Using Pandas to calculate using groupby() and sum() from a DataFrame-CodePudding

I am currently in the process of learning Pandas and I am stuck at an exercise.

My problem is as follows: I need to calculate the number of total purchases by a cardholder in a month of more than $25000. For this I have been given a hint that I first must create a DataFrame that includes the total purchases by each cardholder in each month (using the groupby() and sum() methods), and then use this DataFrame to do the calculation.)

df_3= df[['Calendar Month','Cardholder Name']].groupby(df['Amount']).sum()
df_3

Which gives the following output

 Amount  Calendar Month Cardholder Name
    
-5924.00    5   JEFFRIES, T
-5522.21    11  LAIR, M
-4800.00    11  KENT, D
-4444.23    6   LAIR, M
-4364.50    2   FOISY, J
... ... ...
20876.68    3   JEFFRIES, T
27087.50    12  COLE, J
29585.16    2   JEFFRIES, T
57510.00    1   LACEY, L
62181.77    4   LACEY, L

I think that this initial Dataframe (df_3) is right, but I don't know how the actual calculation must be done to calculate the number of total purchases by a cardholder in a month of more than $25000.

CodePudding user response：

here is one way to do it. you store the groupby result in a var and then filter it on your condition.

gb=df.groupby(['Month','Cardholder Name'])['amount'].sum().to_frame()

gb[gb['amount'] > 25000]

                         amount
Month   Cardholder Name     
1       LACEY, L         57510.00
2       JEFFRIES, T      29585.16
4       LACEY, L         62181.77
12      COLE, J          27087.50