posted`          <chr> "2/16/2000", "4/16/2005", "10/30/2006"
 $ latitude               <chr> "33.9325", "36.9741667", "4.440663"
 $ longitude              <dbl> -114.00500, -122.02972, -75.24414
@@ -3317,7 +3317,7 @@

The “problems”

-

+

@@ -3345,14 +3345,14 @@ 

Rows: 3
 Columns: 12
-$ datetime               <chr> "2/2/2000 19:33", "4/10/2005 22:52", "7/21/2006…
+$ datetime               <chr> "2/2/2000 19:33", "4/10/2005 22:52", "7/21/2006 13:00"
 $ city                   <chr> "bouse", "santa cruz", "ibague (colombia)"
 $ state                  <chr> "az", "ca", NA
 $ country                <chr> "us", "us", NA
 $ shape                  <chr> NA, NA, "circle"
 $ `duration (seconds)`   <chr> "2`", "8`", "0.5`"
-$ `duration (hours/min)` <chr> "each a few seconds", "eight seconds", "1/2 seg…
-$ comments               <chr> "Driving through Plomosa Pass towards Bouse Loo…
+$ `duration (hours/min)` <chr> "each a few seconds", "eight seconds", "1/2 segundo"
+$ comments               <chr> "Driving through Plomosa Pass towards Bouse Looking NE towards Prescott about 60 degrees…
 $ `date posted`          <chr> "2/16/2000", "4/16/2005", "10/30/2006"
 $ latitude               <chr> "33.9325", "36.9741667", "4.440663"
 $ longitude              <dbl> -114.00500, -122.02972, -75.24414
@@ -3362,18 +3362,16 @@ 

 
 
colnames(ufo)

 
-
 [1] "datetime"             "city"                 "state"               
- [4] "country"              "shape"                "duration (seconds)"  
- [7] "duration (hours/min)" "comments"             "date posted"         
-[10] "latitude"             "longitude"            "...12"               

+
 [1] "datetime"             "city"                 "state"                "country"              "shape"               
+ [6] "duration (seconds)"   "duration (hours/min)" "comments"             "date posted"          "latitude"            
+[11] "longitude"            "...12"               

 
 
ufo = clean_names(ufo)
 colnames(ufo)

 
-
 [1] "datetime"           "city"               "state"             
- [4] "country"            "shape"              "duration_seconds"  
- [7] "duration_hours_min" "comments"           "date_posted"       
-[10] "latitude"           "longitude"          "x12"               

+
 [1] "datetime"           "city"               "state"              "country"            "shape"             
+ [6] "duration_seconds"   "duration_hours_min" "comments"           "date_posted"        "latitude"          
+[11] "longitude"          "x12"               

 
 
 
@@ -3390,10 +3388,8 @@ 

 
table(gender)

 
 
gender
-     F FeMAle FEMALE     Fm      M     Ma   mAle   Male   MaLe   MALE    Man 
-    80     88     76     87     99     76     84     83     79     93     84 
- Woman 
-    71 

+     F FeMAle FEMALE     Fm      M     Ma   mAle   Male   MaLe   MALE    Man  Woman 
+    80     88     76     87     99     76     84     83     79     93     84     71

Example of Cleaning: more complicated

@@ -3485,13 +3481,11 @@

ufo[(p$row-1),] 
# A tibble: 3 × 12
-  datetime  city  state country shape duration_seconds duration_hours_… comments
-  <chr>     <chr> <chr> <chr>   <chr>            <dbl> <chr>            <chr>   
-1 2/2/2000… bouse az    us      <NA>               2   each a few seco… Driving…
-2 4/10/200… sant… ca    us      <NA>               8   eight seconds    2 red l…
-3 7/21/200… ibag… <NA>  <NA>    circ…              0.5 1/2 segundo      Viajaba…
-# … with 4 more variables: date_posted <chr>, latitude <chr>, longitude <dbl>,
-#   x12 <dbl>
+ datetime city state country shape duration_seconds duration_hours_… comments date_posted latitude longitude x12 + <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <dbl> <dbl> +1 2/2/2000 19:… bouse az us <NA> 2 each a few seco… Driving… 2/16/2000 33.9325 -114. NA +2 4/10/2005 22… sant… ca us <NA> 8 eight seconds 2 red l… 4/16/2005 36.9741… -122. NA +3 7/21/2006 13… ibag… <NA> <NA> circ… 0.5 1/2 segundo Viajaba… 10/30/2006 4.440663 -75.2 NA

Paste can add things back to variables

@@ -3695,20 +3689,18 @@ 

filter(ufo, str_detect(comments, "two aliens"))
# A tibble: 2 × 12
-  datetime  city  state country shape duration_seconds duration_hours_… comments
-  <chr>     <chr> <chr> <chr>   <chr>            <dbl> <chr>            <chr>   
-1 10/14/20… yuma  va    us      form…              300 5 minutes        ((HOAX?…
-2 7/1/2007… nort… ct    <NA>    unkn…               60 1 minute         Witness…
-# … with 4 more variables: date_posted <chr>, latitude <chr>, longitude <dbl>,
-#   x12 <dbl>
+ datetime city state country shape duration_seconds duration_hours_… comments date_posted latitude longitude x12 + <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <dbl> <dbl> +1 10/14/2006 2… yuma va us form… 300 5 minutes ((HOAX?… 4/27/2007 36.615 -82.6 NA +2 7/1/2007 23:… nort… ct <NA> unkn… 60 1 minute Witness… 10/19/2011 41.9856… -71.9 NA 
filter(ufo, str_detect(comments, "two aliens")) %>% select(comments)
# A tibble: 2 × 1
-  comments                                                                      
-  <chr>                                                                         
-1 ((HOAX??))  two aliens appeared from a bright light to peacefully investigate…
-2 Witnessed two aliens walking along baseball field fence.
+ comments + <chr> +1 ((HOAX??)) two aliens appeared from a bright light to peacefully investigate the surroundings in the woods +2 Witnessed two aliens walking along baseball field fence.

‘Find’ functions: str_subset() is easier

@@ -3766,8 +3758,8 @@ 

head(ufo$duration_hours_min, 8)
-
[1] "45 minutes"   "1-2 hrs"      "20 seconds"   "1/2 hour"     "15 minutes"  
-[6] "5 minutes"    "about 3 mins" "20 minutes"
+
[1] "45 minutes"   "1-2 hrs"      "20 seconds"   "1/2 hour"     "15 minutes"   "5 minutes"    "about 3 mins"
+[8] "20 minutes"  
ufo %>% mutate(duration_hours_min = 
                  str_replace(string = duration_hours_min, 
@@ -3776,8 +3768,8 @@ 

   pull(duration_hours_min) %>%
   head(8)
-
[1] "45 mins"      "1-2 hrs"      "20 seconds"   "1/2 hour"     "15 mins"     
-[6] "5 mins"       "about 3 mins" "20 mins"
+
[1] "45 mins"      "1-2 hrs"      "20 seconds"   "1/2 hour"     "15 mins"      "5 mins"       "about 3 mins"
+[8] "20 mins"
@@ -3804,8 +3796,7 @@ 

library(lubridate)#need to load this one!
 head(ufo$datetime)
-
[1] "10/10/1949 20:30" "10/10/1949 21:00" "10/10/1955 17:00" "10/10/1956 21:00"
-[5] "10/10/1960 20:00" "10/10/1961 19:00"
+
[1] "10/10/1949 20:30" "10/10/1949 21:00" "10/10/1955 17:00" "10/10/1956 21:00" "10/10/1960 20:00" "10/10/1961 19:00"
ufo$date_posted = mdy(ufo$date_posted)
@@ -3813,8 +3804,7 @@ 

