The hmeq$\_$small dataset contains information on $5960$ home equity loans, including $7$ features on the characteristics of the loan.

Load the data set hmeq$\_$small.csv as a data frame.

Create a new data frame with all the rows with missing data deleted.

Create a second data frame with the missing data in columns CLNO and YOJ filled in with the mean value of the column.

Print the summaries of the two new data frames.

Ex: Using only the first hundred rows, found in hmeq$\_$sample.csv$,$ the output is:

suppressPackageStartupMessages$($library$($tidyverse$))$

# Read in hmeq$\_$small.csv

hmeq $<-$ # Your code here

hmeq$CLNO $<-$ as$.$numeric$($hmeq$CLNO$)$

# Create a new data frame with the rows with missing values dropped

hmeqDelete $<-$ # Your code here

# Create a new data frame with the missing values of CLNO and YOJ filled in by the mean of the column

meanCLNO $=$ mean$($hmeq$CLNO, na$.$rm$=$TRUE$)$

meanYOJ $=$ mean$($hmeq$YOJ, na$.$rm$=$TRUE$)$

hmeqReplace $<-$ # Your code here

#Print the summary for each new data frame

print$("$Summary of hmeqDelete is $")$

summary$($hmeqDelete$)$

print$("$Summary of hmeqReplace is $")$

summary$($hmeqReplace$)$