Challenge 1 Solution

challenge_1

railroads

faostat

wildbirds

Susannah Reed Poland

Reading in data and creating a post

Author

Susannah Reed Poland

Published

June 6, 2023

Code

library(tidyverse)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

Challenge Overview

Today I have read in a dataset and described it.

Read in the Data

I read in the following dataset: railroad_2012_clean_county.csv ⭐

Code

read_csv("_data/railroad_2012_clean_county.csv")

Code

railroad<-read_csv("_data/railroad_2012_clean_county.csv")
railroad

Describe the data

This dataframe seems to contain 3 variables (State, County, and Total Employees) and 2930 observations. Inferring from the title of the table, it seems that this table is showing us the number of people working for the railroad in each county in 2012.

Code

railroad%>%
  select(state)%>%
  n_distinct()

[1] 53

There are 53 unique “States” in the table, and I would presume that this count includes some territories, districts, or areas that are not official U.S. states. Here is a list of the distinct states:

Code

railroad%>%
  select(state)%>%
  distinct()

A quick scan of this list reveals that ‘DC’ is included, which I presume to be the District of Columbia plus others perhaps including Puerto Rico, etc.

---
title: "Challenge 1 Solution"
author: "Susannah Reed Poland"
description: "Reading in data and creating a post"
date: "6/6/2023"
format:
  html:
    df-print: paged
    toc: true
    code-fold: true
    code-copy: true
    code-tools: true
categories:
  - challenge_1
  - railroads
  - faostat
  - wildbirds
  - Susannah Reed Poland
editor_options: 
  chunk_output_type: console
---

```{r}
#| label: setup
#| warning: false
#| message: false

library(tidyverse)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```

## Challenge Overview

Today I have read in a dataset and described it. 

## Read in the Data

I read in the following dataset: railroad_2012_clean_county.csv ⭐

```{r}
read_csv("_data/railroad_2012_clean_county.csv")
railroad<-read_csv("_data/railroad_2012_clean_county.csv")
railroad
```

## Describe the data

This dataframe seems to contain 3 variables (State, County, and Total Employees) and 2930 observations. Inferring from the title of the table, it seems that this table is showing us the number of people working for the railroad in each county in 2012. 

```{r}
#| label: summary
railroad%>%
  select(state)%>%
  n_distinct()
```

There are 53 unique "States" in the table, and I would presume that this count includes some territories, districts, or areas that are not official U.S. states. Here is a list of the distinct states: 

```{r}
railroad%>%
  select(state)%>%
  distinct()

```

A quick scan of this list reveals that 'DC' is included, which I presume to be the District of Columbia plus others perhaps including Puerto Rico, etc.