head(ufo$date_posted)
-
[1] "2004-04-27" "2005-12-16" "2008-01-21" "2004-01-17" "2004-01-22"
-[6] "2007-04-27"
+
[1] "2004-04-27" "2005-12-16" "2008-01-21" "2004-01-17" "2004-01-22" "2007-04-27"
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z=rL^=lpn!b!HBrJB_El7>St6`Q94**_ER|=C^3^er2Yf2|Di(*iQ&f@r5G*!2@h zOJ@2j*&0z5fmzvj1NlyS3XuZIJ)k^pg@ViP1*d#URb599=Ei6Yumc#*qh=cEMw@CM z42V@k-(OT0^g^CaiZ|Kh^WjKljP}mjZhn3Sk>UXz2BENx+a%XQNd9DwVS@S;9YvH+S(tPUHBbd_OAZadVhYXQaRe^NaK;E2*K^? z*RhlQ0Eh3B0^{xM?lqYb>($+|UE8p4rmA~OV3CgQNyLq{s=QN-5POk&M?n|=Z(k0) z#x9Odv(u9ov>>Jz5x6r|qw2>X0VbchC?UBQCh4Db!v?C!X1!Z41qNx`Zq{bIn2%*- zqhqTpfRiY%2l4fuMs(qe(%#O4A`CIJ#zr==x5^TMwB< z)zb5II^}wu2{p)dfaL7tz*nYxYZ zf(=4O!j*X#Kn%-H)*S?3VUb-`PxH+w7=K_}1-{jPdR7#fSb zTQIr&SWYmC%B$Y-ssC}kYll{mv>2j0e_u&^nsx1FUKrIu>j4T~_vj})*gfi_Uy6}c z&AN*~ewQmE7?B+ztYV>m7jWNK1>-%SZx}e@NU4zuUzId&2@H)E#N3 zjG3goguH}-S_MPFC_?2h_w4tzgg=Yr&AqizFU>E_dm;4mRBM!QYv%B=bVSC-E}nC!c_Fu;JfRIA~kak%W@I3*Y7IM z^F}Kt@?G9^5d;$Ov$eclYwsNh_6bNdxiONIzbYqt7+snNR`^Ce9D1qg7zbL9_ z3C(_1e4MGATt8}m8)=(yfn83Z^+9WaXTopNZ&DN^vhXQOew|Fs@WJmGp@GbT>Z4yD z0v?&BH+eY5J0w_F(ghF0-5jyJlC?nY&qITsU6zXn{(TTSIU6}TyF0#)Iv~&MDB(e- Krj}HcLjFI~S}-aA From 05a970f53cfc70112005e13fc262df17ae64dc38 Mon Sep 17 00:00:00 2001 From: avahoffman Date: Tue, 26 Jul 2022 18:08:20 -0600 Subject: [PATCH 2/7] Update lectures --- lecture_notes/Advanced_Data_IO.R | 154 +-- lecture_notes/Advanced_Data_IO.Rmd | 90 +- lecture_notes/Advanced_Data_IO.html | 1413 +++++++-------------------- lecture_notes/Advanced_Data_IO.pdf | Bin 7430893 -> 7720822 bytes 4 files changed, 498 insertions(+), 1159 deletions(-) diff --git a/lecture_notes/Advanced_Data_IO.R b/lecture_notes/Advanced_Data_IO.R index d0d2fee..666e70e 100644 --- a/lecture_notes/Advanced_Data_IO.R +++ b/lecture_notes/Advanced_Data_IO.R @@ -1,4 +1,4 @@ -## ---- include=FALSE----------------------------------------------------------- +## ---- include=FALSE------------------------------------------------------------------------------------------------------------------ library(tidyverse) library(rvest) library(jsonlite) @@ -6,68 +6,86 @@ library(jsonlite) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ library(googlesheets4) -## ----eval=FALSE--------------------------------------------------------------- -## # Prompts a browser pop-up -## gs4_auth() +## ----eval=FALSE---------------------------------------------------------------------------------------------------------------------- +# Prompts a browser pop-up +gs4_auth() -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ # Once set up, you can automate this process by passing your email gs4_auth(email = "avamariehoffman@gmail.com") -## ----eval = FALSE------------------------------------------------------------- -## library(googledrive) -## drive_auth(email= "", -## token = readRDS("google-sheets-token.rds")) # Saved in a file +## ----eval = FALSE-------------------------------------------------------------------------------------------------------------------- +library(googledrive) +drive_auth(email= "", + token = readRDS("google-sheets-token.rds")) # Saved in a file -## ----------------------------------------------------------------------------- -sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9", - "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077") -sheet_dat_1 = read_sheet(sheet_url) +## ------------------------------------------------------------------------------------------------------------------------------------ +sheet_url <- + "https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077" +sheet_dat_1 <- read_sheet(sheet_url) head(sheet_dat_1) -## ----------------------------------------------------------------------------- -sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9", - "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077") -sheet_dat_oceania = read_sheet(sheet_url, sheet = "Oceania") +## ------------------------------------------------------------------------------------------------------------------------------------ +sheet_dat_oceania <- read_sheet(sheet_url, sheet = "Oceania") head(sheet_dat_oceania) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ +read_sheet(sheet_url, sheet = "Oceania", range = cell_rows(1:4)) + + +## ------------------------------------------------------------------------------------------------------------------------------------ +read_sheet(sheet_url, sheet = "Oceania", range = cell_cols("A:B")) + + +## ------------------------------------------------------------------------------------------------------------------------------------ sheet_names(sheet_url) -## ----------------------------------------------------------------------------- -gapminder_sheets = sheet_names(sheet_url) +## ------------------------------------------------------------------------------------------------------------------------------------ +gapminder_sheets <- sheet_names(sheet_url) -data_list = list() +data_list <- list() for(g_sheet in gapminder_sheets){ data_list[[g_sheet]] = read_sheet(sheet_url, sheet = g_sheet) } -str(data_list) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ str(data_list) -## ----------------------------------------------------------------------------- -sheet_dat_oceania = sheet_dat_oceania %>% +## ----eval=FALSE---------------------------------------------------------------------------------------------------------------------- +data_list[[{sheet}]] +# OR +data_list${sheet} + + +## ---- out.width="80%", echo=FALSE, fig.alt='.'--------------------------------------------------------------------------------------- +ottrpal::include_slide("https://docs.google.com/presentation/d/104LQkFTsC5R9vAC4HHj4mK7IjCTH55X6BkrAb3aDd6E/edit#slide=id.g13f84314e00_0_0") + + +## ------------------------------------------------------------------------------------------------------------------------------------ +sheet_dat_oceania <- data_list$Oceania + +sheet_dat_oceania <- sheet_dat_oceania %>% mutate(lifeExp_days = lifeExp * 365) -sheet_out = gs4_create("Oceania-days", + +sheet_out <- gs4_create("Oceania-days", sheets = list(Oceania_days = sheet_dat_oceania)) -## ----eval = FALSE------------------------------------------------------------- -## # Opens a browser window -## gs4_browse(sheet_out) +## ----eval = FALSE-------------------------------------------------------------------------------------------------------------------- +# Opens a browser window +gs4_browse(sheet_out) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ sheet_append(sheet_out, data = sheet_dat_oceania, sheet = "Oceania_days") @@ -75,21 +93,27 @@ sheet_append(sheet_out, data = sheet_dat_oceania, sheet = "Oceania_days") -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ #install.packages("jsonlite") library(jsonlite) -jsonData <- fromJSON(paste0("https://raw.githubusercontent.com/Biuni", - "/PokemonGO-Pokedex/master/pokedex.json")) +jsonData <- + fromJSON("https://raw.githubusercontent.com/Biuni/PokemonGO-Pokedex/master/pokedex.json") head(jsonData) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ dim(jsonData$pokemon) +class(jsonData$pokemon) + +jsonData$pokemon %>% filter(type == "Fire") %>% select(!(img)) + + +## ------------------------------------------------------------------------------------------------------------------------------------ class(jsonData$pokemon$type) # Can be lists jsonData$pokemon$type -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ class(jsonData$pokemon$next_evolution[[1]]) # Or lists of data.frames! jsonData$pokemon$next_evolution @@ -104,21 +128,21 @@ jsonData$pokemon$next_evolution -## ----------------------------------------------------------------------------- -recount_url = "http://bowtie-bio.sourceforge.net/recount/" +## ------------------------------------------------------------------------------------------------------------------------------------ +recount_url <- "http://bowtie-bio.sourceforge.net/recount/" # install.packages("rvest") library(rvest) htmlfile = read_html(recount_url) -nds = html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table') -dat = html_table(nds) -dat = as.data.frame(dat) +nds <- html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table') +dat <- html_table(nds) +dat <- as.data.frame(dat) head(dat) -## ----------------------------------------------------------------------------- -colnames(dat) = as.character(dat[1,]) -dat = dat[-1,] +## ------------------------------------------------------------------------------------------------------------------------------------ +colnames(dat) <- as.character(dat[1,]) +dat <- dat[-1,] head(dat) @@ -138,33 +162,33 @@ head(dat) -## ----------------------------------------------------------------------------- +## ------------------------------------------------------------------------------------------------------------------------------------ #install.packages("httr") library(httr) # Requests a random cat fact -query_url = "https://thatcopy.pw/catapi/rest/" +query_url <- "https://thatcopy.pw/catapi/rest/" -req = GET(query_url) +req <- GET(query_url) content(req) -## ---- eval = FALSE------------------------------------------------------------ -## # install.packages("twitteR") -## library(twitteR) -## # Supplied by Twitter -## setup_twitter_oauth("API key", "API secret") -## -## searchTwitter("crab cake", geocode="39.290692,-76.610221,5mi") - - -## ---- eval = FALSE------------------------------------------------------------ -## # install.packages("tidycensus") -## library(tidycensus) -## # Supplied by census.gov -## census_api_key("YOUR API KEY GOES HERE") -## -## get_decennial(geography = "state", -## variables = "P013001", # code for median age -## year = 2010) +## ---- eval = FALSE------------------------------------------------------------------------------------------------------------------- +# install.packages("twitteR") +library(twitteR) +# Supplied by Twitter +setup_twitter_oauth("API key", "API secret") + +searchTwitter("crab cake", geocode="39.290692,-76.610221,5mi") + + +## ---- eval = FALSE------------------------------------------------------------------------------------------------------------------- +# install.packages("tidycensus") +library(tidycensus) +# Supplied by census.gov +census_api_key("YOUR API KEY GOES HERE") + +get_decennial(geography = "state", + variables = "P013001", # code for median age + year = 2010) diff --git a/lecture_notes/Advanced_Data_IO.Rmd b/lecture_notes/Advanced_Data_IO.Rmd index a16bcb1..4669579 100644 --- a/lecture_notes/Advanced_Data_IO.Rmd +++ b/lecture_notes/Advanced_Data_IO.Rmd @@ -5,6 +5,8 @@ output: ioslides_presentation: css: styles.css widescreen: yes +editor_options: + chunk_output_type: console --- ```{r, echo = FALSE, include=FALSE, purl=FALSE} @@ -20,7 +22,7 @@ library(jsonlite) # Google Sheets ---- +## {.small} ```{r, out.width="100%", echo = FALSE, purl=FALSE} knitr::include_graphics("media/AdvancedIO_googlesheet.png") @@ -30,7 +32,7 @@ https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9AZqTqS3mbMF3zt2db48ZP5v3rkrA ## Reading data with the googlesheets4 package -First, set up Google credentials +First, set up Google credentials. This doesn't currently work with AnVIL. ```{r} library(googlesheets4) @@ -54,14 +56,14 @@ drive_auth(email= "", token = readRDS("google-sheets-token.rds")) # Saved in a file ``` -## Reading data with the googlesheets4 package +## Reading data with the googlesheets4 package {.smaller} -Read in using `googlesheets4::read_sheet` +Read in using `read_sheet()` ```{r} -sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9", - "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077") -sheet_dat_1 = read_sheet(sheet_url) +sheet_url <- + "https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077" +sheet_dat_1 <- read_sheet(sheet_url) head(sheet_dat_1) ``` @@ -70,15 +72,25 @@ head(sheet_dat_1) Specify the sheet name if necessary: ```{r} -sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9", - "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077") -sheet_dat_oceania = read_sheet(sheet_url, sheet = "Oceania") +sheet_dat_oceania <- read_sheet(sheet_url, sheet = "Oceania") head(sheet_dat_oceania) ``` +## Pull in a subset of data: rows + +```{r} +read_sheet(sheet_url, sheet = "Oceania", range = cell_rows(1:4)) +``` + +## Pull in a subset of data: columns + +```{r} +read_sheet(sheet_url, sheet = "Oceania", range = cell_cols("A:B")) +``` + ## Reading data with the googlesheets4 package -Alternatively, list out the sheet names using `sheet_names()`. +List out the sheet names using `sheet_names()`. ```{r} sheet_names(sheet_url) @@ -89,13 +101,12 @@ sheet_names(sheet_url) Iterate through the sheet names: ```{r} -gapminder_sheets = sheet_names(sheet_url) +gapminder_sheets <- sheet_names(sheet_url) -data_list = list() +data_list <- list() for(g_sheet in gapminder_sheets){ data_list[[g_sheet]] = read_sheet(sheet_url, sheet = g_sheet) } -str(data_list) ``` ## Reading data with the googlesheets4 package @@ -106,12 +117,29 @@ Iterate through the sheet names: str(data_list) ``` +## Reading data with the googlesheets4 package + +Pull out sheets as needed: + +```{r eval=FALSE} +data_list[[{sheet}]] +# OR +data_list${sheet} +``` + +```{r, out.width="80%", echo=FALSE, fig.alt='.'} +ottrpal::include_slide("https://docs.google.com/presentation/d/104LQkFTsC5R9vAC4HHj4mK7IjCTH55X6BkrAb3aDd6E/edit#slide=id.g13f84314e00_0_0") +``` + ## Writing data with the googlesheets4 package ```{r} -sheet_dat_oceania = sheet_dat_oceania %>% +sheet_dat_oceania <- data_list$Oceania + +sheet_dat_oceania <- sheet_dat_oceania %>% mutate(lifeExp_days = lifeExp * 365) -sheet_out = gs4_create("Oceania-days", + +sheet_out <- gs4_create("Oceania-days", sheets = list(Oceania_days = sheet_dat_oceania)) ``` ```{r eval = FALSE} @@ -149,13 +177,13 @@ knitr::include_graphics("github_json.png") https://docs.github.com/en/rest/reference/search ---- +## {.small} ```{r} #install.packages("jsonlite") library(jsonlite) -jsonData <- fromJSON(paste0("https://raw.githubusercontent.com/Biuni", - "/PokemonGO-Pokedex/master/pokedex.json")) +jsonData <- + fromJSON("https://raw.githubusercontent.com/Biuni/PokemonGO-Pokedex/master/pokedex.json") head(jsonData) ``` @@ -163,6 +191,14 @@ head(jsonData) ```{r} dim(jsonData$pokemon) +class(jsonData$pokemon) + +jsonData$pokemon %>% filter(type == "Fire") %>% select(!(img)) +``` + +## Going deeper.. + +```{r} class(jsonData$pokemon$type) # Can be lists jsonData$pokemon$type ``` @@ -251,22 +287,22 @@ https://rvest.tidyverse.org/articles/selectorgadget.html ## rvest package ```{r} -recount_url = "http://bowtie-bio.sourceforge.net/recount/" +recount_url <- "http://bowtie-bio.sourceforge.net/recount/" # install.packages("rvest") library(rvest) htmlfile = read_html(recount_url) -nds = html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table') -dat = html_table(nds) -dat = as.data.frame(dat) +nds <- html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table') +dat <- html_table(nds) +dat <- as.data.frame(dat) head(dat) ``` ## Little cleanup ```{r} -colnames(dat) = as.character(dat[1,]) -dat = dat[-1,] +colnames(dat) <- as.character(dat[1,]) +dat <- dat[-1,] head(dat) ``` @@ -336,9 +372,9 @@ https://github.com/ThatCopy/catAPI/wiki/Usage library(httr) # Requests a random cat fact -query_url = "https://thatcopy.pw/catapi/rest/" +query_url <- "https://thatcopy.pw/catapi/rest/" -req = GET(query_url) +req <- GET(query_url) content(req) ``` diff --git a/lecture_notes/Advanced_Data_IO.html b/lecture_notes/Advanced_Data_IO.html index 75a50c7..6114b9c 100644 --- a/lecture_notes/Advanced_Data_IO.html +++ b/lecture_notes/Advanced_Data_IO.html @@ -3098,6 +3098,10 @@ display: list-item; } + details > summary > p:only-child { + display: inline; + } + slides > slide { -webkit-transition: all 0.4s ease-in-out; -moz-transition: all 0.4s ease-in-out; @@ -3127,6 +3131,7 @@ pre > code.sourceCode { white-space: pre; position: relative; } pre > code.sourceCode > span { display: inline-block; line-height: 1.25; } pre > code.sourceCode > span:empty { height: 1.2em; } + .sourceCode { overflow: visible; } code.sourceCode > span { color: inherit; text-decoration: inherit; } div.sourceCode { margin: 1em 0; } pre.sourceCode { margin: 0; } @@ -3229,7 +3234,10 @@ color: black; } .left-half{ float: left; width: 48%; } -.right-half{ float: right; width: 48%; } +.right-half{ float: right; width: 48%; } +.codesmall pre { +font-size: 16px; +} @@ -3248,7 +3256,7 @@

    Google Sheets

    -

    +

    @@ -3256,7 +3264,7 @@

    Reading data with the googlesheets4 package

    -

    First, set up Google credentials

    +

    First, set up Google credentials. This doesn’t currently work with AnVIL.

    library(googlesheets4)
    @@ -3274,21 +3282,23 @@

    drive_auth(email= "<email>", token = readRDS("google-sheets-token.rds")) # Saved in a file -

    Reading data with the googlesheets4 package

    +

    Reading data with the googlesheets4 package

    + +

    Read in using read_sheet()

    -

    Read in using googlesheets4::read_sheet

    +
    sheet_url <- 
+  "https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077"
+sheet_dat_1 <- read_sheet(sheet_url)
    -
    sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9",
-                   "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077")
-sheet_dat_1 = read_sheet(sheet_url)
    +
    Auto-refreshing stale OAuth token.
    -
    Reading from "gapminder"
    +
    ✔ Reading from "gapminder".
    -
    Range "Africa"
    +
    ✔ Range 'Africa'.
    head(sheet_dat_1)
    -
    # A tibble: 6 x 6
+
    # A tibble: 6 × 6
   country continent  year lifeExp      pop gdpPercap
   <chr>   <chr>     <dbl>   <dbl>    <dbl>     <dbl>
 1 Algeria Africa     1952    43.1  9279525     2449.
@@ -3302,17 +3312,15 @@ 
    
 
 
    Specify the sheet name if necessary:
    
 
-
    sheet_url = paste0("https://docs.google.com/spreadsheets/d/1U6Cf_qEOhiR9",
-                   "AZqTqS3mbMF3zt2db48ZP5v3rkrAEJY/edit#gid=780868077")
-sheet_dat_oceania = read_sheet(sheet_url, sheet = "Oceania")
    
+
    sheet_dat_oceania <- read_sheet(sheet_url, sheet = "Oceania")
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Oceania'"
    
+
    ✔ Range ''Oceania''.
    
 
 
    head(sheet_dat_oceania)
    
 
-
    # A tibble: 6 x 6
+
    # A tibble: 6 × 6
   country   continent  year lifeExp      pop gdpPercap
   <chr>     <chr>     <dbl>   <dbl>    <dbl>     <dbl>
 1 Australia Oceania    1952    69.1  8691212    10040.
@@ -3322,9 +3330,47 @@ 
    
 5 Australia Oceania    1972    71.9 13177000    16789.
 6 Australia Oceania    1977    73.5 14074100    18334.
    
 
+

    Pull in a subset of data: rows

    + +
    read_sheet(sheet_url, sheet = "Oceania", range =  cell_rows(1:4))
    + +
    ✔ Reading from "gapminder".
    + +
    ✔ Range ''Oceania'!1:4'.
    + +
    # A tibble: 3 × 6
+  country   continent  year lifeExp      pop gdpPercap
+  <chr>     <chr>     <dbl>   <dbl>    <dbl>     <dbl>
+1 Australia Oceania    1952    69.1  8691212    10040.
+2 Australia Oceania    1957    70.3  9712569    10950.
+3 Australia Oceania    1962    70.9 10794968    12217.
    + +

    Pull in a subset of data: columns

    + +
    read_sheet(sheet_url, sheet = "Oceania", range =  cell_cols("A:B"))
    + +
    ✔ Reading from "gapminder".
    + +
    ✔ Range ''Oceania'!A:B'.
    + +
    # A tibble: 24 × 2
+   country   continent
+   <chr>     <chr>    
+ 1 Australia Oceania  
+ 2 Australia Oceania  
+ 3 Australia Oceania  
+ 4 Australia Oceania  
+ 5 Australia Oceania  
+ 6 Australia Oceania  
+ 7 Australia Oceania  
+ 8 Australia Oceania  
+ 9 Australia Oceania  
+10 Australia Oceania  
+# … with 14 more rows
    +

    Reading data with the googlesheets4 package

    -

    Alternatively, list out the sheet names using sheet_names().

    +

    List out the sheet names using sheet_names().

    sheet_names(sheet_url)
    @@ -3334,71 +3380,32 @@

    Iterate through the sheet names:

    -
    gapminder_sheets = sheet_names(sheet_url)
+
    gapminder_sheets <- sheet_names(sheet_url)
 
-data_list = list()
+data_list <- list()
 for(g_sheet in gapminder_sheets){
   data_list[[g_sheet]] = read_sheet(sheet_url, sheet = g_sheet)
 }
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Africa'"
    
+
    ✔ Range ''Africa''.
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Americas'"
    
+
    ✔ Range ''Americas''.
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Asia'"
    
+
    ✔ Range ''Asia''.
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Europe'"
    
+
    ✔ Range ''Europe''.
    
 
-
    Reading from "gapminder"
    
+
    ✔ Reading from "gapminder".
    
