如何循环更新许多熊猫数据框

Question

I'm working with many dataframes and I need to update all of them in the same way. I think it would be easier to do it in a loop rather than write a unique line for each change. But I can't manage to update the dataframes.

Here is what I've tried (but doesn't work)

pd1=pd.read_csv('data1.csv')
pd2=pd.read_csv('data2.csv')

samples = [pd1,pd2]

for i, df in enumerate(samples):
    samples[i] = samples[i].truncate(after=99, axis="rows")

Any ideas how to update the changes or iterate through dataframes in a proper way?

Answer 1

This will overwrite your files though, so if you want to preserve the orginial, you'll need to save as a different file name, like:

pd.read_csv(file, nrows=100).to_csv('trunc_'+ file, index=False)

But you can iterate through:

import pandas as pd

filenames = ['data1.csv','data2.csv']

for file in filenames:
    pd.read_csv(file, nrows=100).to_csv(file, index=False)

Answer 2

Assuming 2 dfs as :

print(df1)
   col1  col2 col3 col4
0     1     2    A    S
1     3     4    A    P
2     5     6    B    R
3     7     8    B    B

print(df2)
   col5  col6 col3
0     9    10    A
1    11    12    R

you can update and store in a dictionary as:

samples  = [df1,df2]
frames={}
for e,i in enumerate(samples):
    frames.update([('df'+str(e+1), i.truncate(after=2, axis="rows"))])

print(frames)

{'df1':    col1  col2 col3 col4
0     1     2    A    S
1     3     4    A    P
2     5     6    B    R, 'df2':    col5  col6 col3
0     9    10    A
1    11    12    R}

Now just call the key to get your dataframe:

print(frames['df1'])

   col1  col2 col3 col4
0     1     2    A    S
1     3     4    A    P
2     5     6    B    R