salaryjob2.Rmd

---
title: "Untitled"
output: 
  flexdashboard::flex_dashboard:
    vertical_layout: scroll
    theme: cosmo
---

```{r setup, include=FALSE}
getwd()

setwd("/home/ilke/Downloads")

df<- read.csv("ödev.csv",sep=",", header=TRUE,stringsAsFactors = FALSE)
```


```{r}
library(flexdashboard)
library(ggplot2)
library(readr)
library(highcharter)
library(dplyr)
library(ggplot2)
library(tidyverse)
library(lubridate)
library(readxl)
library(funModeling)
library(gridExtra)
library(magrittr)
library(scales)
library(plotrix)
library(RColorBrewer)
library(readr)
library(maps)
library(highcharter)
library(dplyr)
library(tidyverse)
library(magrittr)
library(DataExplorer)
library(maps)
library(plotly)
library(DT)
library(tidytext)
library(gridExtra)
library(readxl)
library(ggplot2)
library(dplyr)
library(plotly)
library(tidyr)
library(d3Tree)
```






Sample Layout 1 {data-orientation=rows data-icon="fa-bar-chart"}
=====================================

## Row 1 {data-height=110}

### kişi sayısı

```{r}
valueBox(1122, icon = "fa-heart", color="rgb(100,100,100)")
```
### Title Adet

```{r}
valueBox("5", icon = "fa-heart", color="rgb(200,100,100)")
```
### Tip Adedi

```{r}
valueBox("4", icon = "fa-heart",color="rgb(26,110,204)")
```

## Row 2 {data-height=400}  

### Salary-title-type

```{r}
saçılım<- plot_ly(df , x= ~experience_level , y = ~salary , z= ~job_title , color = ~job_title , text = ~salary ) %>%
  add_markers() %>%
  layout(
    scene = list(xaxis = list(title = "LEVEL"),
                 yaxis= list(title = "SALARY"),
                 zaxis = list (title = "TİTLE"))
  )
saçılım
```


    

## Row 3 {data-height=250}  

### Title Sıklıkları

```{r}
#iş sıklıkları
tmp <- df %>% group_by(job_title) %>% tally() %>% mutate(Percent = n/sum(n))
tmp$colors <- c("#d35400", "#2980b9", "#2ecc71","red", "magenta")
tmp <- arrange(tmp,desc(Percent))
highchart() %>% 
  hc_xAxis(categories = c("Data scientist", "Data analyst", "Machine learning", "Big data", "ML Ops")) %>%
  hc_yAxis(title=list(text='Percentage')) %>%
  hc_add_series(tmp, "bar", hcaes(x = job_title, y = Percent, color=colors)) %>% 
  hc_tooltip(pointFormat = "{point.y:.2f}</br>",shared = FALSE) %>% 
  hc_legend(enabled=FALSE)
```

### Type Sıklıkları

```{r}
#type sıklıkları
tmp2 <- df %>% group_by(experience_level) %>% tally() %>% mutate(Percent = n/sum(n))
tmp2$colors <- c("#d35400", "#2980b9", "#2ecc71","magenta")
tmp2 <- arrange(tmp2,desc(Percent))
highchart() %>% 
  hc_xAxis(categories = c("Senior", "Mid", "Entry", "Executive")) %>%
  hc_yAxis(title=list(text='Percentage')) %>%
  hc_add_series(tmp2, "bar", hcaes(x = experience_level, y = Percent, color=colors)) %>% 
  hc_tooltip(pointFormat = "{point.y:.2f}</br>",shared = FALSE) %>% 
  hc_legend(enabled=FALSE)

```
Sample Layout 2 {data-icon="fa-area-chart"}
=====================================  


Column {data-width=250}
-------------------------------------

### ortak
```{r}
ggplot(data = df) + 
  geom_bar(mapping = aes(x = job_title, fill = experience_level), position = "dodge")
```

### remote
```{r}
data <- c(131, 1026)
data_percent <- prop.table(data) * 100
library(ggplot2)
data_df <- data.frame(remote = c("Remote", "No remote"), count = c(131, 1026))

ggplot(data = data_df, aes(x = "", y = count, fill = remote)) + 
  geom_bar(width = 1, stat = "identity") + 
  coord_polar("y", start = 0) + 
  ggtitle("Location Pie Chart") +
  scale_fill_manual(values = c("#00BFC4", "#F8766D")) +
  theme_void() + 
  labs(fill = "location", title = "Location Pie Chart") +
  geom_text(aes(label = paste0(round(data_percent), "%")), position = position_stack(vjust = 0.5))
```

### lokasyon
```{r}
top_10_locations <- df %>% group_by(location) %>% 
  summarise(count=n()) %>% 
  arrange(desc(count)) %>% 
  top_n(10)

ggplot(data = top_10_locations, aes(x = location, y = count, colour = location)) +
  geom_bar(stat = "identity") +
  ggtitle("Lokasyon ve Count") +
  xlab("Lokasyon") +
  ylab("Count")
```