Data Wrangling with Pandas: Working with Series & DataFrames


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Pandas, a popular Python library, is part of the open-source PyData stack. In this 10-video Skillsoft Aspire course, you will learn that Pandas represents data in a tabular format which makes it easy and intuitive to perform data manipulation, cleaning, and exploration. You will use Python's DataFrame a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). To take this course, you should already be familiar with Python programming language; all code writing is in Jupyter notebooks. You will work with basic Pandas data structures, Pandas Series objects representing a single column of data which can store numerical values, strings, Booleans, and more complex data types. Learn how to use Pandas DataFrame, which represents data in table form. Finally, learn to append and sort series values, add missing data, add columns, and aggregate data in a DataFrame. The closing exercise involves instantiating a Pandas Series object by using both a list and a dictionary; changing the Series index to something other than default value; and practicing sorting Series values in place.



Expected Duration (hours)
1.2

Lesson Objectives

Data Wrangling with Pandas: Working with Series & DataFrames

  • Course Overview
  • install and work with Pandas
  • create and configure Pandas Series objects
  • perform data wrangling operations on Series objects
  • use appending and sorting operations on Series objects
  • create and configure Pandas DataFrame objects
  • perform indexing operations on DataFrames
  • identify and troubleshoot missing data
  • work with aggregations on columns
  • perform statistical operations on DataFrames
  • recall basic concepts and instantiate Series and DataFrame objects
  • Course Number:
    it_dsdwppdj_01_enus

    Expertise Level
    Beginner