Python Pandas Dynamically Read Excel Sheet with Multiple Header Rows of Different Column Size

Question

I have an excel sheet that I am trying to read into as a dataframe. The sheet has multiple header rows that each can have varying amount of columns. Some of the columns are similar, but no always. Is there a way I can split the rows into separate dataframes?

The data for example would be:

The ideal output would be three separate dataframes which their respective rows and column headers.

Do you know the number of rows after which to split?

Vishnudev Krishnadas
– Vishnudev Krishnadas

2018-11-02 18:52:41 +00:00
Commented Nov 2, 2018 at 18:52 — Vishnudev Krishnadas
– Vishnudev Krishnadas, Commented Nov 2, 2018 at 18:52

Charles Landau · Accepted Answer · 2018-11-02 19:01:24Z

1

.read_excel has header, skiprows and skipfooter arguments that let you do this, provided that you can detect or know ahead of time what row each header is on. With these and usecols you can define any "window" on the sheet as your df. Combining multiple windows can then be accomplished with concat, merge, append, and join, per usual.

answered Nov 2, 2018 at 19:01

Charles Landau

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