select specific rows in text file to read into two separate columns in a pandas dataframe

Question

I have a text file like the following

2022-mary ['apple', 'oranges', 'pineapple'] 2022-cindy ['mango', 'banana', 'berry'] 2022-andrew ['coconut', 'cabbage']

I would like to produce a pandas dataframe with 2 columns from the text file above that looks like this

 user fruits 0 2022-mary ['apple', 'oranges', 'pineapple'] 1 2022-cindy ['mango', 'banana', 'berry'] 2 2022-andrew ['coconut', 'cabbage']

I wonder if there is an efficient way to accomplish this with pd.read_csv() functions.

Answer 1

Create one column DataFrame and then selecting even and odd values:

 df = pd.read_csv(file, sep="|", names=['data']) df = pd.DataFrame({'user': df.data.iloc[::2].to_numpy(), 'fruits': df.data.iloc[1::2].to_numpy()})

Or create list:

 with open(file) as f: lines = f.read().splitlines() df = pd.DataFrame({'user': lines[::2], 'fruits': lines[1::2]})