Copy and append colums from one csv to another csv file using python

Question

I have two CSV files. Let them be source.csv and dest.csv

---

source.csv:

  A B C D
  1 3 6 3
  1 4 3 1
  2 4 1 6
  1 3 5 7

dest.csv:

  E F G H
  1 3 5 2
  1 3 4 2
  1 5 2 4
  1 3 5 2

I'm trying to copy the B'th column from source.csv and append it after the column F(position 2) of dest.csv so that the dest.csv will look like this

dest.csv:

  E F B G H
  1 3 3 5 2
  1 3 4 4 2
  1 5 4 2 4
  1 3 3 5 2

Huge thank you to any help provide.

Answer 1

First, you need to read the files, then insert the column and finally save the df as a new csv file:

import pandas as pd

df_source = pd.read_csv('source.csv')
df_dest = pd.read_csv('dest.csv')

df_dest.insert(2,'B',df_source['B']) #This modifies df_dest in place.

df_dest.to_csv('dest_output.csv)

Note that this will only work if both files (source and dest) are in the same location where you are running your script. If not, provide the full paths when reading with the read_csv method. (Ie: read_csv('PATH) ).

Answer 2

i got the answer.!!

def patch(count_of_files):
stitch_key = "BatchOutput_" + str(count_of_files)
files_name = []
for files in os.listdir(directory):  # Loping through directory and taking each files to add to files_name
    if stitch_key in files:
        files_name.append(files)
df = pd.read_csv(directory+"/"+files_name[0], index_col=False)
for i in files_name:
    if i == files_name[0]:  # continuing loop for first file
        continue
    df_temp = pd.read_csv(directory+"/"+i, index_col=False)
    columns_name = df_temp.columns.values.tolist()  # taking all column names into a list
    columns_name = columns_name[7:10]
    percentile_0 = df_temp.iloc[:, [7]]
    percentile_1 = df_temp.iloc[:, [8]]
    percentile_2 = df_temp.iloc[:, [9]]
    df.insert(7, columns_name[0], percentile_0,allow_duplicates=True)  # inserting percentiles into dataframe
    df.insert(7, columns_name[1], percentile_1,allow_duplicates=True)
    df.insert(7, columns_name[2], percentile_2,allow_duplicates=True)
df.to_csv(directory+"/"+files_name[0], index=False)  # converting the dataframe into output csv
for files in files_name:
    if files == files_name[0]:
        continue
    os.remove(directory+"/"+files)