data analysis programming

Business Finance

data analysis programing

Daemen College

Question Description

1/. 2.1 Project: Pandas Series Fundamentals

Overview

Now that we have some Python fundamentals under our belt, let's start using the powerful pandas library. We'll begin by learning a few fundamental concepts while working with Series — or single-column data.

Required Learning Resources

Data Analysis with Pandas and Python – Udemy Course
https://www.udemy.com/course/data-analysis-with-pandas/ (Links to an external site.)

Required Videos

    • 30. Create Jupyter Notebook for the Series Module
    • 31. Create a Series Object from a Python List
    • 32. Create a Series Object from a Python Dictionary
    • 33. Intro to Attributes on a Series Object
    • 34. Intro to Methods on a Series Object
    • 35. Parameters and Arguments
    • 36. Create Series from a Dataset with the pd.read_csv Method
    • 37. Use the head and tail Methods to Return Rows from Beginning and End of Dataset

Instructions

  • In the same project folder as the previous assignment, create a new notebook named 2.1 Pandas Series Fundamentals.
  • Give the notebook a top-level heading to match the file name.
  • Work through the assigned videos. Create at least one new second-level heading per video. (A complex video might require additional headings.) Follow the steps in the corresponding video, creating markdown notes, code, and comments. Demonstrate your familiarity with the concepts covered in the videos. Add appropriate comments to help recall key concepts.

  • As desired, add additional comments or markdown cells to add any additional information and notes you’d like to have for future reference.

  • Pick 3 key concepts and add some additional cells in which you experiment with those concepts in ways that go beyond the examples demonstrated in the videos.

  • For an A+ or potentially for extra credit, add an additional section or two to play and experiment further with key concepts. As desired, search for additional sources of insight into the assigned concepts.

What to Submit

  • Save the notebook.
  • Export your Jupyter Notebook as an HTML file.
  • Upload and submit both the HTML file and the Jupyter file.

Grading Rubric

For an A to A+
Demonstrate thorough coverage of the assigned concepts from the videos. Include well formatted headings, followed by explanatory notes for key concepts in markdown. Add at least 3 sections of one or more cells in which you experiment with the assigned concepts in ways that go beyond the examples in the videos themselves.

For a B to B+
Demonstrate thorough coverage of at least 80% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference.

For a C to C+

Demonstrate thorough coverage of at least 70% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference.

2/ 2.1 Discussion

Use this discussion board to share tips, recommendations, and discussion regarding the assigned project(s).

To foster dialogue, I'm requiring everyone to post something -- whether a question, a reflection, or feedback to other users. Here are recommended ideas to prompt your contributions:

  • Have you gotten stuck? You're undoubtedly not alone. Please describe your problem and include screenshots if relevant.
  • Can you provide help in response to another student's question? If so, please do!
  • Did you discover any helpful tips in this process? Please share it. Provide relevant screenshots, links, etc.

