2.2_2.3: Visualizing Data

Visualizing Data from existing Data in a csv or excel file or txt

Histogram of Income from Credit data

library(readr)
Credit <- read_csv("Credit.csv")

## Parsed with column specification:
## cols(
##   id = col_double(),
##   Income = col_double(),
##   Limit = col_double(),
##   Rating = col_double(),
##   Cards = col_double(),
##   Age = col_double(),
##   Education = col_double(),
##   Gender = col_character(),
##   Student = col_character(),
##   Married = col_character(),
##   Ethnicity = col_character(),
##   Balance = col_double()
## )

icm <- Credit$Income

hist(icm, 
      # breaks tell R how many bars you want
      # R can decide to choose what is reasonable 
     breaks = 10,
     main = "Income Distribution",
     xlab = "Income",
     xlim = c(0,250),
     ylim = c(0,200),
     col = "grey",
     freq = TRUE)

Histogram of Balance from Credit Card Data

bal <- Credit$Balance
hist(bal, 
      # breaks tell R how many bars you want
      # R can decide to choose what is reasonable 
     breaks = 12,
     main = "Balance Distribution",
     xlab = "Balance",
     xlim = c(0,2500),
     ylim = c(0,150),
     col = "red",
     freq = TRUE)

Bar Graph of Ethnicity from Credit Card Data

ethty <- Credit$Ethnicity
ethty_1 <- table(ethty)
barplot(ethty_1,
     main = "Bar Graph of Ethnicity",
     xlab = "Ethnicity",
     ylab = "Frequency",
     ylim = c(0,250),
     col="green")

Pie Chart of Ethnicity from Credit Card Data

ethty <- Credit$Ethnicity
ethty_1 <- table(ethty)
    # calculate percentages
pct <- round(ethty_1/sum(ethty_1)*100,2)
    # add percents to labels
lbls <- paste(names(ethty_1), pct, "%") 
pie(ethty_1,
     main = "Pie Chart of Ethnicity", 
    col=c("grey", "skyblue3", "skyblue1"),
    labels=lbls)