 
-
    Range "'Oceania'"
    
-
-
    str(data_list)
    
-
-
    List of 5
- $ Africa  : tibble [624 × 6] (S3: tbl_df/tbl/data.frame)
-  ..$ country  : chr [1:624] "Algeria" "Algeria" "Algeria" "Algeria" ...
-  ..$ continent: chr [1:624] "Africa" "Africa" "Africa" "Africa" ...
-  ..$ year     : num [1:624] 1952 1957 1962 1967 1972 ...
-  ..$ lifeExp  : num [1:624] 43.1 45.7 48.3 51.4 54.5 ...
-  ..$ pop      : num [1:624] 9279525 10270856 11000948 12760499 14760787 ...
-  ..$ gdpPercap: num [1:624] 2449 3014 2551 3247 4183 ...
- $ Americas: tibble [300 × 6] (S3: tbl_df/tbl/data.frame)
-  ..$ country  : chr [1:300] "Argentina" "Argentina" "Argentina" "Argentina" ...
-  ..$ continent: chr [1:300] "Americas" "Americas" "Americas" "Americas" ...
-  ..$ year     : num [1:300] 1952 1957 1962 1967 1972 ...
-  ..$ lifeExp  : num [1:300] 62.5 64.4 65.1 65.6 67.1 ...
-  ..$ pop      : num [1:300] 17876956 19610538 21283783 22934225 24779799 ...
-  ..$ gdpPercap: num [1:300] 5911 6857 7133 8053 9443 ...
- $ Asia    : tibble [396 × 6] (S3: tbl_df/tbl/data.frame)
-  ..$ country  : chr [1:396] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
-  ..$ continent: chr [1:396] "Asia" "Asia" "Asia" "Asia" ...
-  ..$ year     : num [1:396] 1952 1957 1962 1967 1972 ...
-  ..$ lifeExp  : num [1:396] 28.8 30.3 32 34 36.1 ...
-  ..$ pop      : num [1:396] 8425333 9240934 10267083 11537966 13079460 ...
-  ..$ gdpPercap: num [1:396] 779 821 853 836 740 ...
- $ Europe  : tibble [360 × 6] (S3: tbl_df/tbl/data.frame)
-  ..$ country  : chr [1:360] "Albania" "Albania" "Albania" "Albania" ...
-  ..$ continent: chr [1:360] "Europe" "Europe" "Europe" "Europe" ...
-  ..$ year     : num [1:360] 1952 1957 1962 1967 1972 ...
-  ..$ lifeExp  : num [1:360] 55.2 59.3 64.8 66.2 67.7 ...
-  ..$ pop      : num [1:360] 1282697 1476505 1728137 1984060 2263554 ...
-  ..$ gdpPercap: num [1:360] 1601 1942 2313 2760 3313 ...
- $ Oceania : tibble [24 × 6] (S3: tbl_df/tbl/data.frame)
-  ..$ country  : chr [1:24] "Australia" "Australia" "Australia" "Australia" ...
-  ..$ continent: chr [1:24] "Oceania" "Oceania" "Oceania" "Oceania" ...
-  ..$ year     : num [1:24] 1952 1957 1962 1967 1972 ...
-  ..$ lifeExp  : num [1:24] 69.1 70.3 70.9 71.1 71.9 ...
-  ..$ pop      : num [1:24] 8691212 9712569 10794968 11872264 13177000 ...
-  ..$ gdpPercap: num [1:24] 10040 10950 12217 14526 16789 ...
    
+
    ✔ Range ''Oceania''.

    Reading data with the googlesheets4 package

    @@ -3443,14 +3450,27 @@

    ..$ pop : num [1:24] 8691212 9712569 10794968 11872264 13177000 ... ..$ gdpPercap: num [1:24] 10040 10950 12217 14526 16789 ... +

    Reading data with the googlesheets4 package

    + +

    Pull out sheets as needed:

    + +
    data_list[[{sheet}]]
+# OR
+data_list${sheet}
    + +

    .

    +

    Writing data with the googlesheets4 package

    -
    sheet_dat_oceania = sheet_dat_oceania %>%
+
    sheet_dat_oceania <- data_list$Oceania
+
+sheet_dat_oceania <- sheet_dat_oceania %>%
   mutate(lifeExp_days = lifeExp * 365)
-sheet_out = gs4_create("Oceania-days", 
+
+sheet_out <- gs4_create("Oceania-days", 
                        sheets = list(Oceania_days = sheet_dat_oceania))
    
 
-
    Creating new Sheet: "Oceania-days"
    
+
    ✔ Creating new Sheet: "Oceania-days".
    
 
 
    # Opens a browser window
 gs4_browse(sheet_out)
    
@@ -3459,9 +3479,9 @@ 
    
 
 
    sheet_append(sheet_out, data = sheet_dat_oceania, sheet = "Oceania_days")
    
 
-
    Writing to "Oceania-days"
    
+
    ✔ Writing to "Oceania-days".
    
 
-
    Appending 24 row(s) to "Oceania_days"
    
+
    ✔ Appending 24 rows to 'Oceania_days'.

