Introduction to Pandas for Developers Training Video

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A Practical Training Course That Teaches Real World Skills In this project-based Introduction to Pandas for Developers video tutorial series, you'll quickly have relevant skills for real-world applications. Follow along with our expert instructor in this training course to get: Concise, informative and broadcast-quality Introduction to Pandas for Developers training videos delivered to your desktop The ability to learn at your own pace with our intuitive, easy-to-use interface A quick grasp of even the most complex Introduction to Pandas for Developers subjects because they're broken into simple, easy to follow tutorial videos Practical working files further enhance the learning process and provide a degree of retention that is unmatched by any other form of Introduction to Pandas for Developers tutorial, online or offline...so you'll know the exact steps for your own projects. Course Fast Facts: Only 5.5 hours to complete this course 83 tutorial videos Expert instructors lead each course Download to any Windows PC or Mac and save for viewing off line Course is accessible 24/7 from any computer once downloaded You can study from home or at work at your own pace in your own time Course Description In this Introduction to Pandas for Developers training course, expert author Matt Harrison will teach you how to load data in Pandas data structures. This course is designed for users that are already familiar with Python.

You will start by learning about Python lists, Pandas series, and boolean arrays, then jump into learning about dataframes. From there, Matt will teach you about relational algebra, tweaking dataframes, and joins. This video tutorial also covers filtering dataframes, grouping, serialization, plotting, and time series. Finally, you will learn about machine learning and using Pandas with scikit-learn.

Once you have completed this computer based training course, you will have learned about...

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Temario

  • 01. Introduction
    • What Is Pandas?
    • About The Author
    • Installation
    • Pandas Vs. Other Platforms
    • 0105 How To Access Your Working Files
  • 02. Basic Series
    • Python Lists
    • Numpy 1D Arrays
    • Pandas Series
    • Boolean Arrays
    • Series Index
  • 03. More Series
    • 0301 Data Types
    • 0302 Iteration
    • 0303 Broadcasting Operations
    • 0304 Crud Operations Reading
    • 0305 Crud Operations Update
    • 0306 Crud Operations Deletion
    • 0307 Summary Statistics
    • 0308 Dealing With Duplicates
    • 0309 Dealing With Nan
    • 0310 Plotting
    • 0311 Serialization
  • 04. Dataframe Basics
    • 0401 Columnar Data
    • 0402 Similarities To Python Dictionaries
    • 0403 Creation From Lists And Dicts
    • 0404 Reading CSV Files
  • 05. Relational Algebra
    • 0501 Selection
    • 0502 Projection
    • 0503 Cartesian Product
    • 0504 Union
    • 0505 Difference
  • 06. More Dataframes
    • 0601 Exploring Data
    • 0602 Axes Of Dataframes
    • 0603 Index And Columns
    • 0604 Summary Statistics
    • 0605 Histograms
    • 0606 Transposing Data
  • 07. Tweaking Dataframes
    • 0701 Adding Rows
    • 0702 Adding Columns
    • 0703 Applying Functions To Columns
    • 0704 Removing Columns
    • 0705 Sorting Data
    • 0706 Iteration Over Data
    • 0707 Setting Data
  • 08. Joins
    • 0801 Concat With Rows
    • 0802 Concat With Cols
    • 0803 Inner Join
    • 0804 Outer Join
    • 0805 Left Join
    • 0806 Right Join
    • 0807 Join On Index
  • 09. Filtering Dataframes
    • 0901 Filtering Columns
    • 0902 Boolean Arrays
    • 0903 Filtering Rows
    • 0904 Using Functions To Filter
    • 0905 Boolean Operations For Filtering
    • 0906 Dealing With Nan
  • 10. Grouping
    • 1001 Basic Grouping
    • 1002 More Grouping
    • 1003 Pivoting
    • 1004 Stacking/Unstacking
  • 11. Serialization
    • 1101 CSV Reading And Writing
    • 1102 JSON
    • 1103 Pickle
    • 1104 Numpy
    • 1105 Excel
  • 12. Plotting
    • 1201 Basic Plotting
    • 1202 Histograms
    • 1203 Bar Plots
    • 1204 Line Plots
    • 1205 Faceting
  • 13. Time Series
    • 1301 Date Manipulation
    • 1302 Window Functions
    • 1303 Plotting
  • 14. Machine Learning
    • 1401 Using Pandas With Scikit-Learn
    • 1402 Sample Regression
  • 15. Sample Application
    • 1501 Crawling Data
    • 1502 Crawling Data - Part 2
    • 1503 Munging Data
    • 1504 Munging Data - Part 2
    • 1505 Plotting Data
    • 1506 Creating An Infographic
    • 1507 Creating An Infographic - Part 2
  • 16. Conclusion
    • 1601 Conclusion

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