Import data
# excel file
data <- read_excel("data/myData_charts.xls")
## New names:
## • `` -> `...1`
data
## # A tibble: 16,383 × 29
## ...1 year unitid institution_name city_txt state_cd zip_text
## <dbl> <dbl> <dbl> <chr> <chr> <chr> <dbl>
## 1 1 2015 100654 Alabama A & M University Normal AL 35762
## 2 2 2015 100654 Alabama A & M University Normal AL 35762
## 3 3 2015 100654 Alabama A & M University Normal AL 35762
## 4 4 2015 100654 Alabama A & M University Normal AL 35762
## 5 5 2015 100654 Alabama A & M University Normal AL 35762
## 6 6 2015 100654 Alabama A & M University Normal AL 35762
## 7 7 2015 100654 Alabama A & M University Normal AL 35762
## 8 8 2015 100654 Alabama A & M University Normal AL 35762
## 9 9 2015 100654 Alabama A & M University Normal AL 35762
## 10 10 2015 100654 Alabama A & M University Normal AL 35762
## # ℹ 16,373 more rows
## # ℹ 22 more variables: classification_code <dbl>, classification_name <chr>,
## # classification_other <chr>, ef_male_count <dbl>, ef_female_count <dbl>,
## # ef_total_count <dbl>, sector_cd <dbl>, sector_name <chr>, sportscode <dbl>,
## # partic_men <chr>, partic_women <chr>, partic_coed_men <chr>,
## # partic_coed_women <chr>, sum_partic_men <dbl>, sum_partic_women <dbl>,
## # rev_men <chr>, rev_women <chr>, total_rev_menwomen <chr>, exp_men <chr>, …
Plot prices
#data %>%
#ggplot(aes(rank)) +
#geom_bar()
library(ggplot2)
# plot the age distribution using a histogram
ggplot(data, aes(x = sports)) +
geom_bar() +
labs(title = "Frequency of Sports",
x = "Sports",
y = "Count")
