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Creating Powerpoint Presentations with Python

Posted by Chris Moffitt in articles   

Introduction

Love it or loathe it, PowerPoint is widely used in most business settings. This article will not debate the merits of PowerPoint but will show you how to use python to remove some of the drudgery of PowerPoint by automating the creation of PowerPoint slides using python.

Fortunately for us, there is an excellent python library for creating and updating PowerPoint files: python-pptx . The API is very well documented so it is pretty easy to use. The only tricky part is understanding the PowerPoint document structure including the various master layouts and elements. Once you understand the basics, it is relatively simple to automate the creation of your own PowerPoint slides. This article will walk through an example of reading in and analyzing some Excel data with pandas, creating tables and building a graph that can be embedded in a PowerPoint file.

PowerPoint File Basics

Python-pptx can create blank PowerPoint files but most people are going to prefer working with a predefined template that you can customize with your own content. Python-pptx’s API supports this process quite simply as long as you know a few things about your template.

Before diving into some code samples, there are two key components you need to understand: Slide Layouts and Placeholders . In the images below you can see an example of two different layouts as well as the template’s placeholders where you can populate your content.

In the image below, you can see that we are using Layout 0 and there is one placeholder on the slide at index 1.

In this image, we use Layout 1 for a completely different look.

In order to make your life easier with your own templates, I created a simple standalone script that takes a template and marks it up with the various elements.

I won’t explain all the code line by line but you can see analyze_ppt.py on github. Here is the function that does the bulk of the work:

The basic flow of this function is to loop through and create an example of every layout included in the source PowerPoint file. Then on each slide, it will populate the title (if it exists). Finally, it will iterate through all of the placeholders included in the template and show the index of the placeholder as well as the type.

If you want to try it yourself:

Refer to the input and output files to see what you get.

Creating your own PowerPoint

For the dataset and analysis, I will be replicating the analysis in Generating Excel Reports from a Pandas Pivot Table . The article explains the pandas data manipulation in more detail so it will be helpful to make sure you are comfortable with it before going too much deeper into the code.

Let’s get things started with the inputs and basic shell of the program:

After we create our command line args, we read the source Excel file into a pandas DataFrame. Next, we use that DataFrame as an input to create the Pivot_table summary of the data:

Consult the Generating Excel Reports from a Pandas Pivot Table if this does not make sense to you.

The next piece of the analysis is creating a simple bar chart of sales performance by account:

Here is a scaled down version of the image:

We have a chart and a pivot table completed. Now we are going to embed that information into a new PowerPoint file based on a given PowerPoint template file.

Before I go any farther, there are a couple of things to note. You need to know what layout you would like to use as well as where you want to populate your content. In looking at the output of analyze_ppt.py we know that the title slide is layout 0 and that it has a title attribute and a subtitle at placeholder 1.

Here is the start of the function that we use to create our output PowerPoint:

This code creates a new presentation based on our input file, adds a single slide and populates the title and subtitle on the slide. It looks like this:

Pretty cool huh?

The next step is to embed our picture into a slide.

From our previous analysis, we know that the graph slide we want to use is layout index 8, so we create a new slide, add a title then add a picture into placeholder 1. The final step adds a subtitle at placeholder 2.

Here is our masterpiece:

For the final portion of the presentation, we will create a table for each manager with their sales performance.

Here is an image of what we’re going to achieve:

Creating tables in PowerPoint is a good news / bad news story. The good news is that there is an API to create one. The bad news is that you can’t easily convert a pandas DataFrame to a table using the built in API . However, we are very fortunate that someone has already done all the hard work for us and created PandasToPowerPoint .

This excellent piece of code takes a DataFrame and converts it to a PowerPoint compatible table. I have taken the liberty of including a portion of it in my script. The original has more functionality that I am not using so I encourage you to check out the repo and use it in your own code.

The code takes each manager out of the pivot table and builds a simple DataFrame that contains the summary data. Then uses the df_to_table to convert the DataFrame into a PowerPoint compatible table.

If you want to run this on your own, the full code would look something like this:

All of the relevant files are available in the github repository .

One of the things I really enjoy about using python to solve real world business problems is that I am frequently pleasantly surprised at the rich ecosystem of very well thought out python tools already available to help with my problems. In this specific case, PowerPoint is rarely a joy to use but it is a necessity in many environments.

After reading this article, you should know that there is some hope for you next time you are asked to create a bunch of reports in PowerPoint. Keep this article in mind and see if you can find a way to automate away some of the tedium!

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5 Best Ways to Create PowerPoint Files Using Python

💡 Problem Formulation: Automating the creation of PowerPoint presentations is a common task for those who need to generate reports or summaries regularly. For instance, a user may wish to create a presentation summarizing sales data from a CSV file or visualize a project’s progress in a structured format. The desired output is a fully formatted PowerPoint file (.pptx) with various elements like titles, texts, images, and charts, as specified by the input data or customization requirements.

Method 1: Using python-pptx

The python-pptx library provides a comprehensive set of features for creating PowerPoint files (.pptx) in Python. It allows for adding slides, text, images, charts, and more, with a high level of customization. Manipulate slides at a granular level by accessing placeholders, creating bulleted lists, and setting properties like font size or color programmatically.

Here’s an example:

The code snippet above creates a PowerPoint file named python-pptx-presentation.pptx with one slide that includes a title and a subtitle.

In this overview, we create a presentation object, add a new slide with a predefined layout, set text for the title and subtitle placeholders, and then save the presentation. This method gives users the ability to create detailed, professional presentations through code.