3/ 2.2 Project: Pandas Series Part 2

Unformatted Attachment Preview

1/. 2.1 Project: Pandas Series Fundamentals Overview Now that we have some Python fundamentals under our belt, let's start using the powerful pandas library. We'll begin by learning a few fundamental concepts while working with Series — or single-column data. Required Learning Resources Data Analysis with Pandas and Python – Udemy Course https://www.udemy.com/course/data-analysis-with-pandas/ (Links to an external site.) Required Videos • o o o o o o o o 30. Create Jupyter Notebook for the Series Module 31. Create a Series Object from a Python List 32. Create a Series Object from a Python Dictionary 33. Intro to Attributes on a Series Object 34. Intro to Methods on a Series Object 35. Parameters and Arguments 36. Create Series from a Dataset with the pd.read_csv Method 37. Use the head and tail Methods to Return Rows from Beginning and End of Dataset Instructions 1. In the same project folder as the previous assignment, create a new notebook named 2.1 Pandas Series Fundamentals. 2. Give the notebook a top-level heading to match the file name. 3. Work through the assigned videos. Create at least one new second-level heading per video. (A complex video might require additional headings.) Follow the steps in the corresponding video, creating markdown notes, code, and comments. Demonstrate your familiarity with the concepts covered in the videos. Add appropriate comments to help recall key concepts. 4. As desired, add additional comments or markdown cells to add any additional information and notes you’d like to have for future reference. 5. Pick 3 key concepts and add some additional cells in which you experiment with those concepts in ways that go beyond the examples demonstrated in the videos. 6. For an A+ or potentially for extra credit, add an additional section or two to play and experiment further with key concepts. As desired, search for additional sources of insight into the assigned concepts. What to Submit 1. Save the notebook. 2. Export your Jupyter Notebook as an HTML file. 3. Upload and submit both the HTML file and the Jupyter file. Grading Rubric For an A to A+ Demonstrate thorough coverage of the assigned concepts from the videos. Include well formatted headings, followed by explanatory notes for key concepts in markdown. Add at least 3 sections of one or more cells in which you experiment with the assigned concepts in ways that go beyond the examples in the videos themselves. For a B to B+ Demonstrate thorough coverage of at least 80% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference. For a C to C+ Demonstrate thorough coverage of at least 70% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference. 2/ 2.1 Discussion Use this discussion board to share tips, recommendations, and discussion regarding the assigned project(s). To foster dialogue, I'm requiring everyone to post something -- whether a question, a reflection, or feedback to other users. Here are recommended ideas to prompt your contributions: • • • Have you gotten stuck? You're undoubtedly not alone. Please describe your problem and include screenshots if relevant. Can you provide help in response to another student's question? If so, please do! Did you discover any helpful tips in this process? Please share it. Provide relevant screenshots, links, etc. 3/ 2.2 Project: Pandas Series Part 2 Overview Now that we have some Python fundamentals under our belt, let's start using the powerful pandas library. We'll begin by learning a few fundamental concepts while working with Series — or single-column data. Required Learning Resources Data Analysis with Pandas and Python – Udemy Course https://www.udemy.com/course/data-analysis-with-pandas/ (Links to an external site.) Required Videos • o o o o o 38. Passing pandas Objects to Python Built-In Functions 39. Accessing More Series Attributes 40. Use the sort_values method ... 41. Use the inplace Parameter ... 42. Use the sort-index Method ... o o o 43. Use Python's in Keyword ... 44. Extract Series Values by Index Position 45. Extract Series Values by Index Label Instructions 1. In the same project folder as the previous assignment, create a new notebook named 2.2 Pandas Series Part 2. 2. Give the notebook a top-level heading to match the file name. 3. Work through the assigned videos. Create at least one new second-level heading per video. (A complex video might require additional headings.) Follow the steps in the corresponding video, creating markdown notes, code, and comments. Demonstrate your familiarity with the concepts covered in the videos. Add appropriate comments to help recall key concepts. 4. As desired, add additional comments or markdown cells to add any additional information and notes you’d like to have for future reference. 5. Pick 3 key concepts and add some additional cells in which you experiment with those concepts in ways that go beyond the examples demonstrated in the videos. 6. For an A+ or potentially for extra credit, add an additional section or two to play and experiment further with key concepts. As desired, search for additional sources of insight into the assigned concepts. What to Submit 1. Save the notebook. 2. Export your Jupyter Notebook as an HTML file. 3. Upload and submit both the HTML file and the Jupyter file. Grading Rubric For an A to A+ Demonstrate thorough coverage of the assigned concepts from the videos. Include well formatted headings, followed by explanatory notes for key concepts in markdown. Add at least 3 sections of one or more cells in which you experiment with the assigned concepts in ways that go beyond the examples in the videos themselves. For a B to B+ Demonstrate thorough coverage of at least 80% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference. For a C to C+ Demonstrate thorough coverage of at least 70% of the assigned concepts from the videos. Include well headings for each major concept and at least some notes in markdown or code comments for your future reference. 4/ 2.2 Discussion No unread replies.No replies. Use this discussion board to share tips, recommendations, and discussion regarding the assigned project(s). To foster dialogue, I'm requiring everyone to post something -- whether a question, a reflection, or feedback to other users. Here are recommended ideas to prompt your contributions: • • • Have you gotten stuck? You're undoubtedly not alone. Please describe your problem and include screenshots if relevant. Can you provide help in response to another student's question? If so, please do! Did you discover any helpful tips in this process? Please share it. Provide relevant screenshots, links, etc. ...
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