    JHU Tidyverse Book

    +

    #install.packages("jsonlite")
 library(jsonlite)
-jsonData <- fromJSON(paste0("https://raw.githubusercontent.com/Biuni",
-                            "/PokemonGO-Pokedex/master/pokedex.json"))
+jsonData <-
+  fromJSON("https://raw.githubusercontent.com/Biuni/PokemonGO-Pokedex/master/pokedex.json")
 head(jsonData)
    $pokemon
-     id num               name                                              img
-1     1 001          Bulbasaur http://www.serebii.net/pokemongo/pokemon/001.png
-2     2 002            Ivysaur http://www.serebii.net/pokemongo/pokemon/002.png
-3     3 003           Venusaur http://www.serebii.net/pokemongo/pokemon/003.png
-4     4 004         Charmander http://www.serebii.net/pokemongo/pokemon/004.png
-5     5 005         Charmeleon http://www.serebii.net/pokemongo/pokemon/005.png
-6     6 006          Charizard http://www.serebii.net/pokemongo/pokemon/006.png
-7     7 007           Squirtle http://www.serebii.net/pokemongo/pokemon/007.png
-8     8 008          Wartortle http://www.serebii.net/pokemongo/pokemon/008.png
-9     9 009          Blastoise http://www.serebii.net/pokemongo/pokemon/009.png
-10   10 010           Caterpie http://www.serebii.net/pokemongo/pokemon/010.png
-11   11 011            Metapod http://www.serebii.net/pokemongo/pokemon/011.png
-12   12 012         Butterfree http://www.serebii.net/pokemongo/pokemon/012.png
-13   13 013             Weedle http://www.serebii.net/pokemongo/pokemon/013.png
-14   14 014             Kakuna http://www.serebii.net/pokemongo/pokemon/014.png
-15   15 015           Beedrill http://www.serebii.net/pokemongo/pokemon/015.png
-16   16 016             Pidgey http://www.serebii.net/pokemongo/pokemon/016.png
-17   17 017          Pidgeotto http://www.serebii.net/pokemongo/pokemon/017.png
-18   18 018            Pidgeot http://www.serebii.net/pokemongo/pokemon/018.png
-19   19 019            Rattata http://www.serebii.net/pokemongo/pokemon/019.png
-20   20 020           Raticate http://www.serebii.net/pokemongo/pokemon/020.png
-21   21 021            Spearow http://www.serebii.net/pokemongo/pokemon/021.png
-22   22 022             Fearow http://www.serebii.net/pokemongo/pokemon/022.png
-23   23 023              Ekans http://www.serebii.net/pokemongo/pokemon/023.png
-24   24 024              Arbok http://www.serebii.net/pokemongo/pokemon/024.png
-25   25 025            Pikachu http://www.serebii.net/pokemongo/pokemon/025.png
-26   26 026             Raichu http://www.serebii.net/pokemongo/pokemon/026.png
-27   27 027          Sandshrew http://www.serebii.net/pokemongo/pokemon/027.png
-28   28 028          Sandslash http://www.serebii.net/pokemongo/pokemon/028.png
-29   29 029 Nidoran ♀ (Female) http://www.serebii.net/pokemongo/pokemon/029.png
-30   30 030           Nidorina http://www.serebii.net/pokemongo/pokemon/030.png
-31   31 031          Nidoqueen http://www.serebii.net/pokemongo/pokemon/031.png
-32   32 032   Nidoran ♂ (Male) http://www.serebii.net/pokemongo/pokemon/032.png
-33   33 033           Nidorino http://www.serebii.net/pokemongo/pokemon/033.png
-34   34 034           Nidoking http://www.serebii.net/pokemongo/pokemon/034.png
-35   35 035           Clefairy http://www.serebii.net/pokemongo/pokemon/035.png
-36   36 036           Clefable http://www.serebii.net/pokemongo/pokemon/036.png
-37   37 037             Vulpix http://www.serebii.net/pokemongo/pokemon/037.png
-38   38 038          Ninetales http://www.serebii.net/pokemongo/pokemon/038.png
-39   39 039         Jigglypuff http://www.serebii.net/pokemongo/pokemon/039.png
-40   40 040         Wigglytuff http://www.serebii.net/pokemongo/pokemon/040.png
-41   41 041              Zubat http://www.serebii.net/pokemongo/pokemon/041.png
-42   42 042             Golbat http://www.serebii.net/pokemongo/pokemon/042.png
-43   43 043             Oddish http://www.serebii.net/pokemongo/pokemon/043.png
-44   44 044              Gloom http://www.serebii.net/pokemongo/pokemon/044.png
-45   45 045          Vileplume http://www.serebii.net/pokemongo/pokemon/045.png
-46   46 046              Paras http://www.serebii.net/pokemongo/pokemon/046.png
-47   47 047           Parasect http://www.serebii.net/pokemongo/pokemon/047.png
-48   48 048            Venonat http://www.serebii.net/pokemongo/pokemon/048.png
-49   49 049           Venomoth http://www.serebii.net/pokemongo/pokemon/049.png
-50   50 050            Diglett http://www.serebii.net/pokemongo/pokemon/050.png
-51   51 051            Dugtrio http://www.serebii.net/pokemongo/pokemon/051.png
-52   52 052             Meowth http://www.serebii.net/pokemongo/pokemon/052.png
-53   53 053            Persian http://www.serebii.net/pokemongo/pokemon/053.png
-54   54 054            Psyduck http://www.serebii.net/pokemongo/pokemon/054.png
-55   55 055            Golduck http://www.serebii.net/pokemongo/pokemon/055.png
-56   56 056             Mankey http://www.serebii.net/pokemongo/pokemon/056.png
-57   57 057           Primeape http://www.serebii.net/pokemongo/pokemon/057.png
-58   58 058          Growlithe http://www.serebii.net/pokemongo/pokemon/058.png
-59   59 059           Arcanine http://www.serebii.net/pokemongo/pokemon/059.png
-60   60 060            Poliwag http://www.serebii.net/pokemongo/pokemon/060.png
-61   61 061          Poliwhirl http://www.serebii.net/pokemongo/pokemon/061.png
-62   62 062          Poliwrath http://www.serebii.net/pokemongo/pokemon/062.png
-63   63 063               Abra http://www.serebii.net/pokemongo/pokemon/063.png
-64   64 064            Kadabra http://www.serebii.net/pokemongo/pokemon/064.png
-65   65 065           Alakazam http://www.serebii.net/pokemongo/pokemon/065.png
-66   66 066             Machop http://www.serebii.net/pokemongo/pokemon/066.png
-67   67 067            Machoke http://www.serebii.net/pokemongo/pokemon/067.png
-68   68 068            Machamp http://www.serebii.net/pokemongo/pokemon/068.png
-69   69 069         Bellsprout http://www.serebii.net/pokemongo/pokemon/069.png
-70   70 070         Weepinbell http://www.serebii.net/pokemongo/pokemon/070.png
-71   71 071         Victreebel http://www.serebii.net/pokemongo/pokemon/071.png
-72   72 072          Tentacool http://www.serebii.net/pokemongo/pokemon/072.png
-73   73 073         Tentacruel http://www.serebii.net/pokemongo/pokemon/073.png
-74   74 074            Geodude http://www.serebii.net/pokemongo/pokemon/074.png
-75   75 075           Graveler http://www.serebii.net/pokemongo/pokemon/075.png
-76   76 076              Golem http://www.serebii.net/pokemongo/pokemon/076.png
-77   77 077             Ponyta http://www.serebii.net/pokemongo/pokemon/077.png
-78   78 078           Rapidash http://www.serebii.net/pokemongo/pokemon/078.png
-79   79 079           Slowpoke http://www.serebii.net/pokemongo/pokemon/079.png
-80   80 080            Slowbro http://www.serebii.net/pokemongo/pokemon/080.png
-81   81 081          Magnemite http://www.serebii.net/pokemongo/pokemon/081.png
-82   82 082           Magneton http://www.serebii.net/pokemongo/pokemon/082.png
-83   83 083         Farfetch'd http://www.serebii.net/pokemongo/pokemon/083.png
-84   84 084              Doduo http://www.serebii.net/pokemongo/pokemon/084.png
-85   85 085             Dodrio http://www.serebii.net/pokemongo/pokemon/085.png
-86   86 086               Seel http://www.serebii.net/pokemongo/pokemon/086.png
-87   87 087            Dewgong http://www.serebii.net/pokemongo/pokemon/087.png
-88   88 088             Grimer http://www.serebii.net/pokemongo/pokemon/088.png
-89   89 089                Muk http://www.serebii.net/pokemongo/pokemon/089.png
-90   90 090           Shellder http://www.serebii.net/pokemongo/pokemon/090.png
-91   91 091           Cloyster http://www.serebii.net/pokemongo/pokemon/091.png
-92   92 092             Gastly http://www.serebii.net/pokemongo/pokemon/092.png
-93   93 093            Haunter http://www.serebii.net/pokemongo/pokemon/093.png
-94   94 094             Gengar http://www.serebii.net/pokemongo/pokemon/094.png
-95   95 095               Onix http://www.serebii.net/pokemongo/pokemon/095.png
-96   96 096            Drowzee http://www.serebii.net/pokemongo/pokemon/096.png
-97   97 097              Hypno http://www.serebii.net/pokemongo/pokemon/097.png
-98   98 098             Krabby http://www.serebii.net/pokemongo/pokemon/098.png
-99   99 099            Kingler http://www.serebii.net/pokemongo/pokemon/099.png
-100 100 100            Voltorb http://www.serebii.net/pokemongo/pokemon/100.png
-101 101 101          Electrode http://www.serebii.net/pokemongo/pokemon/101.png
-102 102 102          Exeggcute http://www.serebii.net/pokemongo/pokemon/102.png
-103 103 103          Exeggutor http://www.serebii.net/pokemongo/pokemon/103.png
-104 104 104             Cubone http://www.serebii.net/pokemongo/pokemon/104.png
-105 105 105            Marowak http://www.serebii.net/pokemongo/pokemon/105.png
-106 106 106          Hitmonlee http://www.serebii.net/pokemongo/pokemon/106.png
-107 107 107         Hitmonchan http://www.serebii.net/pokemongo/pokemon/107.png
-108 108 108          Lickitung http://www.serebii.net/pokemongo/pokemon/108.png
-109 109 109            Koffing http://www.serebii.net/pokemongo/pokemon/109.png
-110 110 110            Weezing http://www.serebii.net/pokemongo/pokemon/110.png
-111 111 111            Rhyhorn http://www.serebii.net/pokemongo/pokemon/111.png
-112 112 112             Rhydon http://www.serebii.net/pokemongo/pokemon/112.png
-113 113 113            Chansey http://www.serebii.net/pokemongo/pokemon/113.png
-114 114 114            Tangela http://www.serebii.net/pokemongo/pokemon/114.png
-115 115 115         Kangaskhan http://www.serebii.net/pokemongo/pokemon/115.png
-116 116 116             Horsea http://www.serebii.net/pokemongo/pokemon/116.png
-117 117 117             Seadra http://www.serebii.net/pokemongo/pokemon/117.png
-118 118 118            Goldeen http://www.serebii.net/pokemongo/pokemon/118.png
-119 119 119            Seaking http://www.serebii.net/pokemongo/pokemon/119.png
-120 120 120             Staryu http://www.serebii.net/pokemongo/pokemon/120.png
-121 121 121            Starmie http://www.serebii.net/pokemongo/pokemon/121.png
-122 122 122           Mr. Mime http://www.serebii.net/pokemongo/pokemon/122.png
-123 123 123            Scyther http://www.serebii.net/pokemongo/pokemon/123.png
-124 124 124               Jynx http://www.serebii.net/pokemongo/pokemon/124.png
-125 125 125         Electabuzz http://www.serebii.net/pokemongo/pokemon/125.png
-126 126 126             Magmar http://www.serebii.net/pokemongo/pokemon/126.png
-127 127 127             Pinsir http://www.serebii.net/pokemongo/pokemon/127.png
-128 128 128             Tauros http://www.serebii.net/pokemongo/pokemon/128.png
-129 129 129           Magikarp http://www.serebii.net/pokemongo/pokemon/129.png
-130 130 130           Gyarados http://www.serebii.net/pokemongo/pokemon/130.png
-131 131 131             Lapras http://www.serebii.net/pokemongo/pokemon/131.png
-132 132 132              Ditto http://www.serebii.net/pokemongo/pokemon/132.png
-133 133 133              Eevee http://www.serebii.net/pokemongo/pokemon/133.png
-134 134 134           Vaporeon http://www.serebii.net/pokemongo/pokemon/134.png
-135 135 135            Jolteon http://www.serebii.net/pokemongo/pokemon/135.png
-136 136 136            Flareon http://www.serebii.net/pokemongo/pokemon/136.png
-137 137 137            Porygon http://www.serebii.net/pokemongo/pokemon/137.png
-138 138 138            Omanyte http://www.serebii.net/pokemongo/pokemon/138.png
-139 139 139            Omastar http://www.serebii.net/pokemongo/pokemon/139.png
-140 140 140             Kabuto http://www.serebii.net/pokemongo/pokemon/140.png
-141 141 141           Kabutops http://www.serebii.net/pokemongo/pokemon/141.png
-142 142 142         Aerodactyl http://www.serebii.net/pokemongo/pokemon/142.png
-143 143 143            Snorlax http://www.serebii.net/pokemongo/pokemon/143.png
-144 144 144           Articuno http://www.serebii.net/pokemongo/pokemon/144.png
-145 145 145             Zapdos http://www.serebii.net/pokemongo/pokemon/145.png
-146 146 146            Moltres http://www.serebii.net/pokemongo/pokemon/146.png
-147 147 147            Dratini http://www.serebii.net/pokemongo/pokemon/147.png
-148 148 148          Dragonair http://www.serebii.net/pokemongo/pokemon/148.png
-149 149 149          Dragonite http://www.serebii.net/pokemongo/pokemon/149.png
-150 150 150             Mewtwo http://www.serebii.net/pokemongo/pokemon/150.png
-151 151 151                Mew http://www.serebii.net/pokemongo/pokemon/151.png
-                type height   weight                    candy candy_count
-1      Grass, Poison 0.71 m   6.9 kg          Bulbasaur Candy          25
-2      Grass, Poison 0.99 m  13.0 kg          Bulbasaur Candy         100
-3      Grass, Poison 2.01 m 100.0 kg          Bulbasaur Candy          NA
-4               Fire 0.61 m   8.5 kg         Charmander Candy          25
-5               Fire 1.09 m  19.0 kg         Charmander Candy         100
-6       Fire, Flying 1.70 m  90.5 kg         Charmander Candy          NA
-7              Water 0.51 m   9.0 kg           Squirtle Candy          25
-8              Water 0.99 m  22.5 kg           Squirtle Candy         100
-9              Water 1.60 m  85.5 kg           Squirtle Candy          NA
-10               Bug 0.30 m   2.9 kg           Caterpie Candy          12
-11               Bug 0.71 m   9.9 kg           Caterpie Candy          50
-12       Bug, Flying 1.09 m  32.0 kg           Caterpie Candy          NA
-13       Bug, Poison 0.30 m   3.2 kg             Weedle Candy          12
-14       Bug, Poison 0.61 m  10.0 kg             Weedle Candy          50
-15       Bug, Poison 0.99 m  29.5 kg             Weedle Candy          NA
-16    Normal, Flying 0.30 m   1.8 kg             Pidgey Candy          12
-17    Normal, Flying 1.09 m  30.0 kg             Pidgey Candy          50
-18    Normal, Flying 1.50 m  39.5 kg             Pidgey Candy          NA
-19            Normal 0.30 m   3.5 kg            Rattata Candy          25
-20            Normal 0.71 m  18.5 kg            Rattata Candy          NA
-21    Normal, Flying 0.30 m   2.0 kg            Spearow Candy          50
-22    Normal, Flying 1.19 m  38.0 kg            Spearow Candy          NA
-23            Poison 2.01 m   6.9 kg              Ekans Candy          50
-24            Poison 3.51 m  65.0 kg              Ekans Candy          NA
-25          Electric 0.41 m   6.0 kg            Pikachu Candy          50
-26          Electric 0.79 m  30.0 kg            Pikachu Candy          NA
-27            Ground 0.61 m  12.0 kg          Sandshrew Candy          50
-28            Ground 0.99 m  29.5 kg          Sandshrew Candy          NA
-29            Poison 0.41 m   7.0 kg Nidoran ♀ (Female) Candy          25
-30            Poison 0.79 m  20.0 kg Nidoran ♀ (Female) Candy         100
-31    Poison, Ground 1.30 m  60.0 kg Nidoran ♀ (Female) Candy          NA
-32            Poison 0.51 m   9.0 kg   Nidoran ♂ (Male) Candy          25
-33            Poison 0.89 m  19.5 kg   Nidoran ♂ (Male) Candy         100
-34    Poison, Ground 1.40 m  62.0 kg   Nidoran ♂ (Male) Candy          NA
-35            Normal 0.61 m   7.5 kg           Clefairy Candy          50
-36            Normal 1.30 m  40.0 kg           Clefairy Candy          NA
-37              Fire 0.61 m   9.9 kg             Vulpix Candy          50
-38              Fire 1.09 m  19.9 kg             Vulpix Candy          NA
-39            Normal 0.51 m   5.5 kg         Jigglypuff Candy          50
-40            Normal 0.99 m  12.0 kg         Jigglypuff Candy          NA
-41    Poison, Flying 0.79 m   7.5 kg              Zubat Candy          50
-42    Poison, Flying 1.60 m  55.0 kg              Zubat Candy          NA
-43     Grass, Poison 0.51 m   5.4 kg             Oddish Candy          25
-44     Grass, Poison 0.79 m   8.6 kg             Oddish Candy         100
-45     Grass, Poison 1.19 m  18.6 kg             Oddish Candy          NA
-46        Bug, Grass 0.30 m   5.4 kg              Paras Candy          50
-47        Bug, Grass 0.99 m  29.5 kg              Paras Candy          NA
-48       Bug, Poison 0.99 m  30.0 kg            Venonat Candy          50
-49       Bug, Poison 1.50 m  12.5 kg            Venonat Candy          NA
-50            Ground 0.20 m   0.8 kg            Diglett Candy          50
-51            Ground 0.71 m  33.3 kg                  Dugtrio          NA
-52            Normal 0.41 m   4.2 kg             Meowth Candy          50
-53            Normal 0.99 m  32.0 kg             Meowth Candy          NA
-54             Water 0.79 m  19.6 kg            Psyduck Candy          50
-55             Water 1.70 m  76.6 kg            Psyduck Candy          NA
-56          Fighting 0.51 m  28.0 kg             Mankey Candy          50
-57          Fighting 0.99 m  32.0 kg             Mankey Candy          NA
-58              Fire 0.71 m  19.0 kg          Growlithe Candy          50
-59              Fire 1.91 m 155.0 kg          Growlithe Candy          NA
-60             Water 0.61 m  12.4 kg            Poliwag Candy          25
-61             Water 0.99 m  20.0 kg            Poliwag Candy         100
-62   Water, Fighting 1.30 m  54.0 kg            Poliwag Candy          NA
-63           Psychic 0.89 m  19.5 kg               Abra Candy          25
-64           Psychic 1.30 m  56.5 kg               Abra Candy         100
-65           Psychic 1.50 m  48.0 kg               Abra Candy          NA
-66          Fighting 0.79 m  19.5 kg             Machop Candy          25
-67          Fighting 1.50 m  70.5 kg             Machop Candy         100
-68          Fighting 1.60 m 130.0 kg             Machop Candy          NA
-69     Grass, Poison 0.71 m   4.0 kg         Bellsprout Candy          25
-70     Grass, Poison 0.99 m   6.4 kg         Bellsprout Candy         100
-71     Grass, Poison 1.70 m  15.5 kg         Bellsprout Candy          NA
-72     Water, Poison 0.89 m  45.5 kg          Tentacool Candy          50
-73     Water, Poison 1.60 m  55.0 kg          Tentacool Candy          NA
-74      Rock, Ground 0.41 m  20.0 kg            Geodude Candy          25
-75      Rock, Ground 0.99 m 105.0 kg            Geodude Candy         100
-76      Rock, Ground 1.40 m 300.0 kg            Geodude Candy          NA
-77              Fire 0.99 m  30.0 kg             Ponyta Candy          50
-78              Fire 1.70 m  95.0 kg             Ponyta Candy          NA
-79    Water, Psychic 1.19 m  36.0 kg           Slowpoke Candy          50
-80    Water, Psychic 1.60 m  78.5 kg           Slowpoke Candy          NA
-81          Electric 0.30 m   6.0 kg          Magnemite Candy          50
-82          Electric 0.99 m  60.0 kg          Magnemite Candy          NA
-83    Normal, Flying 0.79 m  15.0 kg                     None          NA
-84    Normal, Flying 1.40 m  39.2 kg              Doduo Candy          50
-85    Normal, Flying 1.80 m  85.2 kg              Doduo Candy          NA
-86             Water 1.09 m  90.0 kg               Seel Candy          50
-87        Water, Ice 1.70 m 120.0 kg               Seel Candy          NA
-88            Poison 0.89 m  30.0 kg             Grimer Candy          50
-89            Poison 1.19 m  30.0 kg             Grimer Candy          NA
-90             Water 0.30 m   4.0 kg           Shellder Candy          50
-91        Water, Ice 1.50 m 132.5 kg           Shellder Candy          NA
-92     Ghost, Poison 1.30 m   0.1 kg             Gastly Candy          25
-93     Ghost, Poison 1.60 m   0.1 kg             Gastly Candy         100
-94     Ghost, Poison 1.50 m  40.5 kg             Gastly Candy          NA
-95      Rock, Ground 8.79 m 210.0 kg                     None          NA
-96           Psychic 0.99 m  32.4 kg            Drowzee Candy          50
-97           Psychic 1.60 m  75.6 kg            Drowzee Candy          NA
-98             Water 0.41 m   6.5 kg             Krabby Candy          50
-99             Water 1.30 m  60.0 kg             Krabby Candy          NA
-100         Electric 0.51 m  10.4 kg            Voltorb Candy          50
-101         Electric 1.19 m  66.6 kg            Voltorb Candy          NA
-102   Grass, Psychic 0.41 m   2.5 kg          Exeggcute Candy          50
-103   Grass, Psychic 2.01 m 120.0 kg          Exeggcute Candy          NA
-104           Ground 0.41 m   6.5 kg             Cubone Candy          50
-105           Ground 0.99 m  45.0 kg             Cubone Candy          NA
-106         Fighting 1.50 m  49.8 kg                     None          NA
-107         Fighting 1.40 m  50.2 kg                     None          NA
-108           Normal 1.19 m  65.5 kg                     None          NA
-109           Poison 0.61 m   1.0 kg            Koffing Candy          50
-110           Poison 1.19 m   9.5 kg            Koffing Candy          NA
-111     Ground, Rock 0.99 m 115.0 kg            Rhyhorn Candy          50
-112     Ground, Rock 1.91 m 120.0 kg            Rhyhorn Candy          NA
-113           Normal 1.09 m  34.6 kg                     None          NA
-114            Grass 0.99 m  35.0 kg                     None          NA
-115           Normal 2.21 m  80.0 kg                     None          NA
-116            Water 0.41 m   8.0 kg             Horsea Candy          50
-117            Water 1.19 m  25.0 kg             Horsea Candy          NA
-118            Water 0.61 m  15.0 kg            Goldeen Candy          50
-119            Water 1.30 m  39.0 kg            Goldeen Candy          NA
-120            Water 0.79 m  34.5 kg             Staryu Candy          50
-121   Water, Psychic 1.09 m  80.0 kg             Staryu Candy          NA
-122          Psychic 1.30 m  54.5 kg                     None          NA
-123      Bug, Flying 1.50 m  56.0 kg                     None          NA
-124     Ice, Psychic 1.40 m  40.6 kg                     None          NA
-125         Electric 1.09 m  30.0 kg                     None          NA
-126             Fire 1.30 m  44.5 kg                     None          NA
