1. Data Analysis > 
  2. Data Manipulation > 
  3. Next Steps

Next Steps

Now that we learned about manipulating data, you are ready to dive into data visualization. If you want to review data manipulation with pandas before continuing onward, here are some of our favorite resources:

  1. Python | Pandas dataframe.aggregate()
  2. Python | Pandas dataframe.groupby()
  3. How to create new columns derived from existing columns?
  4. Recode Data
  5. How to manipulate textual data?
  6. How to reshape the layout of tables?
  7. pandas.pivot_table
  8. pandas.melt
  9. pandas.pivot
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  • 2. Our Approach to Learning Data Analysis
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  • 3. Intro to Spreadsheets
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  • 5. Exploratory Data Analysis With Spreadsheets
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      • An Introduction to Exploratory Data Analysis
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  • 19. Exploratory Data Analysis with pandas
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      • Exploring Data with pandas
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  • 20. Cleaning Data with Pandas
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  • 21. Data Manipulation
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      • Recoding Data
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  • 22. Data Visualization with Python
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  • 23. Databases with Python and pandas
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  • 24. Tableau Part 1: Intro to Visualization
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      • Task 3: Verify and Submit
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      • Task 2: Tackling Debt
      • Task 3: Housing Prices
      • Task 4: Submitting Your Work
    • A2: 9 to 5
      • Task 1: Database Exploration
      • Task 2: Aggregate Your Friends and Code Some SQL
      • Task 3: Join in on the Fun
      • Task 4: Subqueries, Unions, Derived Tables, Oh My!
    • A3: Call Center Cleanup
      • Task 1: EDA
      • Task 2: Cleaning Data
      • Task 3: Data Manipulation
      • Task 4: Data Visualization
      • Task 5: Summarize and Bonus Mission
    • A4: The Final Project
      • Checkpoint 1: Choose Your Data
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      • Checkpoint 3: Cleaning Data
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      • count Examples
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      • Spreadsheet Mastery: Exercises Part 2
      • Spreadsheet Mastery: Studio Part 2
    • String Methods
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      • find and index examples
      • lower and upper examples
      • replace Examples
      • split Examples
      • strip Examples
    • Dictionary Methods
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