Challenge 2 Instructions

challenge_2

Author

Kim Darkenwald

Published

August 16, 2022

Code

library(tidyverse)
library(readxl)

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

Challenge Overview

Today’s challenge is to

read in a data set, and describe the data using both words and any supporting information (e.g., tables, etc)
provide summary statistics for different interesting groups within the data, and interpret those statistics

Read in the Data

Read in one (or more) of the following data sets, available in the posts/_data folder, using the correct R package and command.

railroad*.csv or StateCounty2012.xlsx ⭐
FAOstat*.csv ⭐⭐⭐
hotel_bookings ⭐⭐⭐⭐

Code

railroad <- read_excel("_data/StateCounty2012.xls",
                       skip = 4,
                       col_names = c("state", "delete", "county", "delete",
                                     "employees"))%>%
select(!contains("delete"))%>%
  mutate(county=ifelse(state=="CANADA", "CANADA", county))

Because I do not have experience coding, I am using the solutions page and seeing where I have questions. Here are the following questions I have for this code chunk:

Why “skip = 4?”
I assume the “delete” is to delete the empty columns between “state”, “county”, and employees”, however, I don’t understand the “filter(!str_detect(state,”Total”))
I don’t understand the “-2” in the next line.
I’m assuming the last line has two CANADAs in it so that if the “state” has “CANADA” in it, it means the system should put “CANADA” as the county?
Why can’t I see the “New names:”?

Describe the data

Railroad employee totals were gathered for states and their respective counties across the US as well as data from Canada.

Code

select(railroad, filter(railroad, "state", n_distinct))

Error in `select()`:
! Problem while computing `..1 = "state"`.
✖ Input `..1` must be a logical vector, not a character.

Code

summarise(railroad, "state", "total")

# A tibble: 1 × 2
  `"state"` `"total"`
  <chr>     <chr>    
1 state     total

Provide Grouped Summary Statistics

Conduct some exploratory data analysis, using dplyr commands such as group_by(), select(), filter(), and summarise(). Find the central tendency (mean, median, mode) and dispersion (standard deviation, mix/max/quantile) for different subgroups within the data set.

Code

summarize(total_employees = sum (employees))

Error in summarize(total_employees = sum(employees)): object 'employees' not found

Explain and Interpret

Be sure to explain why you choose a specific group. Comment on the interpretation of any interesting differences between groups that you uncover. This section can be integrated with the exploratory data analysis, just be sure it is included.

--- title: "Challenge 2 Instructions" author: "Kim Darkenwald" desription: "Data wrangling: using group() and summarise()" date: "08/16/2022" format: html: toc: true code-fold: true code-copy: true code-tools: true categories: - challenge_2 --- ```{r} #| label: setup #| warning: false #| message: false library(tidyverse) library(readxl) knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE) ``` ## Challenge Overview Today's challenge is to 1) read in a data set, and describe the data using both words and any supporting information (e.g., tables, etc) 2) provide summary statistics for different interesting groups within the data, and interpret those statistics ## Read in the Data Read in one (or more) of the following data sets, available in the `posts/_data` folder, using the correct R package and command. - railroad\*.csv or StateCounty2012.xlsx ⭐ - FAOstat\*.csv ⭐⭐⭐ - hotel_bookings ⭐⭐⭐⭐ ```{r} railroad <- read_excel("_data/StateCounty2012.xls", skip = 4, col_names = c("state", "delete", "county", "delete", "employees"))%>% select(!contains("delete"))%>% mutate(county=ifelse(state=="CANADA", "CANADA", county)) ``` Because I do not have experience coding, I am using the solutions page and seeing where I have questions. Here are the following questions I have for this code chunk: 1. Why "skip = 4?" 2. I assume the "delete" is to delete the empty columns between "state", "county", and employees", however, I don't understand the "filter(!str_detect(state,"Total")) 3. I don't understand the "-2" in the next line. 4. I'm assuming the last line has two CANADAs in it so that if the "state" has "CANADA" in it, it means the system should put "CANADA" as the county? 5. Why can't I see the "New names:"? ## Describe the data Railroad employee totals were gathered for states and their respective counties across the US as well as data from Canada. ```{r} #| label: summary select(railroad, filter(railroad, "state", n_distinct)) summarise(railroad, "state", "total") ``` ## Provide Grouped Summary Statistics Conduct some exploratory data analysis, using dplyr commands such as `group_by()`, `select()`, `filter()`, and `summarise()`. Find the central tendency (mean, median, mode) and dispersion (standard deviation, mix/max/quantile) for different subgroups within the data set. ```{r} summarize(total_employees = sum (employees)) ``` ### Explain and Interpret Be sure to explain why you choose a specific group. Comment on the interpretation of any interesting differences between groups that you uncover. This section can be integrated with the exploratory data analysis, just be sure it is included.