Counting String Values in Pivot Across Multiple Columns

I’d like to use Pandas to pivot a table into multiple columns, and get the count of their values.

In this example table:

How do I pivot out this table to show total counts of each string within "Parking Type"? Maybe my mistake is calling this a "pivot?"

Desired output:

Currently, I have a pivot going, but it is only counting the values of the first column, and leaving everything else as 0s. Any guidance would be amazing.

Current Code:

pivot = pd.pivot_table(df, index=["LOCATION"], columns=['PARKING TYPE'], aggfunc=len)
pivot = pivot.reset_index()
pivot.columns = pivot.columns.to_series().apply(lambda x: "".join(x))

>Solution :

You could use pd.crosstab:

out = (pd.crosstab(index=[df['LOCATION'], df['ADDRESS']], columns=df['PARKING TYPE'])
       .reset_index()
       .rename_axis(columns=[None]))

or you could use pivot_table (but you have to pass "ADDRESS" into the index as well):

out = (pd.pivot_table(df, index=['LOCATION','ADDRESS'], columns=['PARKING TYPE'], values='ADDRESS', aggfunc=len, fill_value=0)
       .reset_index()
       .rename_axis(columns=[None]))

Output:

  LOCATION   ADDRESS  LARGE LOT  MEDIUM LOT  SMALL LOT
0  AAA0001  123 MAIN          1           0          1
1  AAA0002  456 TOWN          1           0          0
2  AAA0003   789 AVE          0           2          0