library(readxl)
district <- read_excel("district.xls")
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(pastecs)
## 
## Attaching package: 'pastecs'
## The following objects are masked from 'package:dplyr':
## 
##     first, last
summary(district$DPETBLAP)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.000   0.700   2.900   8.765  10.750  98.100

This variable is the percentage of Black/African American students in each district.

cleaned_DPETBLAP <- na.omit(district$DPETBLAP)
hist(cleaned_DPETBLAP,main = "Histogram of DPETBLAP", xlab = "DPETBLAP", col = "blue", border = "black")

library(ggplot2)
cleaned_data <- district %>%mutate(DPETBLAP_log = log(DPETBLAP))
ggplot(cleaned_data, aes(x = DPETBLAP_log)) +
  geom_histogram(binwidth = 0.1, fill = "blue", color = "black") +
  labs(title = "Histogram of Log Transformed DPETBLAP", x = "Log(DPETBLAP)", y = "Frequency") +
  theme_minimal()
## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_bin()`).

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