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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