This is a straightforward starter template for reading and analyzing Excel files using pandas in Python. It covers the basics: loading spreadsheets, previewing data with head(), and getting summary statistics with describe(). If you're building something that needs to ingest Excel data through Claude Code, this gives you the bare minimum pandas boilerplate to get moving. It's not a comprehensive Excel manipulation toolkit, more like a quick reference for the most common first steps. The template lives in a larger collection that has 27.7K stars, so there's presumably more context in that repo if you need it.

GitHub stars
30.2K
last updated
Aug 21, 2026

Install

$ npx -y skills add davila7/claude-code-templates --skill 'Excel Analysis' --agent claude-code

Installs into .claude/skills of the current project.

Files

Excel Analysis

Quick start

Read Excel files with pandas:

import pandas as pd

# Read Excel file
df = pd.read_excel("data.xlsx", sheet_name="Sheet1")

# Display first few rows
print(df.head())

# Basic statistics
print(df.describe())

Reading multiple sheets

Process all sheets in a workbook:

import pandas as pd

# Read all sheets
excel_file = pd.ExcelFile("workbook.xlsx")

for sheet_name in excel_file.sheet_names:
    df = pd.read_excel(excel_file, sheet_name=sheet_name)
    print(f"\n{sheet_name}:")
    print(df.head())

Data analysis

Perform common analysis tasks:

import pandas as pd

df = pd.read_excel("sales.xlsx")

# Group by and aggregate
sales_by_region = df.groupby("region")["sales"].sum()
print(sales_by_region)

# Filter data
high_sales = df[df["sales"] > 10000]

# Calculate metrics
df["profit_margin"] = (df["revenue"] - df["cost"]) / df["revenue"]

# Sort by column
df_sorted = df.sort_values("sales", ascending=False)

Creating Excel files

Write data to Excel with formatting:

import pandas as pd

Sponsors

Details

Repository
github.com/davila7/claude-code-templates
Category
Office & Documents
First seen
Jun 3, 2026

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