从文本文件中读取列 python

Question

I have a large.txt file more than 10000 column names. It doesn't have any feature values and has only the list of features to be added.

To clarify, the text file has the column names in the following format:

Column1
Column2
Column3
Column4
Column5
…

It only has the list of columns that needs to be imported as column names in my data frame.

I would like to read these column names straight into a dataframe. Is this possible with a pandas command eg df = pd.read_XXX()

Basically the final dataframe needs to look

   final_dataframe = df['Column1'] + df['Column2'] + df['Column3'] + df['Column4'] + df['Column5'] 

... If not with pandas, can someone advise on how to read in a file of this type? I am not familiar with this format.

What i have tried so far: i tried something very similar to

df = pd.DataFrame(columns = pd.read_csv('entire_set.txt', header=None)

What this gave me was an empty dataframe with all the column names that I want. This didnt quite help.

To clarify this problem further, i have a dataframe df_full which has more 20k columns with the values. However i need only a subset of that dataframe. The columns that I need in my final dataframe are enlisted in text file entire_set.txt

If my dataframe was small,i could read the column names from my text file and create a new dataframe using the following:

   final_dataframe = df_full['Column1'] + df_full['Column2'] + df_full['Column3'] + df_full['Column4'] + df_full['Column5'] ...

However this isnt viable for larger feature set. are there ways to only use columns in df from df_full with values.

Answer 1

this will create an empty DataFrame where the column names were imported from a txt using pandas:

import pandas as pd

df = pd.DataFrame(columns = pd.read_csv('column_names.txt', header=None)[0].values)

If you already have a Dataframe and you want to select only the columns in the txt file you can do:

import pandas as pd

new_df = old_df[pd.read_csv('column_names.txt', header=None)[0].values]

print(new_df)