I have created a dataframe from a CSV file and now I'm trying to create a cross-tab of two columns ("Personal_Status" and "Gender"). The output should look like this: Crosstab of Gender and Personal Status including the frequencies of each gender/personal status combination and the totals of each generated row and column.
I tried creditData[["Personal_Status", "Gender"]].value_counts()
but it's not quite where I want it. The output includes a column of each "Personal_Status" value, a "Gender" column, and the frequency of each combination, i.e row 1 = "Single, M, 232"
Any insight is greatly appreciated.
Something like this?
import pandas as pd
df = pd.DataFrame({'Name':['Kathy', 'Linda', 'Peter'],
'Gender': ['F','F','M'],
'Personal_Status':['Divorced','Married','Married']})
df2 = pd.crosstab(df.Personal_Status, df.Gender)
df2.loc['Grand Total']= df2.sum(numeric_only=True, axis=0)
df2.loc[:,'Grand Total'] = df2.sum(numeric_only=True, axis=1)
print(df2)
Output
Gender F M Grand Total
Personal_Status
Divorced 1 0 1
Married 1 1 2
Grand Total 2 1 3