How to export dataframe column wise to separate csv files? And how to append the columns from differ-CodePudding

df1 is this:

    accel_name numb frequency resistance phase
idx                                           
3            K    0       -33          1  4030
4            K    1       -16          2  4028
5            K    2       -18         12  4036
6            K    3       -14         -3  4054
12           K    4        -2         17  4048
13           K    5       -18         12  4048

df2 is this:

    accel_name numb frequency resistance phase
idx                                           
7            P    0      -452       4089   329
8            P    1      -428       4082   427
9            P    2      -382       4078   518
10           P    3      -363       4052   545
11           P    4      -347       4064   508
14           P    5      -373       4068   409

output :

append df2 columns to df1
output frequency.csv, resistance.csv, phase.csv

CodePudding user response：

You can use df.to_csv() to export the relevant dataframes

df = pd.concat([df1, df2], axis=0).sort_index()
cols = ['frequency', 'resistance', 'phase']
for col in cols:
    df[[col]].to_csv(col '.csv')

    accel_name numb frequency resistance phase
idx                                           
3            K    0       -33          1  4030
4            K    1       -16          2  4028
5            K    2       -18         12  4036
6            K    3       -14         -3  4054
7            P    0      -452       4089   329
8            P    1      -428       4082   427
9            P    2      -382       4078   518
10           P    3      -363       4052   545
11           P    4      -347       4064   508
12           K    4        -2         17  4048
13           K    5       -18         12  4048
14           P    5      -373       4068   409

Output:

CodePudding user response：

import pandas as pd
phase = df1['phase']
phase2 = df2['phase']
phases = pd.concat([phase, phase2])
phasees.to_csv('phase_data.csv')

CodePudding user response：

IIUC, use a loop on the concatenated dataframes, slice columns using set operations:

cols = {'frequency', 'resistance', 'phase'}
df = pd.concat([df1, df2])
for c in cols:
    df.drop(columns=cols.difference([c])).to_csv(f'{c}.csv')

example, frequency.csv:

,accel_name,numb,frequency
3,K,0,-33
4,K,1,-16
5,K,2,-18
6,K,3,-14
12,K,4,-2
13,K,5,-18
7,P,0,-452
8,P,1,-428
9,P,2,-382
10,P,3,-363
11,P,4,-347
14,P,5,-373