Pandas：创建一个从 excel 文件中选择行的循环

Question

I am trying to read a certain excel file that contains specific data and modify them as well. Although I am not able to create a loop that reads the first 3 rows and then reads rows based on a pattern. I would like to read initially row numbers 1,2,3 then 10,11,12 and so on. I would appreciate any help. Thanks in advance. Have a nice day!

import numpy 
import pandas as pd 

df = pd.read_excel('My Excel File.xlsx')
for i, row in df.iterrows(0,156,3): 
    dfi = df.iloc[(i)].mean()
    df1 =1/(numpy.log10(dfi))
    print(df1) 

Answer 1

Pandas DataFrame.read_excel method has a parameter called skiprows , it can receive multiple types of data, list , int or callable . The latter being a function that would return True if the function should be skipped and False otherwise ( documentation here )

In your case you did not describe the pattern on how rows are skipped, you said row 1,2,3 then 10,11,12. Assuming that you want to skip these specifics rows you can do:

df = pd.read_excel('My Excel File.xlsx', skiprows=lambda x: (x+1) in [1,2,3,10,11,12])

Here I added 1 to x , x represents the index ( ~ line number) starting at 0.

Answer 2

If I understand your question correctly, you want to do something with every n consecutive rows every m rows. Why not use a condition on the iterable?

import numpy 
import pandas as pd 

n = 3
m = 9

df = pd.read_excel('My Excel File.xlsx')
for idx in range(1, len(df.index)-n, m): 
    wanted_df_slice = df.iloc[[idx:idx+n-1]]
    do_stuff(wanted_df_slice)

Edit: @arhr 's approach seems more elegant, as it uses a parameter that is meant precisely for that, and avoids adding a for loop.