-127              Bug 1.50 m  55.0 kg                     None          NA
-128           Normal 1.40 m  88.4 kg                     None          NA
-129            Water 0.89 m  10.0 kg           Magikarp Candy         400
-130    Water, Flying 6.50 m 235.0 kg           Magikarp Candy          NA
-131       Water, Ice 2.49 m 220.0 kg                     None          NA
-132           Normal 0.30 m   4.0 kg                     None          NA
-133           Normal 0.30 m   6.5 kg              Eevee Candy          25
-134            Water 0.99 m  29.0 kg              Eevee Candy          NA
-135         Electric 0.79 m  24.5 kg                     None          NA
-136             Fire 0.89 m  25.0 kg              Eevee Candy          NA
-137           Normal 0.79 m  36.5 kg                     None          NA
-138      Rock, Water 0.41 m   7.5 kg            Omanyte Candy          50
-139      Rock, Water 0.99 m  35.0 kg                     None          NA
-140      Rock, Water 0.51 m  11.5 kg             Kabuto Candy          50
-141      Rock, Water 1.30 m  40.5 kg             Kabuto Candy          NA
-142     Rock, Flying 1.80 m  59.0 kg                     None          NA
-143           Normal 2.11 m 460.0 kg                     None          NA
-144      Ice, Flying 1.70 m  55.4 kg                     None          NA
-145 Electric, Flying 1.60 m  52.6 kg                     None          NA
-146     Fire, Flying 2.01 m  60.0 kg                     None          NA
-147           Dragon 1.80 m   3.3 kg            Dratini Candy          25
-148           Dragon 3.99 m  16.5 kg            Dratini Candy         100
-149   Dragon, Flying 2.21 m 210.0 kg            Dratini Candy          NA
-150          Psychic 2.01 m 122.0 kg                     None          NA
-151          Psychic 0.41 m   4.0 kg                     None          NA
-              egg spawn_chance avg_spawns spawn_time multipliers
-1            2 km       0.6900     69.000      20:00        1.58
-2     Not in Eggs       0.0420      4.200      07:00    1.2, 1.6
-3     Not in Eggs       0.0170      1.700      11:30        NULL
-4            2 km       0.2530     25.300      08:45        1.65
-5     Not in Eggs       0.0120      1.200      19:00        1.79
-6     Not in Eggs       0.0031      0.310      13:34        NULL
-7            2 km       0.5800     58.000      04:25         2.1
-8     Not in Eggs       0.0340      3.400      07:02         1.4
-9     Not in Eggs       0.0067      0.670      00:06        NULL
-10           2 km       3.0320    303.200      16:35        1.05
-11    Not in Eggs       0.1870     18.700      02:11  3.55, 3.79
-12    Not in Eggs       0.0220      2.200      05:23        NULL
-13           2 km       7.1200    712.000      02:21  1.01, 1.09
-14    Not in Eggs       0.4400     44.000      02:30  3.01, 3.41
-15    Not in Eggs       0.0510      5.100      04:50        NULL
-16           2 km      15.9800      1.598      01:34  1.71, 1.92
-17    Not in Eggs       1.0200    102.000      01:30        1.79
-18    Not in Eggs       0.1300     13.000      01:50        NULL
-19           2 km      13.0500      1.305      01:55  2.55, 2.73
-20    Not in Eggs       0.4100     41.000      01:56        NULL
-21           2 km       4.7300    473.000      12:25  2.66, 2.68
-22    Not in Eggs       0.1500     15.000      01:11        NULL
-23           5 km       2.2700    227.000      12:20  2.21, 2.27
-24    Not in Eggs       0.0720      7.200      01:50        NULL
-25           2 km       0.2100     21.000      04:00        2.34
-26    Not in Eggs       0.0076      0.760      23:58        NULL
-27           5 km       1.1100    111.000      01:58        2.45
-28    Not in Eggs       0.0370      3.700      12:34        NULL
-29           5 km       1.3800    138.000      01:51  1.63, 2.48
-30    Not in Eggs       0.0880      8.800      07:22  1.83, 2.48
-31    Not in Eggs       0.0120      1.200      12:35        NULL
-32           5 km       1.3100    131.000      01:12  1.64, 1.70
-33    Not in Eggs       0.0830      8.300      09:02        1.83
-34    Not in Eggs       0.0170      1.700      12:16        NULL
-35           2 km       0.9200     92.000      03:30  2.03, 2.14
-36    Not in Eggs       0.0120      1.200      03:29        NULL
-37           5 km       0.2200     22.000      13:43  2.74, 2.81
-38    Not in Eggs       0.0077      0.770      01:32        NULL
-39           2 km       0.3900     39.000      08:46        1.85
-40    Not in Eggs       0.0180      1.800      12:28        NULL
-41           2 km       6.5200    652.000      12:28  2.60, 3.67
-42    Not in Eggs       0.4200     42.000      02:15        NULL
-43           5 km       1.0200    102.000      03:58         1.5
-44    Not in Eggs       0.0640      6.400      11:33        1.49
-45    Not in Eggs       0.0097      0.970      23:58        NULL
-46           5 km       2.3600    236.000      01:42        2.02
-47    Not in Eggs       0.0740      7.400      01:22        NULL
-48           5 km       2.2800    228.000      02:31  1.86, 1.90
-49    Not in Eggs       0.0720      7.200      23:40        NULL
-50           5 km       0.4000     40.000      02:22        2.69
-51    Not in Eggs       0.0140      1.400      12:37        NULL
-52           5 km       0.8600     86.000      02:54        1.98
-53    Not in Eggs       0.0220      2.200      02:44        NULL
-54           5 km       2.5400    254.000      03:41        2.27
-55    Not in Eggs       0.0870      8.700      23:06        NULL
-56           5 km       0.9200     92.000      12:52  2.17, 2.28
-57    Not in Eggs       0.0310      3.100      12:33        NULL
-58           5 km       0.9200     92.000      03:57  2.31, 2.36
-59    Not in Eggs       0.0170      1.700      03:11        NULL
-60           5 km       2.1900    219.000      03:40  1.72, 1.73
-61    Not in Eggs       0.1300     13.000      09:14        1.95
-62    Not in Eggs       0.0110      1.100      01:32        NULL
-63           5 km       0.4200     42.000      04:30  1.36, 1.95
-64    Not in Eggs       0.0270      2.700      11:25         1.4
-65    Not in Eggs       0.0073      0.730      12:33        NULL
-66           5 km       0.4900     49.000      01:55  1.64, 1.65
-67    Not in Eggs       0.0340      3.400      10:32         1.7
-68    Not in Eggs       0.0068      0.680      02:55        NULL
-69           5 km       1.1500    115.000      04:10        1.57
-70    Not in Eggs       0.0720      7.200      09:45        1.59
-71    Not in Eggs       0.0059      0.590      12:19        NULL
-72           5 km       0.8100     81.000      03:20        2.52
-73    Not in Eggs       0.0820      8.200      23:36        NULL
-74           2 km       1.1900    119.000      12:40  1.75, 1.76
-75    Not in Eggs       0.0710      7.100      04:53  1.64, 1.72
-76    Not in Eggs       0.0047      0.470      12:16        NULL
-77           5 km       0.5100     51.000      02:50  1.48, 1.50
-78    Not in Eggs       0.0110      1.100      04:00        NULL
-79           5 km       1.0500    105.000      07:12        2.21
-80    Not in Eggs       0.0360      3.600      02:56        NULL
-81           5 km       0.7100     71.000      04:04  2.16, 2.17
-82    Not in Eggs       0.0230      2.300      15:25        NULL
-83           5 km       0.0212      2.120      01:09        NULL
-84           5 km       0.5200     52.000      05:10  2.19, 2.24
-85    Not in Eggs       0.2200     22.000      02:12        NULL
-86           5 km       0.2800     28.000      06:46  1.04, 1.96
-87    Not in Eggs       0.0130      1.300      06:04        NULL
-88           5 km       0.0520      5.200      15:11        2.44
-89    Not in Eggs       0.0031      0.310      01:28        NULL
-90           5 km       0.5200     52.000      07:39        2.65
-91    Not in Eggs       0.0150      1.500      02:33        NULL
-92           5 km       0.7900     79.000      04:21        1.78
-93    Not in Eggs       0.0520      5.200      00:10  1.56, 1.80
-94    Not in Eggs       0.0067      0.670      03:55        NULL
-95          10 km       0.1000     10.000      01:18        NULL
-96           5 km       3.2100    321.000      01:51  2.08, 2.09
-97    Not in Eggs       0.1000     10.000      02:17        NULL
-98           5 km       2.1200    212.000      03:33  2.36, 2.40
-99    Not in Eggs       0.0620      6.200      03:44        NULL
-100          5 km       0.6500     65.000      04:36  2.01, 2.02
-101   Not in Eggs       0.0200      2.000      04:10        NULL
-102          5 km       0.7800     78.000      09:09  2.70, 3.18
-103   Not in Eggs       0.0140      1.400      12:34        NULL
-104          5 km       0.6100     61.000      01:51        1.67
-105   Not in Eggs       0.0200      2.000      03:59        NULL
-106         10 km       0.0200      2.000      03:59        NULL
-107         10 km       0.0220      2.200      05:58        NULL
-108          5 km       0.0110      1.100      02:46        NULL
-109          5 km       0.2000     20.000      08:16        1.11
-110   Not in Eggs       0.0160      1.600      12:17        NULL
-111          5 km       0.6300     63.000      03:21        1.91
-112   Not in Eggs       0.0220      2.200      05:50        NULL
-113         10 km       0.0130      1.300      04:46        NULL
-114          5 km       0.2280     22.800      23:13        NULL
-115          5 km       0.0086      0.860      02:40        NULL
-116          5 km       1.1300    113.000      02:53        2.23
-117   Not in Eggs       0.0340      3.400      03:18        NULL
-118          5 km       2.1800    218.000      03:14  2.15, 2.20
-119   Not in Eggs       0.0800      8.000      05:21        NULL
-120          5 km       1.9500    195.000      22:59  2.38, 2.41
-121   Not in Eggs       0.0340      3.400      06:57        NULL
-122         10 km       0.0031      0.310      01:51        NULL
-123         10 km       0.1400     14.000      05:43        NULL
-124         10 km       0.3500     35.000      05:41        NULL
-125         10 km       0.0740      7.400      04:28        NULL
-126         10 km       0.1000     10.000      20:36        NULL
-127         10 km       0.9900     99.000      03:25        NULL
-128          5 km       0.1200     12.000      00:37        NULL
-129          2 km       4.7800    478.000      14:26  10.1, 11.8
-130   Not in Eggs       0.0032      0.320      02:15        NULL
-131         10 km       0.0060      0.600      08:59        NULL
-132   Not in Eggs       0.0000      0.000        N/A        NULL
-133         10 km       2.7500    275.000      05:32  2.02, 2.64
-134   Not in Eggs       0.0140      1.400      10:54        NULL
-135   Not in Eggs       0.0120      1.200      02:30        NULL
-136   Not in Eggs       0.0170      1.700      07:02        NULL
-137          5 km       0.0120      1.200      02:49        NULL
-138         10 km       0.1400     14.000      10:23        2.12
-139 Omanyte Candy       0.0061      0.610      05:04        NULL
-140         10 km       0.1000     10.000      00:05  1.97, 2.37
-141   Not in Eggs       0.0032      0.320      23:40        NULL
-142         10 km       0.0180      1.800      23:40        NULL
-143         10 km       0.0160      1.600      23:40        NULL
-144   Not in Eggs       0.0000      0.000        N/A        NULL
-145   Not in Eggs       0.0000      0.000        N/A        NULL
-146   Not in Eggs       0.0000      0.000        N/A        NULL
-147         10 km       0.3000     30.000      06:41  1.83, 1.84
-148   Not in Eggs       0.0200      2.000      11:57        2.05
-149   Not in Eggs       0.0011      0.110      23:38        NULL
-150   Not in Eggs       0.0000      0.000        N/A        NULL
-151   Not in Eggs       0.0000      0.000        N/A        NULL
-                                     weaknesses
-1                    Fire, Ice, Flying, Psychic
-2                    Fire, Ice, Flying, Psychic
-3                    Fire, Ice, Flying, Psychic
-4                           Water, Ground, Rock
-5                           Water, Ground, Rock
-6                         Water, Electric, Rock
-7                               Electric, Grass
-8                               Electric, Grass
-9                               Electric, Grass
-10                           Fire, Flying, Rock
-11                           Fire, Flying, Rock
-12            Fire, Electric, Ice, Flying, Rock
-13                  Fire, Flying, Psychic, Rock
-14                  Fire, Flying, Psychic, Rock
-15                  Fire, Flying, Psychic, Rock
-16                               Electric, Rock
-17                               Electric, Rock
-18                               Electric, Rock
-19                                     Fighting
-20                                     Fighting
-21                               Electric, Rock
-22                               Electric, Rock
-23                              Ground, Psychic
-24                              Ground, Psychic
-25                                       Ground
-26                                       Ground
-27                            Water, Grass, Ice
-28                            Water, Grass, Ice
-29                              Ground, Psychic
-30                              Ground, Psychic
-31                  Water, Ice, Ground, Psychic
-32                              Ground, Psychic
-33                              Ground, Psychic
-34                  Water, Ice, Ground, Psychic
-35                                     Fighting
-36                                     Fighting
-37                          Water, Ground, Rock
-38                          Water, Ground, Rock
-39                                     Fighting
-40                                     Fighting
-41                 Electric, Ice, Psychic, Rock
-42                 Electric, Ice, Psychic, Rock
-43                   Fire, Ice, Flying, Psychic
-44                   Fire, Ice, Flying, Psychic
-45                   Fire, Ice, Flying, Psychic
-46         Fire, Ice, Poison, Flying, Bug, Rock
-47         Fire, Ice, Poison, Flying, Bug, Rock
-48                  Fire, Flying, Psychic, Rock
-49                  Fire, Flying, Psychic, Rock
-50                            Water, Grass, Ice
-51                            Water, Grass, Ice
-52                                     Fighting
-53                                     Fighting
-54                              Electric, Grass
-55                              Electric, Grass
-56                       Flying, Psychic, Fairy
-57                       Flying, Psychic, Fairy
-58                          Water, Ground, Rock
-59                          Water, Ground, Rock
-60                              Electric, Grass
-61                              Electric, Grass
-62      Electric, Grass, Flying, Psychic, Fairy
-63                             Bug, Ghost, Dark
-64                             Bug, Ghost, Dark
-65                             Bug, Ghost, Dark
-66                       Flying, Psychic, Fairy
-67                       Flying, Psychic, Fairy
-68                       Flying, Psychic, Fairy
-69                   Fire, Ice, Flying, Psychic
-70                   Fire, Ice, Flying, Psychic
-71                   Fire, Ice, Flying, Psychic
-72                    Electric, Ground, Psychic
-73                    Electric, Ground, Psychic
-74   Water, Grass, Ice, Fighting, Ground, Steel
-75   Water, Grass, Ice, Fighting, Ground, Steel
-76   Water, Grass, Ice, Fighting, Ground, Steel
-77                          Water, Ground, Rock
-78                          Water, Ground, Rock
-79            Electric, Grass, Bug, Ghost, Dark
-80            Electric, Grass, Bug, Ghost, Dark
-81                          Fire, Water, Ground
-82                          Fire, Water, Ground
-83                               Electric, Rock
-84                               Electric, Rock
-85                               Electric, Rock
-86                              Electric, Grass
-87              Electric, Grass, Fighting, Rock
-88                              Ground, Psychic
-89                              Ground, Psychic
-90                              Electric, Grass
-91              Electric, Grass, Fighting, Rock
-92                 Ground, Psychic, Ghost, Dark
-93                 Ground, Psychic, Ghost, Dark
-94                 Ground, Psychic, Ghost, Dark
-95   Water, Grass, Ice, Fighting, Ground, Steel
-96                             Bug, Ghost, Dark
-97                             Bug, Ghost, Dark
-98                              Electric, Grass
-99                              Electric, Grass
-100                                      Ground
-101                                      Ground
-102 Fire, Ice, Poison, Flying, Bug, Ghost, Dark
-103 Fire, Ice, Poison, Flying, Bug, Ghost, Dark
-104                           Water, Grass, Ice
-105                           Water, Grass, Ice
-106                      Flying, Psychic, Fairy
-107                      Flying, Psychic, Fairy
-108                                    Fighting
-109                             Ground, Psychic
-110                             Ground, Psychic
-111  Water, Grass, Ice, Fighting, Ground, Steel
-112  Water, Grass, Ice, Fighting, Ground, Steel
-113                                    Fighting
-114              Fire, Ice, Poison, Flying, Bug
-115                                    Fighting
-116                             Electric, Grass
-117                             Electric, Grass
-118                             Electric, Grass
-119                             Electric, Grass
-120                             Electric, Grass
-121           Electric, Grass, Bug, Ghost, Dark
-122                            Bug, Ghost, Dark
-123           Fire, Electric, Ice, Flying, Rock
-124         Fire, Bug, Rock, Ghost, Dark, Steel
-125                                      Ground
-126                         Water, Ground, Rock
-127                          Fire, Flying, Rock
-128                                    Fighting
-129                             Electric, Grass
-130                              Electric, Rock
-131             Electric, Grass, Fighting, Rock
-132                                    Fighting
-133                                    Fighting
-134                             Electric, Grass
-135                                      Ground
-136                         Water, Ground, Rock
-137                                    Fighting
-138           Electric, Grass, Fighting, Ground
-139           Electric, Grass, Fighting, Ground
-140           Electric, Grass, Fighting, Ground
-141           Electric, Grass, Fighting, Ground
-142           Water, Electric, Ice, Rock, Steel
-143                                    Fighting
-144                 Fire, Electric, Rock, Steel
-145                                   Ice, Rock
-146                       Water, Electric, Rock
-147                          Ice, Dragon, Fairy
-148                          Ice, Dragon, Fairy
-149                    Ice, Rock, Dragon, Fairy
-150                            Bug, Ghost, Dark
-151                            Bug, Ghost, Dark
-                               next_evolution
-1                 002, 003, Ivysaur, Venusaur
-2                               003, Venusaur
-3                                        NULL
-4             005, 006, Charmeleon, Charizard
-5                              006, Charizard
-6                                        NULL
-7              008, 009, Wartortle, Blastoise
-8                              009, Blastoise
-9                                        NULL
-10              011, 012, Metapod, Butterfree
-11                            012, Butterfree
-12                                       NULL
-13                 014, 015, Kakuna, Beedrill
-14                              015, Beedrill
-15                                       NULL
-16               017, 018, Pidgeotto, Pidgeot
-17                               018, Pidgeot
-18                                       NULL
-19                              020, Raticate
-20                                       NULL
-21                                022, Fearow
-22                                       NULL
-23                                 024, Arbok
-24                                       NULL
-25                                026, Raichu
-26                                       NULL
-27                             028, Sandslash
-28                                       NULL
-29              030, 031, Nidorina, Nidoqueen
-30                             031, Nidoqueen
-31                                       NULL
-32               033, 034, Nidorino, Nidoking
-33                              034, Nidoking
-34                                       NULL
-35                              036, Clefable
-36                                       NULL
-37                             038, Ninetales
-38                                       NULL
-39                            040, Wigglytuff
-40                                       NULL
-41                                042, Golbat
-42                                       NULL
-43                 044, 045, Gloom, Vileplume
-44                             045, Vileplume
-45                                       NULL
-46                              047, Parasect
-47                                       NULL
-48                              049, Venomoth
-49                                       NULL
-50                               051, Dugtrio
-51                                       NULL
-52                               053, Persian
-53                                       NULL
-54                               055, Golduck
-55                                       NULL
-56                              057, Primeape
-57                                       NULL
-58                              059, Arcanine
-59                                       NULL
-60             061, 062, Poliwhirl, Poliwrath
-61                             062, Poliwrath
