Code
library(tidyverse)
library(readxl)
::opts_chunk$set(echo = TRUE) knitr
Gayan Udugama
July 10, 2022
Today’s challenge is to
read in a dataset, and
describe the dataset using both words and any supporting information (e.g., tables, etc)
Read in one (or more) of the following data sets, using the correct R package and command.
Find the _data
folder, located inside the posts
folder. Then you can read in the data, using either one of the readr
standard tidy read commands, or a specialized package such as readxl
.
Rows: 2930 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): state, county
dbl (1): total_employees
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Add any comments or documentation as needed. More challenging data sets may require additional code chunks and documentation.
Using a combination of words and results of R commands, can you provide a high level description of the data? Describe as efficiently as possible where/how the data was (likely) gathered, indicate the cases and variables (both the interpretation and any details you deem useful to the reader to fully understand your chosen data).
---
title: "Challenge 1"
author: "Gayan Udugama"
desription: "Reading in data and creating a post"
date: "07/10/2022"
format:
html:
toc: true
code-fold: true
code-copy: true
code-tools: true
categories:
- challenge_1
- railroads
- faostat
- wildbirds
---
```{r}
#| label: setup
#| warning: false
#| message: false
library(tidyverse)
library(readxl)
knitr::opts_chunk$set(echo = TRUE)
```
## Challenge Overview
Today's challenge is to
1) read in a dataset, and
2) describe the dataset using both words and any supporting information (e.g., tables, etc)
## Read in the Data
Read in one (or more) of the following data sets, using the correct R package and command.
- railroad_2012_clean_county.csv ⭐
- birds.csv ⭐⭐
- FAOstat\*.csv ⭐⭐
- wild_bird_data.xlsx ⭐⭐⭐
- StateCounty2012.xls ⭐⭐⭐⭐
Find the `_data` folder, located inside the `posts` folder. Then you can read in the data, using either one of the `readr` standard tidy read commands, or a specialized package such as `readxl`.
```{r}
railroad<-read_csv("_data/railroad_2012_clean_county.csv")
```
Add any comments or documentation as needed. More challenging data sets may require additional code chunks and documentation.
## Describe the data
Using a combination of words and results of R commands, can you provide a high level description of the data? Describe as efficiently as possible where/how the data was (likely) gathered, indicate the cases and variables (both the interpretation and any details you deem useful to the reader to fully understand your chosen data).
```{r}
#label: summary
```