Скачать или смотреть Python One-Liner: Read Multiple Excel Sheets into Pandas Instantly! ⚡📊

Working with multi-sheet Excel files is super common in analytics and reporting — but manually reading each sheet one by one is time-consuming. Pandas provides a powerful shortcut to read all sheets at once!

Here’s how it works 👇

🧩 Step-by-Step Breakdown (Long Way):

Import the pandas library.

Store your Excel file path (e.g., "sales_data.xlsx").

Use pd.read_excel(file, sheet_name=None) — this returns a dictionary where:

Keys = Sheet names

Values = DataFrames of each sheet.

Loop through the dictionary and print or analyze each sheet individually.

This method gives full control for further processing, cleaning, or merging data from multiple sheets.

⚡ Short & Clean (One-Liner):
[pd.read_excel("sales_data.xlsx", sheet_name=None).items()]


or the version we used:

[print(f"{k}:\n{v.head()}\n") for k,v in pd.read_excel("sales_data.xlsx", sheet_name=None).items()]


This single line reads all sheets and displays the top rows of each — perfect for quick validation or EDA (Exploratory Data Analysis).

💡 Why It’s Useful:

Great for multi-department reports, monthly breakdowns, or multi-sheet data exports.

Saves time — no need to manually specify each sheet name.

Works seamlessly with Excel workbooks containing dozens of sheets.

Codes:

Long Way: Read all sheets from an Excel file into a dictionary of DataFrames
import pandas as pd

excel_file = "sales_data.xlsx"
sheets_dict = pd.read_excel(excel_file, sheet_name=None) # Reads all sheets
for sheet, data in sheets_dict.items():
print(f"Sheet Name: {sheet}")
print(data.head())

One-Liner: Read all sheets at once
import pandas as pd; [print(f"{k}:\n{v.head()}\n") for k,v in pd.read_excel("sales_data.xlsx", sheet_name=None).items()]