Selecting a column from a pivot table that has been reindexed in pandas

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I have a dataframe that looks like this:

df = pd.DataFrame({'publisher': ['facebook', 'facebook', 'facebook', 'google', 'google', 'google'],
          'month_leadgen': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'],
         'month_payment': ['2019-01', '2019-02', '2019-03', '2019-01', '2019-02', '2019-03'],
         'revenue': [60, 150, 450, 85, 250, 150]})

I then created a pivot table:

df = df.pivot_table(index=['publisher', 'month_leadgen'], columns='month_payment', values='revenue').reset_index()

I am trying to select the column df['2020-01'] but I am receiving an error message:

KeyError: '2020-01'

Can you help me understand why I cannot select this column? The df doesn't seem to be multi indexed. I cannot select any of the month columns but 'month_payment', 'campaign_name', and 'month_leadgen' can be selected no problem.

pandas pivot-table python-3.x python
1 Answers

Use slice(None) to select all the contents the level. slice(None) exempts you from stating contents of the deeper level. it implies them

df=df.pivot_table(index=['publisher', 'month_leadgen'], columns=['month_payment'], values=['revenue']).reset_index()
print(df)



              publisher month_leadgen         revenue                
month_payment                         2019-01 2019-02 2019-03
0              facebook       2019-01    60.0     NaN     NaN
1              facebook       2019-02     NaN   150.0     NaN
2              facebook       2019-03     NaN     NaN   450.0
3                google       2019-01    85.0     NaN     NaN
4                google       2019-02     NaN   250.0     NaN
5                google       2019-03     NaN     NaN   150.0

Selection

df.loc[:, (slice(None), '2019-01')]

 

               revenue
month_payment   2019-01
0                60.0
1                 NaN
2                 NaN
3                85.0
4                 NaN
5                 NaN
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