Python - Using Pandas to Work with Series & DataFrames

Python    |    Beginner
  • 11 videos | 1h 10m 56s
  • Includes Assessment
  • Earns a Badge
Rating 4.4 of 81 users Rating 4.4 of 81 users (81)
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.

WHAT YOU WILL LEARN

  • 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

IN THIS COURSE

  • 1m 29s
  • 4m 49s
    Find out how to install and work with Pandas. FREE ACCESS
  • Locked
    3.  Pandas Series Objects
    8m 17s
    In this video, you will create and configure Pandas DataFrame objects. FREE ACCESS
  • Locked
    4.  Operations on Series
    6m 34s
    In this video, you will learn how to perform data wrangling operations on Series objects. FREE ACCESS
  • Locked
    5.  Appending and Sorting Series Values
    8m 50s
    In this video, learn how to use appending and sorting operations on lists. FREE ACCESS
  • Locked
    6.  Pandas DataFrames
    8m 36s
    Learn how to create and configure DataFrame objects in Pandas. FREE ACCESS
  • Locked
    7.  Indexing Operations with DataFrames
    6m 10s
    In this video, you will learn how to perform indexing operations on DataFrames. FREE ACCESS
  • Locked
    8.  Missing Data
    5m 51s
    In this video, you will learn how to identify and troubleshoot data that is missing. FREE ACCESS
  • Locked
    9.  Column Aggregations
    7m 42s
    In this video, you will work with aggregations on columns. FREE ACCESS
  • Locked
    10.  Statistical Operations
    6m 51s
    In this video, you will perform statistical operations on DataFrames. FREE ACCESS
  • Locked
    11.  Exercise: Operations on Series and DataFrames
    5m 49s
    Upon completion of this video, you will be able to recall basic concepts and create Series and DataFrame objects. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Book Python 3 and Data Visualization
Book Pandas in Action
Audiobook Pandas in Action

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course Python for Data Science: Advanced Data Visualization Using Seaborn
Rating 4.5 of 275 users Rating 4.5 of 275 users (275)
Course Python for Data Science: Basic Data Visualization Using Seaborn
Rating 4.6 of 328 users Rating 4.6 of 328 users (328)
Course Python - Pandas Advanced Features
Rating 4.6 of 307 users Rating 4.6 of 307 users (307)