Using Python for Data Management and Reporting

Using Python for Data Management and Reporting

English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 6h 19m | 996 MB

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 to collect 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 useable 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; writing and reading to Excel. We will also explore simple report formatting and data visualization.

Come on in and let’s have some fun exploring these topics together.

Table of Contents

Overview
1 About This Course
2 About the Author

Using Jupyter Notebooks
3 Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 1
4 Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 2
5 Installing Jupyter Notebooks, Opening a Notebook, and Setting the Kernel, Part 3
6 Using and Evaluating Both Code and Markdown Cells, Part 1
7 Using and Evaluating Both Code and Markdown Cells, Part 1

panda DataFrames in Jupyter Notebooks
8 Creating a panda DataFrame and Examining Its Properties, Part 1
9 Creating a panda DataFrame and Examining Its Properties, Part 2
10 Slicing and Other Operations on panda DataFrames, Part 1
11 Slicing and Other Operations on panda DataFrames, Part 2
12 Slicing and Other Operations on panda DataFrames, Part 3

SQL Python Database Packages
13 PEP 249 and Python Database Packages
14 Connecting to and Operations on a Database, Part 1
15 Connecting to and Operations on a Database, Part 2
16 Connecting to and Operations on a Database, Part 3

MongoDB Package pymongo
17 Using Python MongoDB Package – pymongo

Delimited Data Text Files
18 What Are Delimited Data Files
19 Reading and Writing CSV Files as pandas DataFrames

Excel Data Files
20 Using pandas DataFrames with Excel

Writing the Report
21 Brief Overview of Adding LaTeX to a Report
22 Good Charting Practices and Review of a Complete Report

Conclusion
23 What’s Next