Excel Analysis with Pandas – Quick Statistics Without Formulas
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: ...