Python for Data Science: Introduction to Pandas


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

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



Expected Duration (hours)
1.1

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:
    it_dspydsdj_03_enus

    Expertise Level
    Beginner