Project Part 1

Apple production is measured in tonnes

  1. I downloaded the Apple production, 2018 data from Our World in Data. I chose this data because my friend grew up on an apple farm and the data is very interesting to her.

  2. This is the Link to the data.

  3. The code chunk below will load the package I am using to read and prepare the data for analysis.

    library(tidyverse)
  1. Read the data in
apple_production <- read_csv(here::here("_posts/2022-05-10-project-part-1/apple-production.csv"))
  1. Use glimpse to see the names and types of the columns
glimpse(apple_production)

Rows: 6,198
Columns: 4
$ Entity                                              <chr> "Afghani…
$ Code                                                <chr> "AFG", "…
$ Year                                                <dbl> 1961, 19…
$ `Crops - Apples - 515 - Production - 5510 - tonnes` <dbl> 15100, 1…
# View(apple_production)
  1. Use output from glimpse and view to prepare the data for analysis

Create the object countries this will include the countries that I would like to compare in my dataset.

Change the name of column 1 from entities to countries and column 4 to Tons.

Use filter to extract the rows I want to keep: year 2001

Select the columns to keep Countries, Years, and Tons

Assign the output to apple

Display the first 10 rows of apple

countries <- c("China",
                "European Union",
                "United States",
                "India",
                "Russia",
                "Brazil")

apple <- apple_production  %>%
  rename(Country = 1, Tons = 4)  %>%
  filter(Year >= 2001, Country %in% countries)  %>%
  select(Country, Year, Tons)

apple

# A tibble: 108 × 3
   Country  Year    Tons
   <chr>   <dbl>   <dbl>
 1 Brazil   2001  716030
 2 Brazil   2002  857388
 3 Brazil   2003  841821
 4 Brazil   2004  980203
 5 Brazil   2005  850535
 6 Brazil   2006  863019
 7 Brazil   2007 1115379
 8 Brazil   2008 1124155
 9 Brazil   2009 1222885
10 Brazil   2010 1279124
# … with 98 more rows

Check to see if the total for 2001 equals the total in the graph

apple  %>% filter(Year == 2001)

# A tibble: 6 × 3
  Country         Year     Tons
  <chr>          <dbl>    <dbl>
1 Brazil          2001   716030
2 China           2001 20022749
3 European Union  2001 12985775
4 India           2001  1230000
5 Russia          2001  1640000
6 United States   2001  4274201

Add a picture

apple production 
write_csv(apple, file= "apple.csv")