I often find myself with several pandas dataframes in the following form:
import pandas as pd df1 = pd.read_table(\'filename1.dat\') df2 = pd.read_table(\'filen
You can set columnA as the index and concat (reset index at the end):
dfs = [df1, df2, df3] pd.concat([df.set_index('columnA') for df in dfs], axis=1).reset_index() Out: columnA first_values second_values third_values 0 name1 342 8 910 1 name2 822 1 301 2 name3 121 1 132 3 name4 3434 2 299