Python - Pandas Advanced Features

Python 3    |    Intermediate
  • 12 videos | 1h 11m 18s
  • Includes Assessment
  • Earns a Badge
Likes 88 Likes 88
This course uses Python, the preferred programming language for data science, to explore Pandas, a popular Python library, and is a part of the open-source PyData stack. In this 11-video Skillsoft Aspire course, learners will use Pandas DataFrame to perform advanced category grouping, aggregations, and filtering operations. You will see how to use Pandas to retrieve a subset of your data by performing filtering operations both on rows, as well as columns. You will perform analysis on multilevel data by using the GROUPBY operation on Dataframe. You will then learn to use data masking or data obfuscation to protect classified or commercially sensitive data. Learners will work with duplicate data, an important part of data cleaning. You will examine the two broad categories of data continuous data which comprise of a continuous range of value, and categorical data has discrete, finite values. Pandas automatically generates indexes for each of our DataFrame rows, and here you will learn to different types of reindexing operations on Dataframe.

WHAT YOU WILL LEARN

  • perform grouping and aggregations on data
    work with multiple, hierarchical indexes
    specify grouping and aggregations with multiple indexes
    perform general user-defined aggregations
    extract subsets of data using filtering
    identify kinds of masking operations
  • troubleshoot data with duplicates
    identify how categorical data differs from continuous
    perform filtering operations on categorical data
    recognize default and custom indexes and reindex DataFrames
    perform filtering operations, drop duplicate data, and work with categories

IN THIS COURSE

  • 1m 37s
  • 5m 17s
    During this video, you will learn how to group and aggregate data. FREE ACCESS
  • Locked
    3.  MultiIndex DataFrames
    4m 53s
    In this video, learn how to work with multiple indexes that are arranged in a hierarchy. FREE ACCESS
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    4.  Grouping and Aggregations with MultiIndex DataFrames
    6m 50s
    Upon completion of this video, you will be able to specify grouping and aggregations with multiple indexes. FREE ACCESS
  • Locked
    5.  General Aggregation Functions
    4m 47s
    In this video, you will learn how to perform general aggregations that are defined by the user. FREE ACCESS
  • Locked
    6.  Filtering
    9m 31s
    In this video, you will extract subsets of data by filtering. FREE ACCESS
  • Locked
    7.  Masking Column Values
    5m 10s
    In this video, you will identify types of masking operations. FREE ACCESS
  • Locked
    8.  Working with Duplicates
    6m 37s
    In this video, you will learn how to troubleshoot data with duplicates. FREE ACCESS
  • Locked
    9.  Working with Categorical Data
    7m 49s
    In this video, you will learn how categorical data differs from continuous data. FREE ACCESS
  • Locked
    10.  Filtering, Adding, and Removing Categories
    7m 21s
    During this video, you will learn how to filter categorical data. FREE ACCESS
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    11.  Reindexing
    6m 35s
    After completing this video, you will be able to recognize default and custom indexes and reindex DataFrames. FREE ACCESS
  • Locked
    12.  Exercise: Filtering, Duplicates and Categorical Data
    4m 53s
    In this video, you will learn how to perform filtering operations, drop duplicate data, and work with categories. FREE ACCESS

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