Using Python for Data Management and Reporting

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Chris Behrens

2:34:02

6 View

1. Overview

1. About This Course.mp4

02:15

2. About the Author.mp4

00:43

2. Using Jupyter Notebooks

1. Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 1.mp4

04:19

2. Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 2.mp4

15:00

3. Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 3.mp4

06:00

4. Using and Evaluating Both Code and Markdown Cells, Part 1.mp4

08:54

5. Using and Evaluating Both Code and Markdown Cells, Part 1.mp4

08:28

3. panda DataFrames in Jupyter Notebooks

1. Creating a panda DataFrame and Examining Its Properties, Part 1.mp4

06:43

2. Creating a panda DataFrame and Examining Its Properties, Part 2.mp4

07:16

3. Slicing and Other Operations on panda DataFrames, Part 1.mp4

06:11

4. Slicing and Other Operations on panda DataFrames, Part 2.mp4

05:15

5. Slicing and Other Operations on panda DataFrames, Part 3.mp4

07:05

4. SQL Python Database Packages

1. PEP 249 and Python Database Packages.mp4

06:16

2. Connecting to and Operations on a Database, Part 1.mp4

04:43

3. Connecting to and Operations on a Database, Part 2.mp4

10:57

4. Connecting to and Operations on a Database, Part 3.mp4

01:59

5. MongoDB Package pymongo

1. Using Python MongoDB Package - pymongo.mp4

09:56

6. Delimited Data Text Files

1. What Are Delimited Data Files.mp4

04:33

2. Reading and Writing CSV Files as pandas DataFrames.mp4

04:28

7. Excel Data Files

1. Using pandas DataFrames with Excel.mp4

07:17

8. Writing the Report

1. Brief Overview of Adding LaTeX to a Report.mp4

05:56

2. Good Charting Practices and Review of a Complete Report.mp4

17:36

9. Conclusion

1. Whats Next.mp4

02:12

Description

Get a look at accessing data in common databases, explore Excel operations, and learn about simple report formatting and data visualization.

What You'll Learn?

Data abounds in our world. It is collected in various forms, various ways, and various qualities. It is collected for a multitude of purposes, including collecting for some undefined future use. Being able to access that data and make some sense of it is an important skill for now and the future. Python is an excellent resource for exploring data and making it usable for a variety of purposes. Using Python and Jupyter Notebooks, we will look at accessing data in some common databases, such as MySQL, PostgreSQL, and MongoDB. We will explore Excel operations, such as writing and reading to Excel. We will also explore simple report formatting and data visualization.

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Python

Data Science

Chris Behrens

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