-62                                       NULL
-63                064, 065, Kadabra, Alakazam
-64                              065, Alakazam
-65                                       NULL
-66                 067, 068, Machoke, Machamp
-67                               068, Machamp
-68                                       NULL
-69           070, 071, Weepinbell, Victreebel
-70                            071, Victreebel
-71                                       NULL
-72                            073, Tentacruel
-73                                       NULL
-74                  075, 076, Graveler, Golem
-75                                 076, Golem
-76                                       NULL
-77                              078, Rapidash
-78                                       NULL
-79                               080, Slowbro
-80                                       NULL
-81                              082, Magneton
-82                                       NULL
-83                                       NULL
-84                                085, Dodrio
-85                                       NULL
-86                               087, Dewgong
-87                                       NULL
-88                                   089, Muk
-89                                       NULL
-90                              091, Cloyster
-91                                       NULL
-92                  093, 094, Haunter, Gengar
-93                                094, Gengar
-94                                       NULL
-95                                       NULL
-96                                 097, Hypno
-97                                       NULL
-98                               099, Kingler
-99                                       NULL
-100                            101, Electrode
-101                                      NULL
-102                            103, Exeggutor
-103                                      NULL
-104                              105, Marowak
-105                                      NULL
-106                                      NULL
-107                                      NULL
-108                                      NULL
-109                              110, Weezing
-110                                      NULL
-111                               112, Rhydon
-112                                      NULL
-113                                      NULL
-114                                      NULL
-115                                      NULL
-116                               117, Seadra
-117                                      NULL
-118                              119, Seaking
-119                                      NULL
-120                              121, Starmie
-121                                      NULL
-122                                      NULL
-123                                      NULL
-124                                      NULL
-125                                      NULL
-126                                      NULL
-127                                      NULL
-128                                      NULL
-129                             130, Gyarados
-130                                      NULL
-131                                      NULL
-132                                      NULL
-133 134, 135, 136, Vaporeon, Jolteon, Flareon
-134                                      NULL
-135                                      NULL
-136                                      NULL
-137                                      NULL
-138                              139, Omastar
-139                                      NULL
-140                             141, Kabutops
-141                                      NULL
-142                                      NULL
-143                                      NULL
-144                                      NULL
-145                                      NULL
-146                                      NULL
-147            148, 149, Dragonair, Dragonite
-148                            149, Dragonite
-149                                      NULL
-150                                      NULL
-151                                      NULL
-                         prev_evolution
-1                                  NULL
-2                        001, Bulbasaur
-3          001, 002, Bulbasaur, Ivysaur
-4                                  NULL
-5                       004, Charmander
-6      004, 005, Charmander, Charmeleon
-7                                  NULL
-8                         007, Squirtle
-9         007, 008, Squirtle, Wartortle
-10                                 NULL
-11                        010, Caterpie
-12          010, 011, Caterpie, Metapod
-13                                 NULL
-14                          013, Weedle
-15             013, 014, Weedle, Kakuna
-16                                 NULL
-17                          016, Pidgey
-18          016, 017, Pidgey, Pidgeotto
-19                                 NULL
-20                         019, Rattata
-21                                 NULL
-22                         021, Spearow
-23                                 NULL
-24                           023, Ekans
-25                                 NULL
-26                         025, Pikachu
-27                                 NULL
-28                       027, Sandshrew
-29                                 NULL
-30                 029, Nidoran(Female)
-31  029, 030, Nidoran(Female), Nidorina
-32                                 NULL
-33                   032, Nidoran(Male)
-34    032, 033, Nidoran(Male), Nidorino
-35                                 NULL
-36                        035, Clefairy
-37                                 NULL
-38                          037, Vulpix
-39                                 NULL
-40                      039, Jigglypuff
-41                                 NULL
-42                           041, Zubat
-43                                 NULL
-44                          043, Oddish
-45              043, 044, Oddish, Gloom
-46                                 NULL
-47                           046, Paras
-48                                 NULL
-49                         048, Venonat
-50                                 NULL
-51                         050, Diglett
-52                                 NULL
-53                          052, Meowth
-54                                 NULL
-55                         054, Psyduck
-56                                 NULL
-57                          056, Mankey
-58                                 NULL
-59                       058, Growlithe
-60                                 NULL
-61                         060, Poliwag
-62         060, 061, Poliwag, Poliwhirl
-63                                 NULL
-64                            063, Abra
-65              063, 064, Abra, Kadabra
-66                                 NULL
-67                          066, Machop
-68            066, 067, Machop, Machoke
-69                                 NULL
-70                      069, Bellsprout
-71     069, 070, Bellsprout, Weepinbell
-72                                 NULL
-73                       072, Tentacool
-74                                 NULL
-75                         074, Geodude
-76          074, 075, Geodude, Graveler
-77                                 NULL
-78                          077, Ponyta
-79                                 NULL
-80                        079, Slowpoke
-81                                 NULL
-82                       081, Magnemite
-83                                 NULL
-84                                 NULL
-85                           084, Doduo
-86                                 NULL
-87                            086, Seel
-88                                 NULL
-89                          088, Grimer
-90                                 NULL
-91                        090, Shellder
-92                                 NULL
-93                          092, Gastly
-94            092, 093, Gastly, Haunter
-95                                 NULL
-96                                 NULL
-97                         096, Drowzee
-98                                 NULL
-99                          098, Krabby
-100                                NULL
-101                        100, Voltorb
-102                                NULL
-103                      102, Exeggcute
-104                                NULL
-105                         104, Cubone
-106                                NULL
-107                                NULL
-108                                NULL
-109                                NULL
-110                        109, Koffing
-111                                NULL
-112                        111, Rhyhorn
-113                                NULL
-114                                NULL
-115                                NULL
-116                                NULL
-117                         116, Horsea
-118                                NULL
-119                        118, Goldeen
-120                                NULL
-121                         120, Staryu
-122                                NULL
-123                                NULL
-124                                NULL
-125                                NULL
-126                                NULL
-127                                NULL
-128                                NULL
-129                                NULL
-130                       129, Magikarp
-131                                NULL
-132                                NULL
-133                                NULL
-134                          133, Eevee
-135                          133, Eevee
-136                          133, Eevee
-137                                NULL
-138                                NULL
-139                        138, Omanyte
-140                                NULL
-141                         140, Kabuto
-142                                NULL
-143                                NULL
-144                                NULL
-145                                NULL
-146                                NULL
-147                                NULL
-148                        147, Dratini
-149        147, 148, Dratini, Dragonair
-150                                NULL
-151                                NULL
    + id num name img type height weight candy +1 1 001 Bulbasaur http://www.serebii.net/pokemongo/pokemon/001.png Grass, Poison 0.71 m 6.9 kg Bulbasaur Candy +2 2 002 Ivysaur http://www.serebii.net/pokemongo/pokemon/002.png Grass, Poison 0.99 m 13.0 kg Bulbasaur Candy +3 3 003 Venusaur http://www.serebii.net/pokemongo/pokemon/003.png Grass, Poison 2.01 m 100.0 kg Bulbasaur Candy +4 4 004 Charmander http://www.serebii.net/pokemongo/pokemon/004.png Fire 0.61 m 8.5 kg Charmander Candy +5 5 005 Charmeleon http://www.serebii.net/pokemongo/pokemon/005.png Fire 1.09 m 19.0 kg Charmander Candy +6 6 006 Charizard http://www.serebii.net/pokemongo/pokemon/006.png Fire, Flying 1.70 m 90.5 kg Charmander Candy +7 7 007 Squirtle http://www.serebii.net/pokemongo/pokemon/007.png Water 0.51 m 9.0 kg Squirtle Candy +8 8 008 Wartortle http://www.serebii.net/pokemongo/pokemon/008.png Water 0.99 m 22.5 kg Squirtle Candy +9 9 009 Blastoise http://www.serebii.net/pokemongo/pokemon/009.png Water 1.60 m 85.5 kg Squirtle Candy +10 10 010 Caterpie http://www.serebii.net/pokemongo/pokemon/010.png Bug 0.30 m 2.9 kg Caterpie Candy +11 11 011 Metapod http://www.serebii.net/pokemongo/pokemon/011.png Bug 0.71 m 9.9 kg Caterpie Candy +12 12 012 Butterfree http://www.serebii.net/pokemongo/pokemon/012.png Bug, Flying 1.09 m 32.0 kg Caterpie Candy +13 13 013 Weedle http://www.serebii.net/pokemongo/pokemon/013.png Bug, Poison 0.30 m 3.2 kg Weedle Candy +14 14 014 Kakuna http://www.serebii.net/pokemongo/pokemon/014.png Bug, Poison 0.61 m 10.0 kg Weedle Candy +15 15 015 Beedrill http://www.serebii.net/pokemongo/pokemon/015.png Bug, Poison 0.99 m 29.5 kg Weedle Candy +16 16 016 Pidgey http://www.serebii.net/pokemongo/pokemon/016.png Normal, Flying 0.30 m 1.8 kg Pidgey Candy +17 17 017 Pidgeotto http://www.serebii.net/pokemongo/pokemon/017.png Normal, Flying 1.09 m 30.0 kg Pidgey Candy +18 18 018 Pidgeot http://www.serebii.net/pokemongo/pokemon/018.png Normal, Flying 1.50 m 39.5 kg Pidgey Candy +19 19 019 Rattata http://www.serebii.net/pokemongo/pokemon/019.png Normal 0.30 m 3.5 kg Rattata Candy +20 20 020 Raticate http://www.serebii.net/pokemongo/pokemon/020.png Normal 0.71 m 18.5 kg Rattata Candy +21 21 021 Spearow http://www.serebii.net/pokemongo/pokemon/021.png Normal, Flying 0.30 m 2.0 kg Spearow Candy +22 22 022 Fearow http://www.serebii.net/pokemongo/pokemon/022.png Normal, Flying 1.19 m 38.0 kg Spearow Candy +23 23 023 Ekans http://www.serebii.net/pokemongo/pokemon/023.png Poison 2.01 m 6.9 kg Ekans Candy +24 24 024 Arbok http://www.serebii.net/pokemongo/pokemon/024.png Poison 3.51 m 65.0 kg Ekans Candy +25 25 025 Pikachu http://www.serebii.net/pokemongo/pokemon/025.png Electric 0.41 m 6.0 kg Pikachu Candy +26 26 026 Raichu http://www.serebii.net/pokemongo/pokemon/026.png Electric 0.79 m 30.0 kg Pikachu Candy +27 27 027 Sandshrew http://www.serebii.net/pokemongo/pokemon/027.png Ground 0.61 m 12.0 kg Sandshrew Candy +28 28 028 Sandslash http://www.serebii.net/pokemongo/pokemon/028.png Ground 0.99 m 29.5 kg Sandshrew Candy +29 29 029 Nidoran ♀ (Female) http://www.serebii.net/pokemongo/pokemon/029.png Poison 0.41 m 7.0 kg Nidoran ♀ (Female) Candy +30 30 030 Nidorina http://www.serebii.net/pokemongo/pokemon/030.png Poison 0.79 m 20.0 kg Nidoran ♀ (Female) Candy +31 31 031 Nidoqueen http://www.serebii.net/pokemongo/pokemon/031.png Poison, Ground 1.30 m 60.0 kg Nidoran ♀ (Female) Candy +32 32 032 Nidoran ♂ (Male) http://www.serebii.net/pokemongo/pokemon/032.png Poison 0.51 m 9.0 kg Nidoran ♂ (Male) Candy +33 33 033 Nidorino http://www.serebii.net/pokemongo/pokemon/033.png Poison 0.89 m 19.5 kg Nidoran ♂ (Male) Candy +34 34 034 Nidoking http://www.serebii.net/pokemongo/pokemon/034.png Poison, Ground 1.40 m 62.0 kg Nidoran ♂ (Male) Candy +35 35 035 Clefairy http://www.serebii.net/pokemongo/pokemon/035.png Normal 0.61 m 7.5 kg Clefairy Candy +36 36 036 Clefable http://www.serebii.net/pokemongo/pokemon/036.png Normal 1.30 m 40.0 kg Clefairy Candy +37 37 037 Vulpix http://www.serebii.net/pokemongo/pokemon/037.png Fire 0.61 m 9.9 kg Vulpix Candy +38 38 038 Ninetales http://www.serebii.net/pokemongo/pokemon/038.png Fire 1.09 m 19.9 kg Vulpix Candy +39 39 039 Jigglypuff http://www.serebii.net/pokemongo/pokemon/039.png Normal 0.51 m 5.5 kg Jigglypuff Candy +40 40 040 Wigglytuff http://www.serebii.net/pokemongo/pokemon/040.png Normal 0.99 m 12.0 kg Jigglypuff Candy +41 41 041 Zubat http://www.serebii.net/pokemongo/pokemon/041.png Poison, Flying 0.79 m 7.5 kg Zubat Candy +42 42 042 Golbat http://www.serebii.net/pokemongo/pokemon/042.png Poison, Flying 1.60 m 55.0 kg Zubat Candy +43 43 043 Oddish http://www.serebii.net/pokemongo/pokemon/043.png Grass, Poison 0.51 m 5.4 kg Oddish Candy +44 44 044 Gloom http://www.serebii.net/pokemongo/pokemon/044.png Grass, Poison 0.79 m 8.6 kg Oddish Candy +45 45 045 Vileplume http://www.serebii.net/pokemongo/pokemon/045.png Grass, Poison 1.19 m 18.6 kg Oddish Candy +46 46 046 Paras http://www.serebii.net/pokemongo/pokemon/046.png Bug, Grass 0.30 m 5.4 kg Paras Candy +47 47 047 Parasect http://www.serebii.net/pokemongo/pokemon/047.png Bug, Grass 0.99 m 29.5 kg Paras Candy +48 48 048 Venonat http://www.serebii.net/pokemongo/pokemon/048.png Bug, Poison 0.99 m 30.0 kg Venonat Candy +49 49 049 Venomoth http://www.serebii.net/pokemongo/pokemon/049.png Bug, Poison 1.50 m 12.5 kg Venonat Candy +50 50 050 Diglett http://www.serebii.net/pokemongo/pokemon/050.png Ground 0.20 m 0.8 kg Diglett Candy +51 51 051 Dugtrio http://www.serebii.net/pokemongo/pokemon/051.png Ground 0.71 m 33.3 kg Dugtrio +52 52 052 Meowth http://www.serebii.net/pokemongo/pokemon/052.png Normal 0.41 m 4.2 kg Meowth Candy +53 53 053 Persian http://www.serebii.net/pokemongo/pokemon/053.png Normal 0.99 m 32.0 kg Meowth Candy +54 54 054 Psyduck http://www.serebii.net/pokemongo/pokemon/054.png Water 0.79 m 19.6 kg Psyduck Candy +55 55 055 Golduck http://www.serebii.net/pokemongo/pokemon/055.png Water 1.70 m 76.6 kg Psyduck Candy +56 56 056 Mankey http://www.serebii.net/pokemongo/pokemon/056.png Fighting 0.51 m 28.0 kg Mankey Candy +57 57 057 Primeape http://www.serebii.net/pokemongo/pokemon/057.png Fighting 0.99 m 32.0 kg Mankey Candy +58 58 058 Growlithe http://www.serebii.net/pokemongo/pokemon/058.png Fire 0.71 m 19.0 kg Growlithe Candy + candy_count egg spawn_chance avg_spawns spawn_time multipliers weaknesses +1 25 2 km 0.6900 69.000 20:00 1.58 Fire, Ice, Flying, Psychic +2 100 Not in Eggs 0.0420 4.200 07:00 1.2, 1.6 Fire, Ice, Flying, Psychic +3 NA Not in Eggs 0.0170 1.700 11:30 NULL Fire, Ice, Flying, Psychic +4 25 2 km 0.2530 25.300 08:45 1.65 Water, Ground, Rock +5 100 Not in Eggs 0.0120 1.200 19:00 1.79 Water, Ground, Rock +6 NA Not in Eggs 0.0031 0.310 13:34 NULL Water, Electric, Rock +7 25 2 km 0.5800 58.000 04:25 2.1 Electric, Grass +8 100 Not in Eggs 0.0340 3.400 07:02 1.4 Electric, Grass +9 NA Not in Eggs 0.0067 0.670 00:06 NULL Electric, Grass +10 12 2 km 3.0320 303.200 16:35 1.05 Fire, Flying, Rock +11 50 Not in Eggs 0.1870 18.700 02:11 3.55, 3.79 Fire, Flying, Rock +12 NA Not in Eggs 0.0220 2.200 05:23 NULL Fire, Electric, Ice, Flying, Rock +13 12 2 km 7.1200 712.000 02:21 1.01, 1.09 Fire, Flying, Psychic, Rock +14 50 Not in Eggs 0.4400 44.000 02:30 3.01, 3.41 Fire, Flying, Psychic, Rock +15 NA Not in Eggs 0.0510 5.100 04:50 NULL Fire, Flying, Psychic, Rock +16 12 2 km 15.9800 1.598 01:34 1.71, 1.92 Electric, Rock +17 50 Not in Eggs 1.0200 102.000 01:30 1.79 Electric, Rock +18 NA Not in Eggs 0.1300 13.000 01:50 NULL Electric, Rock +19 25 2 km 13.0500 1.305 01:55 2.55, 2.73 Fighting +20 NA Not in Eggs 0.4100 41.000 01:56 NULL Fighting +21 50 2 km 4.7300 473.000 12:25 2.66, 2.68 Electric, Rock +22 NA Not in Eggs 0.1500 15.000 01:11 NULL Electric, Rock +23 50 5 km 2.2700 227.000 12:20 2.21, 2.27 Ground, Psychic +24 NA Not in Eggs 0.0720 7.200 01:50 NULL Ground, Psychic +25 50 2 km 0.2100 21.000 04:00 2.34 Ground +26 NA Not in Eggs 0.0076 0.760 23:58 NULL Ground +27 50 5 km 1.1100 111.000 01:58 2.45 Water, Grass, Ice +28 NA Not in Eggs 0.0370 3.700 12:34 NULL Water, Grass, Ice +29 25 5 km 1.3800 138.000 01:51 1.63, 2.48 Ground, Psychic +30 100 Not in Eggs 0.0880 8.800 07:22 1.83, 2.48 Ground, Psychic +31 NA Not in Eggs 0.0120 1.200 12:35 NULL Water, Ice, Ground, Psychic +32 25 5 km 1.3100 131.000 01:12 1.64, 1.70 Ground, Psychic +33 100 Not in Eggs 0.0830 8.300 09:02 1.83 Ground, Psychic +34 NA Not in Eggs 0.0170 1.700 12:16 NULL Water, Ice, Ground, Psychic +35 50 2 km 0.9200 92.000 03:30 2.03, 2.14 Fighting +36 NA Not in Eggs 0.0120 1.200 03:29 NULL Fighting +37 50 5 km 0.2200 22.000 13:43 2.74, 2.81 Water, Ground, Rock +38 NA Not in Eggs 0.0077 0.770 01:32 NULL Water, Ground, Rock +39 50 2 km 0.3900 39.000 08:46 1.85 Fighting +40 NA Not in Eggs 0.0180 1.800 12:28 NULL Fighting +41 50 2 km 6.5200 652.000 12:28 2.60, 3.67 Electric, Ice, Psychic, Rock +42 NA Not in Eggs 0.4200 42.000 02:15 NULL Electric, Ice, Psychic, Rock +43 25 5 km 1.0200 102.000 03:58 1.5 Fire, Ice, Flying, Psychic +44 100 Not in Eggs 0.0640 6.400 11:33 1.49 Fire, Ice, Flying, Psychic +45 NA Not in Eggs 0.0097 0.970 23:58 NULL Fire, Ice, Flying, Psychic +46 50 5 km 2.3600 236.000 01:42 2.02 Fire, Ice, Poison, Flying, Bug, Rock +47 NA Not in Eggs 0.0740 7.400 01:22 NULL Fire, Ice, Poison, Flying, Bug, Rock +48 50 5 km 2.2800 228.000 02:31 1.86, 1.90 Fire, Flying, Psychic, Rock +49 NA Not in Eggs 0.0720 7.200 23:40 NULL Fire, Flying, Psychic, Rock +50 50 5 km 0.4000 40.000 02:22 2.69 Water, Grass, Ice +51 NA Not in Eggs 0.0140 1.400 12:37 NULL Water, Grass, Ice +52 50 5 km 0.8600 86.000 02:54 1.98 Fighting +53 NA Not in Eggs 0.0220 2.200 02:44 NULL Fighting +54 50 5 km 2.5400 254.000 03:41 2.27 Electric, Grass +55 NA Not in Eggs 0.0870 8.700 23:06 NULL Electric, Grass +56 50 5 km 0.9200 92.000 12:52 2.17, 2.28 Flying, Psychic, Fairy +57 NA Not in Eggs 0.0310 3.100 12:33 NULL Flying, Psychic, Fairy +58 50 5 km 0.9200 92.000 03:57 2.31, 2.36 Water, Ground, Rock + next_evolution prev_evolution +1 002, 003, Ivysaur, Venusaur NULL +2 003, Venusaur 001, Bulbasaur +3 NULL 001, 002, Bulbasaur, Ivysaur +4 005, 006, Charmeleon, Charizard NULL +5 006, Charizard 004, Charmander +6 NULL 004, 005, Charmander, Charmeleon +7 008, 009, Wartortle, Blastoise NULL +8 009, Blastoise 007, Squirtle +9 NULL 007, 008, Squirtle, Wartortle +10 011, 012, Metapod, Butterfree NULL +11 012, Butterfree 010, Caterpie +12 NULL 010, 011, Caterpie, Metapod +13 014, 015, Kakuna, Beedrill NULL +14 015, Beedrill 013, Weedle +15 NULL 013, 014, Weedle, Kakuna +16 017, 018, Pidgeotto, Pidgeot NULL +17 018, Pidgeot 016, Pidgey +18 NULL 016, 017, Pidgey, Pidgeotto +19 020, Raticate NULL +20 NULL 019, Rattata +21 022, Fearow NULL +22 NULL 021, Spearow +23 024, Arbok NULL +24 NULL 023, Ekans +25 026, Raichu NULL +26 NULL 025, Pikachu +27 028, Sandslash NULL +28 NULL 027, Sandshrew +29 030, 031, Nidorina, Nidoqueen NULL +30 031, Nidoqueen 029, Nidoran(Female) +31 NULL 029, 030, Nidoran(Female), Nidorina +32 033, 034, Nidorino, Nidoking NULL +33 034, Nidoking 032, Nidoran(Male) +34 NULL 032, 033, Nidoran(Male), Nidorino +35 036, Clefable NULL +36 NULL 035, Clefairy +37 038, Ninetales NULL +38 NULL 037, Vulpix +39 040, Wigglytuff NULL +40 NULL 039, Jigglypuff +41 042, Golbat NULL +42 NULL 041, Zubat +43 044, 045, Gloom, Vileplume NULL +44 045, Vileplume 043, Oddish +45 NULL 043, 044, Oddish, Gloom +46 047, Parasect NULL +47 NULL 046, Paras +48 049, Venomoth NULL +49 NULL 048, Venonat +50 051, Dugtrio NULL +51 NULL 050, Diglett +52 053, Persian NULL +53 NULL 052, Meowth +54 055, Golduck NULL +55 NULL 054, Psyduck +56 057, Primeape NULL +57 NULL 056, Mankey +58 059, Arcanine NULL + [ reached 'max' / getOption("max.print") -- omitted 93 rows ]

