Python - Introduction to Pandas and DataFrames

Python 3
  • 14 Videos | 1h 5m 35s
  • Includes Assessment
  • Earns a Badge
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Simplify data analysis with Pandas DataFrames. Pandas is a Python library that enables you to work with series and tabular data, including initialization, and population. For this course, learners do not need prior experience working with Pandas, but should be familiar with Python3, and Jupyter Notebooks. Topics include the following: Define your own index for a Pandas series object; load data from a CSV (comma separated values) file, to create a Pandas DataFrame; Add and remove data from your Pandas DataFrame; Analyze a portion of your DataFrame; Examine how to reshape or reorient data, and to create a pivot table. Finally, represent multidimensional data in two-dimensional DataFrames, with multi or hierarchical indexes.

WHAT YOU WILL LEARN

  • understand the various applications of Pandas and why it is a building block in the field of data science
    install Pandas and create a Pandas Series
    work with Pandas Series by accessing elements using the default and a custom index
    define a Pandas DataFrame and describe how data can be stored and accessed in these data structures
    initialize and populate a simple Pandas DataFrame
    load data into a DataFrame from a CSV file
    edit individual cells and entire rows and columns in a Pandas DataFrame
  • access specific rows and columns of a Pandas DataFrame using the index and labels
    access parts of a Pandas DataFrame based on specific conditions
    describe the concept of hierarchical index or multi-index and why can be useful
    re-orient a DataFrame as a pivot table to better visualize data
    apply a multi-index to a DataFrame and reshape it using the stack and melt operations
    work with Pandas for basic tabular data manipulation

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 19s
    UP NEXT
  • Playable
    2. 
    Features of Pandas and the Pandas Ecosystem
    3m 5s
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    3. 
    Introduction to Pandas
    5m 42s
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    4. 
    Work with Pandas
    6m 14s
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    5. 
    Introduction to DataFrames
    2m 27s
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    6. 
    Work with DataFrames
    5m 59s
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    7. 
    Load Data into a DataFrame
    2m 54s
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    8. 
    Add and Delete DataFrame Contents
    8m 1s
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    9. 
    Select Parts of a DataFrame
    5m 22s
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    10. 
    Access Pandas DataFrames
    5m 23s
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    11. 
    Introduction to Multi-Indexing in a Dataframe
    3m 1s
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    12. 
    Reshape DataFrames
    4m 22s
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    13. 
    Reshape Dataframes Using Stack and Melt Operations
    6m 31s
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    14. 
    Exercise: Pandas for Basic Tabular Data Manipulation
    4m 15s

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