Create single pandas dataframe from a list of dataframes

Question

I have a list of about 25 dfs and all of the columns are the same. Although the row count is different, I am only interested in the first row of each df. How can I iterate through the list of dfs, copy the first row from each and concatenate them all into a single df?

@DYZ - OP need something else, because partly dupe reopened. — jezrael, Jun 03 '20 at 07:17

score 0 · Accepted Answer · answered Jun 03 '20 at 06:56

0

Select first row by position with DataFrame.iloc and [[0]] for one row DataFrames and join together by concat:

df = pd.concat([x.iloc[[0]] for x in dfs], ignore_index=True)

Or use DataFrame.head for one row DataFrames:

df = pd.concat([x.head(1) for x in dfs], ignore_index=True)

answered Jun 03 '20 at 06:56

jezrael

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can you use .iloc if the row indices are unnamed? – NayyNeww Jun 03 '20 at 07:01
@NayyNeww - yes, it select first row, not important what is index values. – jezrael Jun 03 '20 at 07:02

Create single pandas dataframe from a list of dataframes

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