    Data frame structure from JSON

    @@ -4411,6 +3697,37 @@ 

    [1] 151  17
    +
    class(jsonData$pokemon)
    + +
    [1] "data.frame"
    + +
    jsonData$pokemon %>% filter(type == "Fire") %>% select(!(img))
    + +
        id num       name type height   weight            candy candy_count         egg spawn_chance avg_spawns spawn_time multipliers
+1    4 004 Charmander Fire 0.61 m   8.5 kg Charmander Candy          25        2 km       0.2530      25.30      08:45        1.65
+2    5 005 Charmeleon Fire 1.09 m  19.0 kg Charmander Candy         100 Not in Eggs       0.0120       1.20      19:00        1.79
+3   37 037     Vulpix Fire 0.61 m   9.9 kg     Vulpix Candy          50        5 km       0.2200      22.00      13:43  2.74, 2.81
+4   38 038  Ninetales Fire 1.09 m  19.9 kg     Vulpix Candy          NA Not in Eggs       0.0077       0.77      01:32        NULL
+5   58 058  Growlithe Fire 0.71 m  19.0 kg  Growlithe Candy          50        5 km       0.9200      92.00      03:57  2.31, 2.36
+6   59 059   Arcanine Fire 1.91 m 155.0 kg  Growlithe Candy          NA Not in Eggs       0.0170       1.70      03:11        NULL
+7   77 077     Ponyta Fire 0.99 m  30.0 kg     Ponyta Candy          50        5 km       0.5100      51.00      02:50  1.48, 1.50
+8   78 078   Rapidash Fire 1.70 m  95.0 kg     Ponyta Candy          NA Not in Eggs       0.0110       1.10      04:00        NULL
+9  126 126     Magmar Fire 1.30 m  44.5 kg             None          NA       10 km       0.1000      10.00      20:36        NULL
+10 136 136    Flareon Fire 0.89 m  25.0 kg      Eevee Candy          NA Not in Eggs       0.0170       1.70      07:02        NULL
+            weaknesses                  next_evolution  prev_evolution
+1  Water, Ground, Rock 005, 006, Charmeleon, Charizard            NULL
+2  Water, Ground, Rock                  006, Charizard 004, Charmander
+3  Water, Ground, Rock                  038, Ninetales            NULL
+4  Water, Ground, Rock                            NULL     037, Vulpix
+5  Water, Ground, Rock                   059, Arcanine            NULL
+6  Water, Ground, Rock                            NULL  058, Growlithe
+7  Water, Ground, Rock                   078, Rapidash            NULL
+8  Water, Ground, Rock                            NULL     077, Ponyta
+9  Water, Ground, Rock                            NULL            NULL
+10 Water, Ground, Rock                            NULL      133, Eevee
    + +

    Going deeper..

