Pandas groupby cumulative sum,mean,median based on the flag values

Question

I need to calculate cumulative calculations (sum,mean,median,etc) based on the values of Indicator

It should do the calculations for all the false indicator and print it adjacent to the true.
then calculated value should reset and start from true until true appears again for Indicator.

Input data frame

Amount	Indicator
10	False
20	False
5	True
8	False
4	False
6	True

output would be

Amount	Indicator	Sum	Mean
10	False
20	False
5	True	30	15
8	False
4	False
6	True	17	5.6

I tried to use groupby with cumsum() using Indicator as group , but have not had any luck yet.

Asked By: ALphaCS

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Source

Answer 1

Let’s use cumsum of Indicator column as group key to get cumsum and size of Amount column

m = df['Indicator'].cumsum()

df['Sum'] = df.groupby(m)['Amount'].cumsum().shift().where(df['Indicator'])
df['Mean'] = df['Sum'].shift(-1).div(df.groupby(m)['Amount'].transform('size')).shift()

print(df)

   Amount  Indicator   Sum       Mean
0      10      False   NaN        NaN
1      20      False   NaN        NaN
2       5       True  30.0  15.000000
3       8      False   NaN        NaN
4       4      False   NaN        NaN
5       6       True  17.0   5.666667

Answered By: Ynjxsjmh

Answer 2

In one go using only one groupby:

df[["Sum", "Mean"]] = np.NaN
df.loc[df.Indicator, ["Sum", "Mean"]] = (df.groupby(df.Indicator.cumsum())
                                         .agg({"Amount": ["sum", "mean"]})
                                         .shift(1).iloc[1:].values)

Answered By: bitflip

Pandas groupby cumulative sum,mean,median based on the flag values

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