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Working with pandas

pandas is one of Python's most popular packages for data analysis and manipulation. It provides powerful data structures like DataFrames, which let you work with structured data efficiently - filtering, aggregating, and transforming datasets with just a few lines of code. As a developer, you'll often encounter pandas when building e-commerce platforms, processing transaction data, or implementing analytics features for business dashboards.

In this exercise, the sales dictionary has been created and contains information on recent transactions.

This exercise is part of the course

Intermediate Python for Developers

View Course

Exercise instructions

  • Import the pandas module using an alias of pd.
  • Convert sales into a DataFrame, saving as sales_df.
  • Preview the first few rows of sales_df.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import pandas as pd
import pandas ____ ____

# Convert sales to a pandas DataFrame
sales_df = ____.____(sales)

# Preview the first few rows
print(sales_df.____())
Edit and Run Code