Application

Application#

How to Submit#

Your answers to this chapter’s application questions should be added to the notebook template.

Submit the Colab link on Canvas for the assignment submission.

Application Questions#

Q1: Create your own Series object. Write code the accomplishes the following tasks. Your answer for these items should include a Python program + comments that document process and explain your code.

  • Perform at least two unique arithmetic operations on the Series

  • Test for null values in your series

Q2: Create your own small DataFrame. Write code that accomplishes the following tasks. Your answer for these items should include a Python program + comments that document process and explain your code.

  • Select a specific column(s) using its index label or name attribute

  • Select a specific row(s) using its index label or index value

  • Determine summary statistics for values in the DataFrame

Q3A: Load a structured data file as a DataFrame. You’re welcome to use your own data file, the file from Thursday’s in-class work, or the sample-data.csv file provided with this lab (GitHub, Google Drive).

  • Click here for more background on the sample data.

Q3B: Using the DataFrame you created for Q3A, write code that accomplishes the following tasks. Your answer for these items should include a Python program + comments that document process and explain your code.

  • Shows the first five rows

  • Shows the last five rows

  • Checks the data types for each column

  • Returns a technical summary for the DataFrame

Q3C: Using the DataFrame you created for Q7A, write code that executes AT LEAST FOUR (4) of the following tasks. Your answer for these items should include a Python program + comments that document process and explain your code.

  • Sorts a column by ascending values

  • Sorts a column by descending values

  • Selects a specific column in the DataFrame

  • Creates a new DataFrame with select columns from existing DataFrame

  • Uses a comparison operator to filter rows in the DataFrame

  • Uses an isin statement to filter rows in the DataFrame

  • Selects specific rows and columns

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