Reserves reports variable names

Project description

# installs
# install.packages("tidyverse")
# install.packages("janitor")
# install.packages("readxl")

# load libraries

library(tidyverse)

## ── Attaching packages ─────────────── tidyverse 1.3.0 ──

## ✓ ggplot2 3.3.0     ✓ purrr   0.3.3
## ✓ tibble  3.0.0     ✓ dplyr   0.8.5
## ✓ tidyr   1.0.2     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.5.0

## ── Conflicts ────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(janitor)

## 
## Attaching package: 'janitor'

## The following objects are masked from 'package:stats':
## 
##     chisq.test, fisher.test

library(readxl)

# get all the variable names

glimpse(fall_2015)

## Rows: 8,664
## Columns: 25
## $ pickup_location        <chr> "AFR", "AFR", "AFR", "AFR", "AFR", "AFR", "AFR…
## $ semester               <chr> "Fall 2015", "Fall 2015", "Fall 2015", "Fall 2…
## $ dept                   <chr> "ASRC", "ASRC", "ASRC", "ASRC", "ASRC", "ASRC"…
## $ course_number          <chr> "ASRC 1500", "ASRC 1500", "ASRC 1500", "ASRC 1…
## $ course_title           <chr> "Introduction to Africana Studies", "Introduct…
## $ instructor             <chr> "Taiwo, Olufemi", "Taiwo, Olufemi", "Taiwo, Ol…
## $ reserve_type           <chr> "Physical Reserve", "Physical Reserve", "Physi…
## $ item_format            <chr> "DVD", "DVD", "DVD", "DVD", "Video", "Video", …
## $ document_type          <chr> "HardCopy", "HardCopy", "HardCopy", "HardCopy"…
## $ item_type              <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ title                  <chr> "Concerning Violence: nine scenes from the Ant…
## $ article_title          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ author                 <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ publisher              <chr> NA, NA, NA, "PBS", NA, NA, NA, NA, NA, NA, NA,…
## $ owning_library         <chr> "Africana", "Africana", "Africana", "Africana"…
## $ display_call_no        <chr> "Videodisc 784", "Videodisc 32", "Videodisc 25…
## $ item_enum              <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ chron                  <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ copy_number            <chr> "1", "1", "1", "1", "1", "1", "4", "1", "1", "…
## $ item_barcode           <chr> "31924121064780", "31924099258877", "319240706…
## $ total_circs            <dbl> 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 2, 1, 0, 0, 1…
## $ volume                 <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ issue                  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ e_reserve_total_clicks <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ e_reserve_total_users  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…

tibize <- function(rawnames) {
  names(rawnames) %>%
  as_tibble()
}

tibize(fall_2015) %>%
  arrange(value)

dfraw <- bind_rows(tibize(fall_2015), tibize(fall_2016), tibize(fall_2018), tibize(fall_2019), tibize(spring_2016), tibize(spring_2017), tibize(spring_2018))

dfraw %>%
  count(value, sort=TRUE)