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
Exercise instructions
- Import the
pandasmodule using an alias ofpd. - Convert
salesinto a DataFrame, saving assales_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.____())