ipeds_mlis

library(tidyverse)

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requireNamespace("plotly")

Loading required namespace: plotly

requireNamespace("DT")

Loading required namespace: DT

ipeds.df <- readRDS("./data/ipeds_completions_2000_2023.RData")

ipeds.df %>%
  filter(field_cip %in%  c("25.0101","25.9999")) %>% # library sceince
  filter(award_level %in% c(7)) %>%  # masters level
  group_by(year)  %>%
  summarise(tot_male = sum(tot_awards_male, na.rm= TRUE),
           tot_female= sum(tot_awards_female, na.rm=TRUE),
           tot_female_white = sum(tot_awards_female_white, na.rm=TRUE),
           tot_male_white = sum(tot_awards_male_white, na.rm=TRUE),
           tot_female_black = sum(tot_awards_female_black, na.rm=TRUE),
           tot_male_black = sum(tot_awards_male_black, na.rm=TRUE),
           tot_grand = tot_male+tot_female,
           p_female = tot_female/tot_grand,
           p_male = 1-p_female,
           p_black = (tot_male_black+tot_female_black)/tot_grand,
           p_white = (tot_male_white+tot_female_white)/tot_grand,
           p_otherrace = 1-p_black-p_white
           ) -> ipeds_lib_tot_year.df

Percentage of MLIS Degrees Awarded to Black Students Over time

{ipeds_lib_tot_year.df %>%
           ggplot(aes(x=year,y=p_black)) + 
           geom_line() 
  } %>% plotly::ggplotly()

{ipeds_lib_tot_year.df %>%
           ggplot(aes(x=year,y=p_otherrace)) + 
           geom_line()} %>% plotly::ggplotly()

Total MLIS Degrees Awarded by Year, Gender & Race (3 categories)

ipeds_lib_tot_year.df %>% 
  DT::datatable(extensions = 'Buttons',
      options = list(dom = 'Bfrltip',
                     buttons = c('csv')),)