Python Pandas : pivot table with aggfunc = count unique distinct

Do you mean something like this?

>>> df2.pivot_table(values='X', index='Y', columns='Z', aggfunc=lambda x: len(x.unique()))Z   Z1  Z2  Z3Y             Y1   1   1 NaNY2 NaN NaN   1

Note that using len assumes you don't have NAs in your DataFrame. You can do x.value_counts().count() or len(x.dropna().unique()) otherwise.

python pandas pivot-table

This is a good way of counting entries within .pivot_table:

>>> df2.pivot_table(values='X', index=['Y','Z'], columns='X', aggfunc='count')        X1  X2Y   Z       Y1  Z1   1   1    Z2   1  NaNY2  Z3   1  NaN

python pandas pivot-table

Since at least version 0.16 of pandas, it does not take the parameter "rows"

As of 0.23, the solution would be:

df2.pivot_table(values='X', index='Y', columns='Z', aggfunc=pd.Series.nunique)

which returns:

Z    Z1   Z2   Z3Y                Y1  1.0  1.0  NaNY2  NaN  NaN  1.0

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