Update 04152024

BITSS · Apr 15, 2024 · 98b5099 · 98b5099
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diff --git a/01-data-filtering.md b/01-data-filtering.md
@@ -13,22 +13,17 @@ Copy cleanned data sets (tidy df) from the `SSRP_cleanining` repo into this repo
 
 <div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
 
-
 ```r
 tidy_dfs <- list.files(paste0(clean_path,"/processed/"))
 file.copy(paste0(clean_path,"/processed/",tidy_dfs), 
           paste0("./processed/",tidy_dfs),
           overwrite = TRUE)
 ```
 
-
-
 ```
  [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
 ```
 
-
-
 ### First: basic clean up  
 - load data  
 - rename the title of a reproduction  
@@ -38,7 +33,6 @@ file.copy(paste0(clean_path,"/processed/",tidy_dfs),
 
 <div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
 
-
 ```r
 dis_df <- read_csv("./processed/tidy_di_df.csv") %>%
     mutate(
@@ -54,13 +48,10 @@ dis_df <- read_csv("./processed/tidy_di_df.csv") %>%
     filter(!is.na(repro_score))
 ```
 
-
-
 - Same but to claims-level data
 
 <div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
 
-
 ```r
 claims_df <- read_csv("./processed/tidy_claim_df.csv") %>%
     mutate(paper_title= ifelse(
@@ -75,13 +66,10 @@ claims_df <- read_csv("./processed/tidy_claim_df.csv") %>%
     ) # 98 reproductions (no abandoned)
 ```
 
-
-
 - Same to abandoned papers
 
 <div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
 
-
 ```r
     abandoned_df <- read_csv("./processed/tidy_abandoned_df.csv") %>%
     mutate(paper_title= ifelse(
@@ -96,15 +84,12 @@ claims_df <- read_csv("./processed/tidy_claim_df.csv") %>%
     )  # 104 reproductions total
 ```
 
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 # Make sure there's at least one scored Display Item
 
 The rationale for this filter is that papers should have some sort of reproducibility score associated with them to be counted.
 
 <div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
 
-
 ```r
 has_score <- dis_df %>%
     select(reproduction_id) %>%
@@ -116,8 +101,6 @@ claims_df <- claims_df %>%
 ```
 
 
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-
 # Future Filters
 
 This section explains how to add a filter in the future. Additional features should have a title (e.g. "Make sure there's at least one estimate associated with each claim") followed by a description of the reason we want this filter.