Reading in the Data (Homework 2): Birds

Practice getting the dataset into RStudio and beginning to understand it.

Before we begin…

knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)

Read in the Data

The first step is getting everything up and running.

setwd("../../_data") # set working directory
birds <- read_csv("birds.csv") # assign dataset to variable

First, what are the dimensions and column names?

dim(birds) # dim() returns dimensions of dataset

[1] 30977    14

colnames(birds) # colnames() returns column names

 [1] "Domain Code"      "Domain"           "Area Code"       
 [4] "Area"             "Element Code"     "Element"         
 [7] "Item Code"        "Item"             "Year Code"       
[10] "Year"             "Unit"             "Value"           
[13] "Flag"             "Flag Description"

Okay, and what does this data look like?

head(birds) #head() shows the first few columns of data

# A tibble: 6 x 14
  `Domain Code` Domain       `Area Code` Area   `Element Code` Element
  <chr>         <chr>              <dbl> <chr>           <dbl> <chr>  
1 QA            Live Animals           2 Afgha~           5112 Stocks 
2 QA            Live Animals           2 Afgha~           5112 Stocks 
3 QA            Live Animals           2 Afgha~           5112 Stocks 
4 QA            Live Animals           2 Afgha~           5112 Stocks 
5 QA            Live Animals           2 Afgha~           5112 Stocks 
6 QA            Live Animals           2 Afgha~           5112 Stocks 
# ... with 8 more variables: Item Code <dbl>, Item <chr>,
#   Year Code <dbl>, Year <dbl>, Unit <chr>, Value <dbl>, Flag <chr>,
#   Flag Description <chr>

So, overall it doesn’t seem incredibly messy, just very big!

Conclusion

The next step here is to wrangle the data. Since this set is very big, it will be key to understand what we actually need (what columns etc.) to do the analysis we want to do!

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