Project Part 1

Creating and setting plotting for project part 1

1. I choose and downloaded the tax revenue data from Our.World.in.data.I choose the Tax revenue data because I was curious about how much tax revenue do countries collect today starting from the year 1980 up to 2019.

2. This is the link to the tax revenue data.

3. I will use the coad chunck below in order to read ans pread the tax revenue data for analysis.

library(tidyverse)
library(here)
library(skimr)

4. Reading the data

file_csv <- here("_posts",
                "2022-05-06-project-part-1",
                "total-tax-revenues-gdp.csv")

tax <-read_csv(file_csv)

5. Using glimpse to see names and types of columns

glimpse(tax)

Rows: 5,757
Columns: 4
$ Entity                                       <chr> "Afghanistan", …
$ Code                                         <chr> "AFG", "AFG", "…
$ Year                                         <dbl> 2003, 2004, 200…
$ `Total tax revenue (% of GDP) (ICTD (2021))` <dbl> 2.512631, 4.076…

6. Use output from glimpse ( and View) to prepare data for analysis

• create object region that will list the regions I will extract data set from.

• Changing the names of 1st column to region and forth column to totl_tax_rev

• Using the filter feature to help extract the rows I want to keep and preview

• Select columns to keep: Region, Year, Tax

• Assign output to regional_tax

• Display first 10 rows of regional_tax

regions <- c(
  "France",
             
  "Germany",
             
  "United Kindom",
           
    "Ukraine",
           
    "Japan",
            
   "United States", 
           
    "Tukey",
          
     "Colombia",
          
     "Ghana",
          
     "Afghanistan" )

regional_tax <- tax %>% 
  rename(Region = Entity) %>% 
  rename(TotalTaxRev = 4) %>% 
  filter(Year >= 1980, Region %in% regions) %>% 
  select(Region, Year, TotalTaxRev) 
 

regional_tax

# A tibble: 276 × 3
   Region       Year TotalTaxRev
   <chr>       <dbl>       <dbl>
 1 Afghanistan  2003        2.51
 2 Afghanistan  2004        4.08
 3 Afghanistan  2005        4.67
 4 Afghanistan  2006        7.12
 5 Afghanistan  2007        6.06
 6 Afghanistan  2008        6.17
 7 Afghanistan  2009        8.67
 8 Afghanistan  2010        9.56
 9 Afghanistan  2011        9.36
10 Afghanistan  2012        7.95
# … with 266 more rows

Check that total for 2015 equals total in graph

regional_tax %>% 
  filter(Year == 2016) %>%            
  summarise(total_tax = sum(TotalTaxRev))

# A tibble: 1 × 1
  total_tax
      <dbl>
1      215.

Add Picture

Total Tax Revenue

Write data to file in the project directory

write_csv(regional_tax, file = "regional_tax.csv")