Code
library(tidyverse)
library(readr)
library(readxl)
::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE) knitr
Animesh Sengupta
August 15, 2022
Today’s challenge is to
read in a dataset, and
describe the dataset using both words and any supporting information (e.g., tables, etc)
Read in one (or more) of the following data sets, using the correct R package and command.
Find the _data
folder, located inside the posts
folder. Then you can read in the data, using either one of the readr
standard tidy read commands, or a specialized package such as readxl
.
Add any comments or documentation as needed. More challenging data sets may require additional code chunks and documentation.
Using a combination of words and results of R commands, can you provide a high level description of the data? Describe as efficiently as possible where/how the data was (likely) gathered, indicate the cases and variables (both the interpretation and any details you deem useful to the reader to fully understand your chosen data).
[1] 74 8
[1] "Year and Quarter" "Mortgage" "HE Revolving" "Auto Loan"
[5] "Credit Card" "Student Loan" "Other" "Total"
# A tibble: 5 × 8
`Year and Quarter` Mortgage `HE Revolving` Auto …¹ Credi…² Stude…³ Other Total
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 03:Q1 4.94 0.242 0.641 0.688 0.241 0.478 7.23
2 03:Q2 5.08 0.26 0.622 0.693 0.243 0.486 7.38
3 03:Q3 5.18 0.269 0.684 0.693 0.249 0.477 7.56
4 03:Q4 5.66 0.302 0.704 0.698 0.253 0.449 8.07
5 04:Q1 5.84 0.328 0.72 0.695 0.260 0.446 8.29
# … with abbreviated variable names ¹`Auto Loan`, ²`Credit Card`,
# ³`Student Loan`
---
title: "Challenge 1"
author: "Animesh Sengupta"
desription: "Reading in data and creating a post"
date: "08/15/2022"
format:
html:
toc: true
code-fold: true
code-copy: true
code-tools: true
categories:
- challenge_1
- Animesh Sengupta
- Debt in Trillions data
---
```{r}
#| label: setup
#| warning: false
#| message: false
library(tidyverse)
library(readr)
library(readxl)
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## 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.xlsx ⭐⭐⭐⭐
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}
#| label: Export Data
debt_data <- read_excel("../posts/_data/debt_in_trillions.xlsx")
```
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
dim(debt_data)
colnames(debt_data)
head(debt_data,5)
```