Python for Data Science: Introduction to Pandas

Expected Duration
Lesson Objectives
Course Number
Expertise Level


Discover how to work with series and tabular data, including initialization, population, and manipulation of Pandas Series and DataFrames.

Expected Duration (hours)

Lesson Objectives

Python for Data Science: Introduction to Pandas

  • understand the various applications of Pandas and why it is a building block in the field of data science
  • install Pandas and create a Pandas Series
  • work with Pandas Series by accessing elements using the default and a custom index
  • define a Pandas DataFrame and describe how data can be stored and accessed in these data structures
  • initialize and populate a simple Pandas DataFrame
  • load data into a DataFrame from a CSV file
  • edit individual cells and entire rows and columns in a Pandas DataFrame
  • access specific rows and columns of a Pandas DataFrame using the index and labels
  • access parts of a Pandas DataFrame based on specific conditions
  • describe the concept of hierarchical index or multi-index and why can be useful
  • re-orient a DataFrame as a pivot table to better visualize data
  • apply a multi-index to a DataFrame and reshape it using the stack and melt operations
  • work with Pandas for basic tabular data manipulation
  • Course Number:

    Expertise Level