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Load the hmeq _ small.csv data set as a data frame. Standardize the data set as a new data frame. Normalize the data set as

Load the hmeq_small.csv data set as a data frame.
Standardize the data set as a new data frame.
Normalize the data set as a new data frame.
Print the means and standard deviations of both the standardized and normalized data.
Ex: Using the first 100 rows, found in hmeq_sample.csv, the output is:
The means of df1 are LOAN 1.631348e-16
MORTDUE 1.276118e-18
VALUE -2.447266e-17
YOJ -8.732091e-17
CLAGE -1.036208e-16
CLNO -5.068409e-17
DEBTINC 9.188053e-17
dtype: float64
The standard deviations of df1 are LOAN 1.005141
MORTDUE 1.005797
VALUE 1.005420
YOJ 1.005666
CLAGE 1.005602
CLNO 1.005479
DEBTINC 1.017700
dtype: float64
The means of df2 are LOAN 0.671006
MORTDUE 0.358735
VALUE 0.299044
YOJ 0.292135
CLAGE 0.448986
CLNO 0.346377
DEBTINC 0.624927
dtype: float64
The standard deviations of df2 are LOAN 0.269531
MORTDUE 0.247183
VALUE 0.187587
YOJ 0.237945
CLAGE 0.226345
CLNO 0.188681
DEBTINC 0.222946
dtype: float64
# Import the necessary modules
hmeq = # Read in the file hmeq_small.csv
# Standardize the data
standardized = # Code to standardize the data
# Output the standardized data as a data frame
df1= # Code to output as a data frame
# Normalize the data
normalized = # Code to normalize the data
# Output the standardized data as a data frame
df2= # Code to ouput as a data frame
# Print the means and standard deviations of df1 and df2
print("The means of df1 are ", # Code for mean of df1)
print("The standard deviations of df1 are ", # Code for standard deviation of df1)
print("The means of df2 are ", # Code for mean of df2)
print("The standard deviations of df2 are ", # Code for standard deviation of df2)

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