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

Here is problem NaN values are exluded, so necessary use fillna with crosstab:

df1 = pd.crosstab(df['Test_Category'], df['Test_Result'].fillna('n/a'))
print (df1)
Test_Result    Fail  Pass  n/a
Test_Category                 
Cat_1             0     1    1
Cat_2             2     0    0
Cat_3             1     2    1

Or use GroupBy.size with unstack for reshape:

df['Test_Result'] = df['Test_Result'].fillna('n/a')

df1 = df.groupby(['Test_Category','Test_Result']).size().unstack()
print (df1)
Test_Result    Fail  Pass  n/a
Test_Category                 
Cat_1           NaN   1.0  1.0
Cat_2           2.0   NaN  NaN
Cat_3           1.0   2.0  1.0

---

df1 = df.groupby(['Test_Category','Test_Result']).size().unstack(fill_value=0)
print (df1)
Test_Result    Fail  Pass  n/a
Test_Category                 
Cat_1             0     1    1
Cat_2             2     0    0
Cat_3             1     2    1

Another solution with pivot_table:

df = df.pivot_table(index='Test_Category',columns='Test_Result', aggfunc='size')