How to merge multiple files horizontally in a single file with multiple columns?

Question

I have about 1000s of files in a folder with single column data. I want to merge them as single file as filename as header and each file values in separte columns.

For example: File1.txt

-0.000633
-0.001362
-0.001909
-0.002638
-0.00282
-0.004096

File2.txt

-0.003002
-0.003184
-0.004096
-0.003913

File3.txt

-0.002638
-0.000086
0.001736
0.001736
0.001736

File4.txt

I want to merge all these files as follows:

Answer 1

file_list = ['File1.txt', 'File2.txt', 'File3.txt']
df = pd.DataFrame()
for file in file_list:
    temp_df = pd.read_csv(file, header=None, names=[file[:-4]])
    df = pd.concat([df, temp_df], axis=1)
    
print(df)

      File1     File2     File3
0 -0.000633 -0.003002 -0.002638
1 -0.001362 -0.003184 -0.000086
2 -0.001909 -0.004096  0.001736
3 -0.002638 -0.003913  0.001736
4 -0.002820 NaN        0.001736
5 -0.004096 NaN       NaN    

Answer 2

Using bash, and tabs separating columns:

#!/usr/bin/env bash                                                                                                                                                                                                                               

combine() {
    local IFS=$'\t' f
    local -a header
    for f in "$@"; do
        header+=("$(basename "$f" .txt)")
    done
    printf "%s\n" "${header[*]}"
    paste "$@"
}

combine File1.txt File2.txt File3.txt File4.txt > filename

Massaging the filenames into the header line is the tricky bit, paste is an easy way to merge the file contents.

Answer 3

try, read_csv + concat

import pandas as pd

file_list = ["File1.txt", "File2.txt"]

pd.concat([pd.read_csv(f, names=[f.replace('.txt', '')]) for f in file_list], axis=1)