how to read certain columns from Excel using Pandas - Python

Solution 1:

You can use column indices (letters) like this:

import pandas as pd
import numpy as np
file_loc = "path.xlsx"
df = pd.read_excel(file_loc, index_col=None, na_values=['NA'], usecols="A,C:AA")
print(df)

Corresponding documentation:

usecols : int, str, list-like, or callable default None

• If None, then parse all columns.

• If str, then indicates comma separated list of Excel column letters and column ranges (e.g. “A:E” or “A,C,E:F”). Ranges are inclusive of both sides.

• If list of int, then indicates list of column numbers to be parsed.

• If list of string, then indicates list of column names to be parsed.

  New in version 0.24.0.

• If callable, then evaluate each column name against it and parse the column if the callable returns True.

Returns a subset of the columns according to behavior above.

New in version 0.24.0.

Solution 2:

parse_cols is deprecated, use usecols instead

that is:

df = pd.read_excel(file_loc, index_col=None, na_values=['NA'], usecols = "A,C:AA")

Solution 3:

"usecols" should help, use range of columns (as per excel worksheet, A,B...etc.) below are the examples

1. Selected Columns

df = pd.read_excel(file_location,sheet_name='Sheet1', usecols="A,C,F")

2. Range of Columns and selected column

df = pd.read_excel(file_location,sheet_name='Sheet1', usecols="A:F,H")

3. Multiple Ranges

df = pd.read_excel(file_location,sheet_name='Sheet1', usecols="A:F,H,J:N")

4. Range of columns

df = pd.read_excel(file_location,sheet_name='Sheet1', usecols="A:N")