Pandas basic | EntropyObserver

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Step-by-Step Pandas Learning Path 1

Step 1: Sample CSV Data

You can save this as a file named amazon_sales.csv:

Step 2: Read the CSV File

This reads the file into a DataFrame named df.

Step 3: Explore the Data

Shows the first 5 rows of the data.

Shows column types and null values.

Gives statistics for numeric columns: mean, min, max, etc.

Lists all column names.

Step 4: Add New Columns

Convert the date column and create useful new ones:

Add a "Sales" column:

Step 5: Select Data

Select a single column:

Select multiple columns:

Select specific rows by index:

Filter rows where City is Seattle:

Step 6: Group and Aggregate

Total quantity sold for each product:

Total sales per city:

Monthly sales:

Average quantity per product:

Combined stats per product:

Orders per hour of the day:

Average order value per city:

Discount vs quantity sold:

Orders per user:

Sales per category:

Step 7: Sorting

Sort by sales in descending order:

Add a sales rank:

Step 8: Clean the Data

Check for missing values:

Drop missing values:

Check for duplicates:

Drop duplicates:

Step 9: Apply Custom Functions

Add 10 percent tax to the price:

Get first word of product name:

Step 10: Save the Data

Export cleaned data to a new file: