Project

0. Load all the libraries you used in your project in this code chunk

library(tidyverse)
library(here)
library(ggcharts)
library(plotly)
library(scales)
theme_set(theme_minimal())

1. Describe why you selected the dataset. In two or more sentences without spelling or grammatical errors.

2. Download the dataset and read it in

data_in <-  read_csv(file = here("posts", "data_raw.csv"))

3. Use glimpse to preview the data

glimpse(data_in)

4. Data preparation steps (using dplyr functions)- took the appropriate steps to prepare the data for analysis

Describe all the steps that you took to prepare the data for analysis

  • I started with data_in

  • THEN

  • THEN

5. Wrote the data you need for your plots to a csv file

7. Create a static plot (using functions from the ggplot2 and scales packages) with at least three lines. The plot contains appropriate labels, title and caption.

Describe all the steps that you took to create the static plot in two or more sentences without spelling or grammatical errors

8. Create an interactive plot using a function from the plotly package

Describe the step(s) that you took to create an interactive plot

9. Describe insights from your line plots in two or more sentences without spelling or grammatical errors

10. Create a bar chart (using the ggcharts package) with at least one bar highlighted. The plot contains appropriate labels, title and caption

Describe the step(s) that you took to create your bar chart in two or more sentences without spelling or grammatical errors

11. Describe insights from your bar chart in two or more sentences without spelling or grammatical errors

12. Indicate the package(s) that you used in this post and the functions they contain that you used (e.g., used filter from the dplyr package to extract the observations for the four countries, …)

Package: tidyverse

  • includes packages readr, dplyr, ggplot2

Functions from readr

  • read_csv: used for reading in comma separated value file data_raw.csv