    + 
    class(jsonData$pokemon$type) # Can be lists
    [1] "list"
    @@ -5489,79 +4806,51 @@

    rvest package

    -
    recount_url = "http://bowtie-bio.sourceforge.net/recount/"
+
    recount_url <- "http://bowtie-bio.sourceforge.net/recount/"
 # install.packages("rvest")
 library(rvest)
 htmlfile = read_html(recount_url)
 
-nds = html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table')
-dat = html_table(nds)
-dat = as.data.frame(dat)
+nds <- html_nodes(htmlfile, xpath = '//*[@id="recounttab"]/table')
+dat <- html_table(nds)
+dat <- as.data.frame(dat)
 head(dat)
    
 
-
           X1                                         X2      X3
-1   Study                                       PMID Species
-2 bodymap not published, but publicly available here   human
-3  cheung                                   20856902   human
-4    core                                   19056941   human
-5   gilad                                   20009012   human
-6    maqc                                   20167110   human
-                                X4                               X5
-1  Number of biological replicates Number of uniquely aligned reads
-2                               19                    2,197,622,796
-3                               41                      834,584,950
-4                                2                        8,670,342
-5                                6                       41,356,738
-6 14 (technical)**  2 (biological)                       71,970,164
-               X6              X7              X8
-1   ExpressionSet     Count table Phenotype table
-2            link            link            link
-3            link            link            link
-4            link            link            link
-5            link            link            link
-6 original pooled original pooled original pooled
-                                               X9
-1                                           Notes
-2 Illumina Human BodyMap 2.0 -- tissue comparison
-3                                    HapMap - CEU
-4                                lung fibroblasts
-5                        liver; males and femlaes
-6                              experiment: MAQC-2
    
+
           X1                                         X2      X3                               X4                               X5
+1   Study                                       PMID Species  Number of biological replicates Number of uniquely aligned reads
+2 bodymap not published, but publicly available here   human                               19                    2,197,622,796
+3  cheung                                   20856902   human                               41                      834,584,950
+4    core                                   19056941   human                                2                        8,670,342
+5   gilad                                   20009012   human                                6                       41,356,738
+6    maqc                                   20167110   human 14 (technical)**  2 (biological)                       71,970,164
+               X6              X7              X8                                              X9
+1   ExpressionSet     Count table Phenotype table                                           Notes
+2            link            link            link Illumina Human BodyMap 2.0 -- tissue comparison
+3            link            link            link                                    HapMap - CEU
+4            link            link            link                                lung fibroblasts
+5            link            link            link                        liver; males and femlaes
+6 original pooled original pooled original pooled                              experiment: MAQC-2

    Little cleanup

    -
    colnames(dat) = as.character(dat[1,])
-dat = dat[-1,]
+
    colnames(dat) <- as.character(dat[1,])
+dat <- dat[-1,]
 head(dat)
    
 
-
           Study                                       PMID Species
-2    bodymap not published, but publicly available here   human
-3     cheung                                   20856902   human
-4       core                                   19056941   human
-5      gilad                                   20009012   human
-6       maqc                                   20167110   human
-7 montgomery                                   20220756   human
-   Number of biological replicates Number of uniquely aligned reads
-2                               19                    2,197,622,796
-3                               41                      834,584,950
-4                                2                        8,670,342
-5                                6                       41,356,738
-6 14 (technical)**  2 (biological)                       71,970,164
-7                               60                     *886,468,054
-    ExpressionSet     Count table Phenotype table
-2            link            link            link
-3            link            link            link
-4            link            link            link
-5            link            link            link
-6 original pooled original pooled original pooled
-7            link            link            link
-                                            Notes
-2 Illumina Human BodyMap 2.0 -- tissue comparison
-3                                    HapMap - CEU
-4                                lung fibroblasts
-5                        liver; males and femlaes
-6                              experiment: MAQC-2
-7                                    HapMap - CEU
    
+
           Study                                       PMID Species  Number of biological replicates Number of uniquely aligned reads
+2    bodymap not published, but publicly available here   human                               19                    2,197,622,796
+3     cheung                                   20856902   human                               41                      834,584,950
+4       core                                   19056941   human                                2                        8,670,342
+5      gilad                                   20009012   human                                6                       41,356,738
+6       maqc                                   20167110   human 14 (technical)**  2 (biological)                       71,970,164
+7 montgomery                                   20220756   human                               60                     *886,468,054
+    ExpressionSet     Count table Phenotype table                                           Notes
+2            link            link            link Illumina Human BodyMap 2.0 -- tissue comparison
+3            link            link            link                                    HapMap - CEU
+4            link            link            link                                lung fibroblasts
+5            link            link            link                        liver; males and femlaes
+6 original pooled original pooled original pooled                              experiment: MAQC-2
+7            link            link            link                                    HapMap - CEU

    Ethics and Web Scraping

    @@ -5611,25 +4900,15 @@

    library(httr) # Requests a random cat fact -query_url = "https://thatcopy.pw/catapi/rest/" +query_url <- "https://thatcopy.pw/catapi/rest/" -req = GET(query_url) +req <- GET(query_url) content(req) -
    $id
-[1] 40
-
-$url
-[1] "https://i.thatcopy.pw/cat/WxT0aQg.jpg"
-
-$webpurl
-[1] "https://i.thatcopy.pw/cat-webp/WxT0aQg.webp"
-
-$x
-[1] 63.21
-
-$y
-[1] 20.35
    +
    {html_document}
+<html class="no-js" lang="en-US">
+[1] <head>\n<meta http-equiv="refresh" content="0">\n<title>thatcopy.pw | 523: Origin is unreachable</title>\n<meta charset="UTF-8"> ...
+[2] <body>\n<div id="cf-wrapper">\n\n    \n\n    <div id="cf-error-details" class="p-0">\n        <header class="mx-auto pt-10 lg:pt ...

    Not all APIs are “open”

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z8Rezaq$FOr9iDcQw~{=wCkw^;(s@6CN+isV~5LtjLz;hATY2^f_Beh~(s&J1&$2 znk)~w<{79h@S~%mNj25=jxtXTOa*lgZoCiuehJ{QH~8LA-ZJ}oM@B$iM)rFz&VH$X ztipnWRZBZRmfA?gZPeQF+?A}j_g@!E0(Jr)f4T13X#K75>4rz>nnx~8q93)Y!@@3YF$;Y=;d&cC}_IDa}Ao!^8QEcCUhl3df!5Q)1A+~<4Lr?HhaF)^{Ht+%Lh?`td#f zF>&<0TVI-v0sF8DI~B72*$XufwCmVtTh1hr^-34j8q%_oYJASkGGOAX({2jbToSx6 zDb-;rb>Mw<+TS^xwl(bw%vPf#`~A)P_eIvuyX)xcG8lBbO7R75r#r5lrc_WUb+o)q z`ST{JsZMpZOE)uexRSY^+4_}FU*Aq+{>73$&i6XHAHNt)F{sMtnf45+ktG$cHli*b z%YV{dEWp9xBoOLfI#hI;zrpN@BVvsF{jb07z59j!`~GO~<$~n#2fR^#-ye-7yn&z^ zHF5vn`=hZK0s_51Ixwor#*r1gL>l+^CDI5y_Rkj+Zif%wtA|nguI|&7FA2y|wCH_`_CX?;d>vq+@&k5zxaC?Q#5l_{aWYkE$Erm^3MR&~-lJv^draO?DK8v*VN zTpV+T8m{=-tAm*bPVpzUKUJv5M~bsHS7colLa;t9h~yT7n@UPaL}Ddpkd9@&6`BC$ zhD1Sh?|cH^S;@f!iWMBr`3pN=;4?3-geNC>n62XaQ9Kk@Yj}}B=f8XN`xjy>$P2T@qAMI>!YDNxY zM_}<$({_$m03;HQK!f{7_{DC`PX7A`7z~aEUo(MXc<|I~6@NH~gc9r+&^_#+$-2Nz3>A#ga*?f$^9;Nmbi zVq?I6M#A9Wo!WoPq5fGh5(Oh(2|*Bxg(!xj&a<{eLW=;TQz592SK@!*Ec= zXgD4Z!2r-j5isJ-B`8J{E=(t)8jV68S_vA3MG!Lsx;z?&hd31+jYa-HIz> z17QZl@X%s|K;u9c`Og@Feu6bvXv~6w2xtNUF$^TcUnQ$C%OHk^dN77iQ6cnWz-@vy9w3H;DKK60)Bl21h`;U;+kK z6Qb1-6l4D=sf3D3kb~9;0(OW60E0pxAvpjP1XB$$g#;ydi1&kXV3P@D1_jA*zl{M4 z2l0I1SR4XuZVCDC-{b=-!6D#>CIl-qu@e#oV+n8d|1lQC@L=yrgdxH90|z_9<0 z4pN8+#(+H%bV58R2*C(`L~I}mg#r(g#Pow56C8m9jsDI5|8f8bBEVjjctQ|EL((n5 z7_iqqBnKXypcoPkXJ;i0um+!3``;a z2@>Q$s&SBbC&-~81`;r^rV@{ZfsHnFJ~#{ofISznARLB9K_UVRVj#1`a^Rx|(1nRH zP!0=SF?g&7j~7rm40uc>VBq@yr5^!45%`0e-z!ECzWYHu7(DGkAEkf|D-0~OhvdMv z=@14|_y-2+$AZWF|7S3GNc~grw;V_ogjP^7=1~6!CRRw91$CgYkSYse7&rjw%|H-~ zL;af`f45;Eh69QH!|LD0fK3Th4h1_Lo?x1RbjyVKz;5*SeE;@;AczNp459=H!$Vp# z&|=kt)ROdVgU`7BB;?ALYVxm Date: Tue, 26 Jul 2022 18:08:26 -0600 Subject: [PATCH 3/7] update labs --- labs/advanced-io-lab-key.R | 40 ++++--- labs/advanced-io-lab-key.Rmd | 34 +++--- labs/advanced-io-lab-key.html | 200 +++++++++++++++++----------------- labs/advanced-io-lab.Rmd | 22 ++-- 4 files changed, 153 insertions(+), 143 deletions(-) diff --git a/labs/advanced-io-lab-key.R b/labs/advanced-io-lab-key.R index f98787b..bb2f09d 100644 --- a/labs/advanced-io-lab-key.R +++ b/labs/advanced-io-lab-key.R @@ -1,45 +1,49 @@ -## ---- include=FALSE----------------------------------------------------------- +## ---- include=FALSE------------------------------------------------------------------------------------------------------------------ library(tidyverse) library(httr) library(jsonlite) library(googlesheets4) -## ----------------------------------------------------------------------------- -sheet_url = "https://docs.google.com/spreadsheets/d/1KIRtcPVn58R3_qr97WNtcOJiY4AaytHzGDzLW_3_R1s/edit?usp=sharing" +## ----eval=FALSE---------------------------------------------------------------------------------------------------------------------- +gs4_auth() -## ----------------------------------------------------------------------------- -x = googlesheets4::read_sheet(sheet_url) +## ------------------------------------------------------------------------------------------------------------------------------------ +sheet_url <- "https://docs.google.com/spreadsheets/d/1KIRtcPVn58R3_qr97WNtcOJiY4AaytHzGDzLW_3_R1s/edit?usp=sharing" -## ----------------------------------------------------------------------------- -googlesheets4::sheet_names(sheet_url) +## ------------------------------------------------------------------------------------------------------------------------------------ +x <- read_sheet(sheet_url) -## ----------------------------------------------------------------------------- -googlesheets4::read_sheet(sheet_url, range = cell_cols(1:2)) -googlesheets4::read_sheet(sheet_url, range = cell_cols("A:B")) +## ------------------------------------------------------------------------------------------------------------------------------------ +sheet_names(sheet_url) -## ----------------------------------------------------------------------------- -jsonData = fromJSON("https://think.cs.vt.edu/corgis/datasets/json/airlines/airlines.json") +## ------------------------------------------------------------------------------------------------------------------------------------ +read_sheet(sheet_url, range = cell_cols("A:B")) -## ---- error = TRUE------------------------------------------------------------ +## ------------------------------------------------------------------------------------------------------------------------------------ +jsonData <- fromJSON("https://think.cs.vt.edu/corgis/datasets/json/airlines/airlines.json") + + +## ---- error = TRUE------------------------------------------------------------------------------------------------------------------- str(jsonData) -## ----------------------------------------------------------------------------- -lga_ord = jsonData %>% +## ------------------------------------------------------------------------------------------------------------------------------------ +lga_ord <- jsonData %>% filter(Airport$Code %in% c("LGA", "ORD") & Time$Year == 2016) -## ----------------------------------------------------------------------------- -airport_compare = as_tibble(list( +## ------------------------------------------------------------------------------------------------------------------------------------ +airport_list <- list( airport_code = lga_ord$Airport$Code, total_flights = lga_ord$Statistics$Flights$Total, delayed_proportion = lga_ord$Statistics$Flights$Delayed / lga_ord$Statistics$Flights$Total - )) + ) +airport_compare <- as_tibble(airport_list) airport_compare diff --git a/labs/advanced-io-lab-key.Rmd b/labs/advanced-io-lab-key.Rmd index a171b4b..e89029f 100644 --- a/labs/advanced-io-lab-key.Rmd +++ b/labs/advanced-io-lab-key.Rmd @@ -16,31 +16,34 @@ library(googlesheets4) This is a lab to practice with Google Sheets and the `googlesheets` package. +Make sure you go through the authentication process. You'll see a popup and will need to grant permissions. + +```{r eval=FALSE} +gs4_auth() +``` + 1. We are going to use a sheet from previous years: https://docs.google.com/spreadsheets/d/1KIRtcPVn58R3_qr97WNtcOJiY4AaytHzGDzLW_3_R1s/edit?usp=sharing ```{r} -sheet_url = "https://docs.google.com/spreadsheets/d/1KIRtcPVn58R3_qr97WNtcOJiY4AaytHzGDzLW_3_R1s/edit?usp=sharing" +sheet_url <- "https://docs.google.com/spreadsheets/d/1KIRtcPVn58R3_qr97WNtcOJiY4AaytHzGDzLW_3_R1s/edit?usp=sharing" ``` - -2. Use the `googlesheets4::read_sheet` function to read in the data like we discussed in class, call this object `x`. +2. Use the `read_sheet()` function to read in the data like we discussed in class, call this object `x`. ```{r} -x = googlesheets4::read_sheet(sheet_url) +x <- read_sheet(sheet_url) ``` 3. Using `sheet_names` function to get the sheet names from the `sheet_url`. ```{r} -googlesheets4::sheet_names(sheet_url) +sheet_names(sheet_url) ``` - -4. Try reading in just the first two columns. See the `range` argument and look at the arguments for `cell_rows`, `cell_limits` and `cell_cols`. +4. Try reading in just the first two columns. Use the `range = cell_cols()` argument. ```{r} -googlesheets4::read_sheet(sheet_url, range = cell_cols(1:2)) -googlesheets4::read_sheet(sheet_url, range = cell_cols("A:B")) +read_sheet(sheet_url, range = cell_cols("A:B")) ``` ## JSON Lab @@ -52,7 +55,7 @@ The following dataset lists airports in the US and details about the number of l 1. Read in data from the following link: https://think.cs.vt.edu/corgis/datasets/json/airlines/airlines.json. Call this `jsonData`. ```{r} -jsonData = fromJSON("https://think.cs.vt.edu/corgis/datasets/json/airlines/airlines.json") +jsonData <- fromJSON("https://think.cs.vt.edu/corgis/datasets/json/airlines/airlines.json") ``` 2. Investigate the data. What are the three main items in `jsonData`? @@ -64,17 +67,20 @@ str(jsonData) 3. Filter `jsonData` to include only NYC LaGuardia and Chicago O'Hare airports (Code : "LGA", "ORD") and Year : 2016. Call this `lga_ord`. ```{r} -lga_ord = jsonData %>% +lga_ord <- jsonData %>% filter(Airport$Code %in% c("LGA", "ORD") & Time$Year == 2016) ``` -4. Create a new tibble out of Airport Code (`Airport$Code`), Total Flights (`Statistics$Flights$Total`), and create a new column for proportion of delayed flights using (`Statistics$Flights$Delayed`). Call this new tibble `airport_compare`. +**Bonus Practice** + +Create a new tibble out of Airport Code (`Airport$Code`), Total Flights (`Statistics$Flights$Total`), and create a new column for proportion of delayed flights using (`Statistics$Flights$Delayed`). Call this new tibble `airport_compare`. ```{r} -airport_compare = as_tibble(list( +airport_list <- list( airport_code = lga_ord$Airport$Code, total_flights = lga_ord$Statistics$Flights$Total, delayed_proportion = lga_ord$Statistics$Flights$Delayed / lga_ord$Statistics$Flights$Total - )) + ) +airport_compare <- as_tibble(airport_list) airport_compare ``` diff --git a/labs/advanced-io-lab-key.html b/labs/advanced-io-lab-key.html index 4845767..8fbb856 100644 --- a/labs/advanced-io-lab-key.html +++ b/labs/advanced-io-lab-key.html @@ -26,11 +26,8 @@ } }); -