Analyzing Data Using Python: Filtering Data in Pandas

Python    |    Intermediate
  • 10 videos | 1h 26m 11s
  • Includes Assessment
  • Earns a Badge
Rating 4.2 of 24 users Rating 4.2 of 24 users (24)
Not all data is useful. Luckily, there are some powerful filtering operations available in pandas. The course begins with a detailed look at how loc and iloc can be used to access specific data from a DataFrame. You'll move on to filter data using the classic pandas lookup syntax and the pandas filter and query methods. You'll illustrate how the filter function accepts wildcards as well as regular expressions and use various methods such as the .isin method to filter data. Furthermore, you'll filter data using either two pairs of square brackets - in which case the resulting subset is itself a DataFrame - or a single pair of square brackets, in which case the returned data takes the form of a Series. You'll drop rows and columns from a pandas DataFrame and see how rows can be filtered out of a DataFrame. Lastly, you'll identify a possible gotcha that arises when you drop rows in-place but neglect to reset the index labels in your object.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Look up data using different techniques
    Apply the loc and iloc functions to access specific rows and columns
    Filter data using the loc, iloc, at, and iat functions
    Filter data using the loc, iloc, at, and iat functions
  • Perform conditional filtering using the query function
    Parse and manipulate datetime values
    Select and drop specific columns
    Apply regular expressions and other advanced techniques to select and drop columns
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 10s
  • 11m 38s
  • Locked
    3.  Leveraging the loc and iloc Functions
    10m 6s
  • Locked
    4.  Using the loc, iloc, at, and iat Functions to Filter Data
    11m 54s
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    5.  Filtering Data Using Wildcards and Boolean Predicates
    11m 2s
    In this video, you'll learn how to filter data using the loc, iloc, at, and iat functions. You'll start by invoking the sample method on your DataFrame and specifying an input argument of 10. A Jupyter notebook is open on the screen. FREE ACCESS
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    6.  Using the Query Function to Filter Data
    9m 15s
    In this demo, you'll learn how to filter and query data using the query function. You'll learn how to use the filter condition to look up the country column and check for equality with a specific string, which is the United States. You'll then be shown how to build a simple query that returns all rows where the customer is in the United States. FREE ACCESS
  • Locked
    7.  Manipulating Data Using Datetime Values
    5m 50s
  • Locked
    8.  Selecting and Dropping Columns
    11m 3s
  • Locked
    9.  Applying Advanced Techniques to Select and Drop Columns
    10m 59s
  • Locked
    10.  Course Summary
    2m 16s

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