Python and ReportLab for Efficient Reporting and Automation

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R-Tutorials Training

2:15:06

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1. Workspace Setup

1.1 notes.pdf

1. Introduction.mp4

00:40

2.1 resources.zip

2. Information on Resources.html

3. Virtual Environment Setup.mp4

03:24

4.1 requirements.txt

4. Installing Python Libraries.mp4

02:36

2. ReportLab Groundwork

1.1 01-reportlab-groundwork.zip

1. Introduction.mp4

01:10

2. The Canvas Object of PDFgen.mp4

07:34

3. ReportLab Anatomy - The Hierarchy of Document Building Blocks.mp4

03:56

4. Building Documents with PLATYPUS - Create Your Own Page and Document Templates.mp4

08:35

5. Include Data Visualizations in Your Reports with Figure to Image Conversion.mp4

05:42

6. Add Tables to Your Report Easily with DataFrame to Table Conversion.mp4

03:19

7. Styling Your Paragraphs and Tables with Dedicated Style Objects.mp4

05:18

8. Overview.mp4

02:01

3. Document Data Analysis Progress with ReportLab

1. Introduction.mp4

01:08

2.1 cereal.csv

2. The Cereal Dataset.mp4

01:45

3. Dataset Import.mp4

03:34

4. Data Type Management with NumPy and alternatives with PyArrow.mp4

03:36

5. Identifying and Handling Invalid Observations.mp4

04:12

6. Equalizing Nutritional Values on the Basis of Weight.mp4

05:49

7. Extending the Analysis with Nutritional Test.mp4

05:14

8. Declaring Variable Units.mp4

02:54

9. Auxiliary Tables.mp4

02:54

10. Improving the Print in the PDF Document.mp4

02:36

11. Overview.mp4

01:49

4. Including Data Visualizations in Your Reports

1. Introduction.mp4

00:43

2. The Matplotlib Figure Object.mp4

00:43

3. Regular Pyplot Charts and the Pandas Plotting System.mp4

05:28

4. Exporting Results of Custom Data Visualization Functions.mp4

06:17

5. Including a Subplot Grid in a Report.mp4

04:39

6. Various Types of Plots Created with Seaborn - Plot Matrix and Facet Grid Plot.mp4

04:43

7. Overview.mp4

00:49

5. Updating and Extending the Report

1.1 02-updating-the-report.zip

1. Introduction.mp4

01:21

2. Introducing Additional Page Templates.mp4

02:16

3. Updating Flowable Style Objects.mp4

03:06

4. Reorganizing Data Tables and Paragraphs.mp4

04:27

5. Handling Multiple Data Visualizations in a Single Document.mp4

01:42

6. Pre-Defined Layouts with the Help of Container Tables.mp4

05:41

7. Building the PLATYPUS Story.mp4

05:03

6. Automating the Report Building Process

1.1 03-automation.zip

1.2 americanHFP.csv

1.3 generalMills.csv

1.4 kelloggs.csv

1.5 nabisco.csv

1.6 post.csv

1.7 quakerOats.csv

1.8 ralstonPurina.csv

1. Why You Should Consider Automating the Process.mp4

02:11

2. Building the Automation.mp4

05:39

3. Farewell.mp4

00:32

Description

Use Python, ReportLab and data visualization packages like Seaborn and Matplotlib to generate automated reports

What You'll Learn?

Understand how Python can help you in data reporting
Learn how to speed up the data reporting process
Write Python code to automate PDF report generation
Understand the ReportLab (Python library) document building system
Document data analysis progress and data visualizations in a PDF report
Plan out document templates, layouts and styles

Who is this for?

Data Analysts

Everybody looking to use Python to automate the reporting process

Analysts interested in new ways to improve and speed up their reporting skills

Students and graduates with a data focused background

What You Need to Know?

General understanding of data visualization

Basic Python skills (dictionaries. lists, loops)

Know how to install Python packages

Interest in analytics

More details

Description
Creating reports is a standard task in the modern working environment. Pretty much every office worker has to do it from time to time, some of us even daily.
Therefore it makes perfect sense to be an expert at it. This can save you a lot of time, make your manager happy and you can be of great help to your colleagues.
Therefore I will demonstrate in this course how you can use Python and the main package ReportLab to easily create reports and to even automate the process for fast reporting of multiple similar data files.
Our target output file type will be the pdf which anybody of us knows and uses regularly.
The portable document format, or PDF, is the standard for document sharing since decades. Its cross platform compatibility, the ease of printing and the variety of written and visual content it can handle, make the pdf one of the most important document formats.
Reading a PDF is easy as it gets, however, generating a PDF document can get complicated.Â Text editing software and many interactive apps are able to generate PDFs â€“ data analysis software usually makes great use of this feature too. On the user's side, PDF generation is just a matter of some mouse clicks. However, in the background the PDF document is written in the PostScript language.
If you are working on your own applications, or if you create a data analysis with a programming language such as Python, then figuring out PDF generation is not as straight forward. You would need an interpreter which translates your code to PostScript and then a PDF document is generated. Sometimes, this process relies on additional software.
If you use python the ReportLab package could be the right tool for you. ReportLab lets you directly create documents in PDF format without any intervening steps. This means that your applications can generate reports very fast, sometimes much faster than stand alone report writing software. A great advantage, especially when you want to automate the process. Besides text, ReportLab also handles charts, graphs, data tables, model outputs â€“ basically anything you can produce with python.
In order to follow along with this course the only skill you need is some beginner level python. So if you know how to install and import packages, handle lists, and how to write simple loops and functions, then you will have no problem keeping up with the course.
Do not worry if your understanding of python is still not at its fullest - I will make an effort in guiding you through the lectures step by step from setting up your working environment, performing a simple data analysis and writing the code for the actual PDF report generation and automation.
Alright I hope you will take this chance to bring your reporting skills to the next level!
Who this course is for:
Data Analysts
Everybody looking to use Python to automate the reporting process
Analysts interested in new ways to improve and speed up their reporting skills
Students and graduates with a data focused background

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R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out – our 100,000+ students love it. We focus on Data Science tutorials. Offering several R courses for every skill level, we are among Udemy's top R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available. All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons. The courses are taught by our main instructor Martin – trained biostatistician and enthusiastic data scientist / R user. Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm. We are here to help you boost your career with analytics training – Just learn and enjoy.

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