• Online, Self-Paced

Pandas is a Python software library used for data science and big data that is used for data manipulation and analysis. In this Skillsoft Aspire course, you will discover how to work with series and tabular data, including initialization, population, and manipulation of Pandas Series and DataFrames.

Learning Objectives

Python for Data Science: Introduction to Pandas

  • Course Overview
  • 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

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Software Development

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.