
Excel Analysis
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-codeInstalls 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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