Take average of window in pandas-CodePudding

I have a large pandas dataframe, I want to average first 12 rows, then next 12 rows and so on. I wrote a for loop for this task

df_list=[]
for i in range(0,len(df),12):
    print(i,i 12)
    df_list.append(df.iloc[i:i 12].mean())
pd.concat(df_list,1).T

Is there an efficient way to do this without for loop

CodePudding user response：

You can divide the index by N i.e. 12 in your case, then group the dataframe by the quotient, and finally call mean on these groups:

# Random dataframe of shape 120,4
>>> df=pd.DataFrame(np.random.randint(10,100,(120,4)), columns=list('ABCD'))
>>> df.groupby(df.index//12).mean()

           A          B          C          D
0  49.416667  52.583333  63.833333  47.833333
1  60.166667  61.666667  53.750000  34.583333
2  49.916667  54.500000  50.583333  64.750000
3  51.333333  51.333333  56.333333  60.916667
4  51.250000  51.166667  50.750000  50.333333
5  56.333333  50.916667  51.416667  59.750000
6  53.750000  57.000000  45.916667  59.250000
7  48.583333  59.750000  49.250000  50.750000
8  53.750000  48.750000  51.583333  68.000000
9  54.916667  48.916667  57.833333  43.333333

CodePudding user response：

I believe you want to split your dataframe to seperate chunks with 12 rows. Then you can use np.arange inside groupby to take the mean of each seperate chunk:

df.groupby(np.arange(len(df)) // 12).mean()