Excel Analysis with Pandas – Quick Statistics Without Formulas

Sat, 21 Feb 2026 09:00:00 +0100

Why Pandas Instead of Excel Formulas?

Excel is ideal for simple tables, but with larger datasets it quickly becomes unwieldy. With Pandas, you can read, analyze, and statistically evaluate Excel files – reproducibly and automatically.

Installation

pip install pandas openpyxl

openpyxl is required for Excel files (.xlsx).

Reading Excel Files

import pandas as pd

# Read Excel file
df = pd.read_excel('sales_data.xlsx', sheet_name='Revenue')

# First look at the data
print(df.head())
print(df.info())

Important parameters:

sheet_name='Name' – Select specific worksheet
usecols='A:E' – Read only specific columns
skiprows=2 – Skip first rows

Basic Statistics

# Quick overview
print(df.describe())

# Individual statistics
print(f"Average: ${df['Revenue'].mean():.2f}")
print(f"Median: ${df['Revenue'].median():.2f}")
print(f"Minimum: ${df['Revenue'].min():.2f}")
print(f"Maximum: ${df['Revenue'].max():.2f}")
print(f"Total: ${df['Revenue'].sum():.2f}")

Output:

Data Analysis on HeidelSec

Excel Analysis with Pandas – Quick Statistics Without Formulas

Why Pandas Instead of Excel Formulas?

Installation

Reading Excel Files

Basic Statistics