Group dataframe and get sum AND count?

by

try this:

In [110]: (df.groupby('Company Name')
   .....:    .agg({'Organisation Name':'count', 'Amount': 'sum'})
   .....:    .reset_index()
   .....:    .rename(columns={'Organisation Name':'Organisation Count'})
   .....: )
Out[110]:
          Company Name   Amount  Organisation Count
0  Vifor Pharma UK Ltd  4207.93                   5

or if you don’t want to reset index:

df.groupby('Company Name')['Amount'].agg(['sum','count'])

or

df.groupby('Company Name').agg({'Amount': ['sum','count']})

Demo:

In [98]: df.groupby('Company Name')['Amount'].agg(['sum','count'])
Out[98]:
                         sum  count
Company Name
Vifor Pharma UK Ltd  4207.93      5

In [99]: df.groupby('Company Name').agg({'Amount': ['sum','count']})
Out[99]:
                      Amount
                         sum count
Company Name
Vifor Pharma UK Ltd  4207.93     5

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