CODEWITHSUNDEEP
pythonpandas
prakash poudel
prakash poudel

Reputation: 11

How can I compute my data frame by slicing the index

I have the data as

A=[0.1,0.3,0.5,0.7,0.9,1.1,1.3,1.5,1.7] 
B=[3,4,6,8,2,10,2,3,4]

If A is my index and B is the value corresponding to A. I have to group the first three i.e [0.1,0.3,0.5] and calculate the average in B i.e [3,4,6]. similarly average of 2nd 3 data [8,2,10] corresponding to [0.7,0.9,1.1] and again of [2,3,4] corresponding to [1.3,1.5,1.7] and then prepare the table for this three average values. Final Data frame should be like

A=[1,2,3]
B=[average 1, average 2, average 3]

Upvotes: 1

Views: 32

Answers (1)

jezrael
jezrael

Reputation: 862641

If need aggregate mean by each 3 values use helper array by length of DataFrame with integer division by 3 with GroupBy.mean:

A=[0.1,0.3,0.5,0.7,0.9,1.1,1.3,1.5,1.7] 
B=[3,4,6,8,2,10,2,3,4]
 
df = pd.DataFrame({'col':B}, index=A)
print (df)
     col
0.1    3
0.3    4
0.5    6
0.7    8
0.9    2
1.1   10
1.3    2
1.5    3
1.7    4
df = df.groupby(np.arange(len(df)) // 3).mean()
df.index +=1
print (df)
        col
1  4.333333
2  6.666667
3  3.000000

Upvotes: 1

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