Convert a txt file with values seperated to dataframe using pandas in python

Question

How do I convert a text file with values separated to a dataframe?

test.txt:

abc89321 , (('mike', 'A1 passed'),)
abc24862 , (('ross', 'm1 passed'),)
abc17695 , (('carter', 'c2 failed'),)

I have a text file with values like this, how to make these values into a dataframe with two columns?

Expected output:

a           b  
abc89321   (('mike', 'A1 passed'),)
abc24862   (('ross', 'm1 passed'),)
abc17695   (('carter', 'c2 failed'),)

gosuto · Accepted Answer · 2020-04-17 20:06:06Z

2

Use .read_csv() in combination with ast.literal_eval:

from ast import literal_eval

df = pd.read_csv(
    'test.csv',
    sep=' , ',
    names=['a', 'b'],
    engine='python',
    converters={'b': literal_eval}
)

df

          a                       b
0  abc89321    ((mike, A1 passed),)
1  abc24862    ((ross, m1 passed),)
2  abc17695  ((carter, c2 failed),)

edited Apr 17, 2020 at 20:06

answered Apr 17, 2020 at 19:58

gosuto

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