How To Form A Pivot Table On Two Categorical Columns And Count For Each Index?

I have a data frame of 62 undergrads from a state university with 13 column (age, class, major, GPA, etc.) print(studentSurvey) ID Gender Age Major ... Text Messages 1

Solution 1:

Check crosstab

pd.crosstab(df['Gender'], df['Major'])

Fix your code

studentSurvey.pivot_table(index="Gender", columns="Major", values="ID", aggfunc="count")

Solution 2:

Try:

(studentSurvey.groupby(['Gender','Major'])
     .value_counts()
     .unstack('Major', fill_value=0)
)

Or you can do crosstab:

pd.crosstab(studentSurvey['Gender'], studentSurvey['Major'])