Pandas, import multiple csv into one data frame with multiple columns

Question

I have 12 csv files which I wanted to import into a data frame in column wise.

For instance, the each 12 csv files are named differently as follows:

filenames = ['experiment_timesteps_1.csv',
             'experiment_timesteps_2.csv',
             'experiment_timesteps_3.csv',
             'experiment_timesteps_4.csv',
             'experiment_timesteps_5.csv',
             'experiment_timesteps_6.csv',
             'experiment_timesteps_8.csv',
             'experiment_timesteps_10.csv',
             'experiment_timesteps_12.csv',
             'experiment_timesteps_15.csv',
             'experiment_timesteps_18.csv',
             'experiment_timesteps_20.csv']

I wanted to use the unique file names (11th to the last 4) as column header in a new data frame. Each file consists of a single column with the same number of rows as follows:

results
266430.1827
318881.2395
285411.9195
279878.2699
272394.9219
239213.2243
274932.4677
290705.0974
315464.9616
240384.0452

I encountered the error with the execution of the following code:

results = DataFrame()
for name in filenames:
    results[name[11:-4]] = read_csv(name, header=0)

ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series

DDD1 · Accepted Answer · 2020-10-07 14:27:05Z

1

If I understood correctly, you can do it as follows:

results = DataFrame()
for name in filenames:
    aux = read_csv(name)
    results[name[11:-4]] = aux["results"]

This will generate a column for each file with the unique identifier you want and the "results" column of each csv will be saved in the corresponding column.

edited Oct 7, 2020 at 14:27

answered Oct 7, 2020 at 14:21

DDD1

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