Pandas, Pivot table from 2 columns with values being a count of one of those columns

Question

I have a pandas dataframe:

+---------------+-------------+
| Test_Category | Test_Result |
+---------------+-------------+
| Cat_1         | Pass        |
|          


        

Answer 1

You could construct a new dataframe using unique values in the two columns as indices and columns, and use pandas' iterrows()

df_out = pd.DataFrame(index=df['Test_Category'].unique().tolist(), columns=df['Test_Result'].unique().tolist())

for index, row in df_out.iterrows():
    for col in df_out.columns:
        df_out.loc[index, col] = len(df[(df['Test_Category'] == index) & (df['Test_Result'] == col)])

Output:

       Pass  nan  Fail
Cat1     1    1     0
Cat2     0    0     2
Cat3     2    1     1

Although using groupby() should definitely be faster.