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vitalstrike82
vitalstrike82

Reputation: 301

Getting the columns to displays month instead of tuples when using pivot_table method

pivot a dataframe using this line:

enter image description here

month_df = pd.pivot_table(loadexpense_df,index="Category",columns="Month",aggfunc={"Month":len}, fill_value=0)

The end result as display below: enter image description here

Q1: How do I write a logic to change the column name ('Month,'Apr) to Apr only and to the rest of column headers?

Q2: Also can pivot table return only the month as header (eg: Apr, May, etc) instead of the tuple (eg: ('Month,'Apr), ('Month,'Aug), etc?

Thanks

Upvotes: 0

Views: 770

Answers (2)

Eduard Ilyasov
Eduard Ilyasov

Reputation: 3308

After getting result of pd.pivot_table() function you get a Dataframe with a columns which represents MultiIndex with two levels. You can solve both of your problems by setting second level of your MultiIndex to Dataframe column labels:

month_df = pd.pivot_table(loadexpense_df,
                          index="Category",
                          columns="Month",
                          aggfunc={"Month":len}, 
                          fill_value=0)

month_df.columns = month_df.columns.get_level_values(level=1)

Upvotes: 2

RoyM
RoyM

Reputation: 747

Q1: Table column-names is contained in month_df.columns, and they are iterable. So:

columns = month_df.columns
tmp = []
for col in columns:
    if len(col) == 2:
        tmp.append(col[1]) #Taking second tuple-value
    else:
        tmp.append(col)

month_df.columns = tmp #Reassigning columns

Q2: I was unable to reproduce your issue with the code given. Mine printed out just fine from the beginning, but I still answered Q1 as I could generate it by hand. But the code

month_df = pd.pivot_table(
    loadexpense_df,index="Category",
    columns="Month",aggfunc={"Month":len},
    fill_value=0)

Gives me only the name of the months as column-names, and not a tuple.

Upvotes: 1

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