分组数据框并获得总和和计数? [英] Group dataframe and get sum AND count?

问题描述

我有一个看起来像这样的数据框:

I have a dataframe that looks like this:

              Company Name              Organisation Name  Amount
10118  Vifor Pharma UK Ltd  Welsh Assoc for Gastro & Endo 2700.00
10119  Vifor Pharma UK Ltd    Welsh IBD Specialist Group,  169.00
10120  Vifor Pharma UK Ltd             West Midlands AHSN 1200.00
10121  Vifor Pharma UK Ltd           Whittington Hospital   63.00
10122  Vifor Pharma UK Ltd                 Ysbyty Gwynedd   75.93

我如何求和Amount并计算Organisation Name，以获得一个新的看起来像这样的数据框?

How do I sum the Amount and count the Organisation Name, to get a new dataframe that looks like this?

              Company Name             Organisation Count   Amount
10118  Vifor Pharma UK Ltd                              5 11000.00

我知道如何对或计数求和:

I know how to sum or count:

df.groupby('Company Name').sum()
df.groupby('Company Name').count()

但不是两者都做！

推荐答案

尝试一下:

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

或者如果您不想重置索引:

or if you don't want to reset index:

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

或

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

演示:

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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