Python - Manipulating & Analyzing Data in Pandas DataFrames

Python 3    |    Intermediate
  • 10 Videos | 48m 10s
  • Includes Assessment
  • Earns a Badge
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Explore advanced data manipulation and analysis with Pandas DataFrames, a Python library that shares similarities with relational databases. To take this course, prior basic experience is needed with Pandas DataFrames, data loading, and Jupyter Notebook data manipulation. You will learn to iterate data in your DataFrame. See how to export data to Excel files, JSON (JavaScript Object Notation) files, and CSV (comma separated values) files. Sort the contents of a DataFrame and manage missing data. Group data with a multi-index. Merge disparate data into a single DataFrame through join and concatenate operations. Finally, you will determine when and where to integrate data with structured queries, similar to SQL.

WHAT YOU WILL LEARN

  • learn how to iterate over a DataFrame's rows and columns
    export the contents of a DataFrame into files of various formats
    describe and apply the different techniques involved in handling datasets where some information is missing
    describe and apply the different techniques involved in handling datasets where some information is missing
    implement a hierarchical index and access the DataFrame's contents based on that index
  • combine two similar DataFrames using the concat operation
    apply a join operation on two related but dissimilar DataFrames using the merge function
    load data into a Pandas DataFrame from a table in a relational database
    use Pandas for advanced tabular data manipulation

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 8s
    UP NEXT
  • Playable
    2. 
    Iterating Over the Contents of a DataFrame
    3m 24s
  • Locked
    3. 
    Exporting a DataFrame
    3m 27s
  • Locked
    4. 
    Sorting
    4m 46s
  • Locked
    5. 
    Handling Missing Data
    5m 36s
  • Locked
    6. 
    Grouping with a Multi-Index
    5m 17s
  • Locked
    7. 
    Merging DataFrames
    3m 24s
  • Locked
    8. 
    Applying Join Operations on DataFrames
    5m 13s
  • Locked
    9. 
    Pandas and Relational Databases
    6m 34s
  • Locked
    10. 
    Exercise: Pandas for Advanced Data Manipulation
    4m 20s

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