Using pandas Combining/merging 2 different Excel files/sheets

calendar_today Asked Aug 20, 2014
thumb_up 8 upvotes
history Updated April 14, 2026

Direct Answer

For num. 1, you can specify skip_footer as explained here; or, alternatively, do data = data.iloc[:-2] once your read the data. For num. 2, you may do: from os.path import…. This is an advisory response with reference links, ranked #196th of 303 by community upvote score, from 2014.


The Problem (Q-score 6, ranked #196th of 303 in the Excel VBA archive)

The scenario as originally posted in 2014

I am trying to combine 2 different Excel files. (thanks to the post Import multiple excel files into python pandas and concatenate them into one dataframe)

The one I work out so far is:

import os
import pandas as pd

df = pd.DataFrame()

for f in ['c:\file1.xls', 'c:\ file2.xls']:
    data = pd.read_excel(f, 'Sheet1')
    df = df.append(data)

df.to_excel("c:\all.xls")

Here is how they look like.

enter image description here

However I want to:

  1. Exclude the last rows of each file (i.e. row4 and row5 in File1.xls; row7 and row8 in File2.xls).
  2. Add a column (or overwrite Column A) to indicate where the data from.

For example:

enter image description here

Is it possible? Thanks.

Why community consensus is tight on this one

Across 303 Excel VBA entries in the archive, the accepted answer here holds niche answer (below median) status — meaning voters are unusually aligned on the right fix.


The Verified Solution — niche answer (below median) (+8)

Advisory answer — community consensus with reference links

Note: the verified answer below is a reference / advisory response rather than a copy-ready snippet.

For num. 1, you can specify skip_footer as explained here; or, alternatively, do

data = data.iloc[:-2]

once your read the data.

For num. 2, you may do:

from os.path import basename
data.index = [basename(f)] * len(data)

Also, perhaps would be better to put all the data-frames in a list and then concat them at the end; something like:

df = []
for f in ['c:\file1.xls', 'c:\ file2.xls']:
    data = pd.read_excel(f, 'Sheet1').iloc[:-2]
    data.index = [os.path.basename(f)] * len(data)
    df.append(data)

df = pd.concat(df)


When to Use It — classic (2013–2016)

Ranked #196th in its category — specialized fit

This pattern sits in the 98% tail relative to the top answer. Reach for it when your scenario closely matches the question title; otherwise browse the Excel VBA archive for a higher-consensus alternative.

What changed between 2014 and 2026

The answer is 12 years old. The Excel VBA object model has been stable across Office 2013, 2016, 2019, 2021, 365, and 2024/2026 LTSC, so the pattern still compiles. Changes that might affect you: 64-bit API declarations (use PtrSafe), blocked macros in downloaded files (Mark-of-the-Web), and the shift toward Office Scripts for web-first workflows.

help
Frequently Asked Questions

This is a below-median answer — when does it still fit?
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Answer score +8 vs the Excel VBA archive median ~4; this entry is niche. The score plus 6 supporting upvotes on the question itself (+6) means the asker and 7 subsequent voters all validated the approach.

This answer links out — what are the reference links worth following?
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Read the first external link for the canonical reference, then search this archive for a top-10 entry in the same category — advisory answers are best paired with a ranked code snippet to close the loop.

Published around 2014 — what’s changed since?
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Published 2014, which is 12 year(s) before today’s Office 2026 build. The Excel VBA object model has had no breaking changes in that window. Three things to re-test: (1) blocked macros on downloaded files (Mark-of-the-Web), (2) 64-bit API declarations (PtrSafe, LongPtr), (3) any shift toward Office Scripts for web scenarios.

Which Excel VBA pattern ranks just above this one at #195?
expand_more

The pattern one rank above is “Excel VBA Run Time Error '424' object required”. If your use case overlaps, compare both before committing.

Data source: Community-verified Q&A snapshot. Q-score 6, Answer-score 8, original post 2014, ranked #196th of 303 in the Excel VBA archive. Last regenerated April 14, 2026.