Analyzing Data Using Python: Filtering Data in Pandas

Python 3.8    |    Intermediate
  • 10 Videos | 1h 30m 11s
  • Includes Assessment
  • Earns a Badge
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

  • Playable
    1. 
    Course Overview
    2m 10s
    UP NEXT
  • Playable
    2. 
    Performing Data Lookup Operations
    11m 38s
  • Locked
    3. 
    Leveraging the loc and iloc Functions
    10m 6s
    FREE ACCESS
  • Locked
    4. 
    Using the loc, iloc, at, and iat Functions to Filter Data
    11m 54s
    FREE ACCESS
  • Locked
    5. 
    Filtering Data Using Wildcards and Boolean Predicates
    11m 2s
    FREE ACCESS
  • Locked
    6. 
    Using the Query Function to Filter Data
    9m 15s
    FREE ACCESS
  • Locked
    7. 
    Manipulating Data Using Datetime Values
    5m 50s
    FREE ACCESS
  • Locked
    8. 
    Selecting and Dropping Columns
    11m 3s
    FREE ACCESS
  • Locked
    9. 
    Applying Advanced Techniques to Select and Drop Columns
    10m 59s
    FREE ACCESS
  • Locked
    10. 
    Course Summary
    2m 16s
    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 of this course, which can be shared on any social network or business platform

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

COURSE Python Statistical Plots: Time Series Data & Regression Analysis in Seaborn
Likes 0 Likes 0  
COURSE Python & Matplotlib: Getting Started with Matplotlib for Data Visualization
Likes 0 Likes 0  
COURSE Python - Using Pandas to Work with Series & DataFrames
Likes 86 Likes 86