Python And Reportlab For Efficient Reporting And Automation

Python And Reportlab For Efficient Reporting And Automation
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 901.40 MB[/center]
| Duration: 2h 15m
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

Requirements

General understanding of data visualization

Basic Python skills (dictionaries. lists, loops)

Know how to install Python packages

Interest in analytics

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. Text editing software and many interactive apps are able to generate PDFs – 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 – 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!

Overview

Section 1: Workspace Setup

Lecture 1 Introduction

Lecture 2 Information on Resources

Lecture 3 Virtual Environment Setup

Lecture 4 Installing Python Libraries

Section 2: ReportLab Groundwork

Lecture 5 Introduction

Lecture 6 The Canvas Object of PDFgen

Lecture 7 ReportLab Anatomy - The Hierarchy of Document Building Blocks

Lecture 8 Building Documents with PLATYPUS - Create Your Own Page and Document Templates

Lecture 9 Include Data Visualizations in Your Reports with Figure to Image Conversion

Lecture 10 Add Tables to Your Report Easily with DataFrame to Table Conversion

Lecture 11 Styling Your Paragraphs and Tables with Dedicated Style Objects

Lecture 12 Overview

Section 3: Document Data Analysis Progress with ReportLab

Lecture 13 Introduction

Lecture 14 The Cereal Dataset

Lecture 15 Dataset Import

Lecture 16 Data Type Management with NumPy and alternatives with PyArrow

Lecture 17 Identifying and Handling Invalid Observations

Lecture 18 Equalizing Nutritional Values on the Basis of Weight

Lecture 19 Extending the Analysis with Nutritional Test

Lecture 20 Declaring Variable Units

Lecture 21 Auxiliary Tables

Lecture 22 Improving the Print in the PDF Document

Lecture 23 Overview

Section 4: Including Data Visualizations in Your Reports

Lecture 24 Introduction

Lecture 25 The Matplotlib Figure Object

Lecture 26 Regular Pyplot Charts and the Pandas Plotting System

Lecture 27 Exporting Results of Custom Data Visualization Functions

Lecture 28 Including a Subplot Grid in a Report

Lecture 29 Various Types of Plots Created with Seaborn - Plot Matrix and Facet Grid Plot

Lecture 30 Overview

Section 5: Updating and Extending the Report

Lecture 31 Introduction

Lecture 32 Introducing Additional Page Templates

Lecture 33 Updating Flowable Style Objects

Lecture 34 Reorganizing Data Tables and Paragraphs

Lecture 35 Handling Multiple Data Visualizations in a Single Document

Lecture 36 Pre-Defined Layouts with the Help of Container Tables

Lecture 37 Building the PLATYPUS Story

Section 6: Automating the Report Building Process

Lecture 38 Why You Should Consider Automating the Process

Lecture 39 Building the Automation

Lecture 40 Farewell

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