Method 2: Using Pandas with python-pptx

This method combines the data manipulation power of Pandas with the presentation capabilities of python-pptx to create PowerPoint files from DataFrame contents. It’s particularly useful for automating the inclusion of tabular data or creating charts based on the DataFrame’s data.

The output is a PowerPoint file named pandas-python-pptx.pptx containing a bar chart representing the quantity of fruits.

This snippet demonstrates using a Pandas DataFrame to generate chart data, which is then used to create a chart in a PowerPoint slide. It showcases the synergy between Pandas for data handling and python-pptx for presentation creation.

Method 3: Using ReportLab with python-pptx

Those seeking to include complex graphics or generate custom visuals can harness the graphic-drawing capabilities of ReportLab with python-pptx. This method leverages ReportLab to create an image, which can then be inserted into a PowerPoint slide.

The output would be a PowerPoint file named reportlab-pptx.pptx containing a slide with a custom bar chart image.

The code above creates a bar chart using ReportLab, saves the chart as an image, and then inserts the image into a PowerPoint slide. This approach is ideal if you need to include bespoke graphics that are not directly supported by python-pptx itself.

Method 4: Using Matplotlib with python-pptx

For those familiar with Matplotlib, this method involves creating a visual plot or chart with Matplotlib, saving it as an image, and then embedding the image into a PowerPoint slide using python-pptx.

The outcome is a PowerPoint file matplotlib-pptx.pptx , with a plot on a slide created by Matplotlib.

In this case, we graph a quadratic function using Matplotlib, save it as an image, and then add that image to a slide in our PowerPoint presentation. This method offers a blend of Matplotlib’s sophisticated plotting tools with the simplicity of python-pptx.

Bonus One-Liner Method 5: Using Officegen

The Officegen package allows for rapid PowerPoint creation with simpler syntax, although with less flexibility compared to python-pptx. It provides functions to add slides, titles, and bullet points.

The outcome is a PowerPoint file officegen-presentation.pptx with a single slide containing a large title.

This snippet uses Officegen to initiate a new presentation, adds a text title to a slide, and saves the presentation. While not as detailed as python-pptx, Officegen is quick for simple presentations.

Summary/Discussion

• Method 1: python-pptx. Full-featured control over presentations. Can be verbose for simple tasks.
• Method 2: Pandas with python-pptx. Ideal for data-driven presentations. Setup can be complex if unfamiliar with data libraries.
• Method 3: ReportLab with python-pptx. Powerful combo for custom graphics. Requires separate handling of graphics and presentation stages.
• Method 4: Matplotlib with python-pptx. Best for users comfortable with Matplotlib. Less direct than using python-pptx alone.
• Bonus Method 5: Officegen. Quick and easy for simple presentations. Limited customization options.

Emily Rosemary Collins is a tech enthusiast with a strong background in computer science, always staying up-to-date with the latest trends and innovations. Apart from her love for technology, Emily enjoys exploring the great outdoors, participating in local community events, and dedicating her free time to painting and photography. Her interests and passion for personal growth make her an engaging conversationalist and a reliable source of knowledge in the ever-evolving world of technology.

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Creating and updating PowerPoint Presentations in Python using python – pptx

python-pptx is library used to create/edit a PowerPoint (.pptx) files. This won’t work on MS office 2003 and previous versions.  We can add shapes, paragraphs, texts and slides and much more thing using this library.

Installation: Open the command prompt on your system and write given below command:

Let’s see some of its usage:

Example 1: Creating new PowerPoint file with title and subtitle slide.

Example 2: Adding Text-Box in PowerPoint.

Example 3: PowerPoint (.pptx) file to Text (.txt) file conversion.

Example 4: Inserting image into the PowerPoint file.

Example 5: Adding Charts to the PowerPoint file.

Example 6: Adding tables to the PowerPoint file.

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A python library for creating PowerPoint slides with Plotly charts

jonboone1/plotlyPowerpoint

Folders and files, repository files navigation, plotly & powerpoint.

A library used to create powerpoint slides including plotly charts. Use this to automate powerpoint creation including certiain charts/visualizations.

Getting Started

Below is a quick tutorial taking you through how to setup and use this library. I will use public data to showcase how it works.

Step 1 - Install Dependencies

I have yet to figure out how to install required packages with the install of this library. Therefore, please ensure you have installed the following packages. For plotly, please refer to the getting started page to learn how to install everything properly.

• plotly.express
• plotly.graph_objects
• plotly.subplots
• scipy.stats

Additionally, if you want to be able to visualize plotly charts, you may have to install additonal requirements. Refer to the plotly getting started page and scroll down for your proper IDE (Jupyter Notebook, Lab, etc.).

Step 2 - Install Package

Step 3 - prepare your powerpoint.

The main function of this library is meant to generate slides which include a plotly chart. In order to do this, you must prepare a powerpoint template with the proper layout. You can design any layout you desire, but make sure that each element you desire to fill with python is created as a placeholder. You can use a powerpoint template I've included in my source code to make things easy (assets/powerpoint_templates/template.pptx).

In order to do this, open up your desired powerpoint and go into the slide master. Insert a new slide or use a current one already created. I recommend to drag this to be first in the order, this will make your life easier later down the road. Now insert the proper elements and arragne them as you please. For the chart, insert an image placeholder and make the apsect ratio similar to a laptop screen. Most images created are in landscape view but not too wide.

Step 4 - Load Library and Prepare Data

If you want to follow along with my tutorial, feel free and copy/paste my code. However, ensure you have pydataset installed before you do.

Step 5 - Find Your Powerpoint Elements

In order for this library to know where to place each element, you must give it each element index. See the following code to learn how to do this:

You will need this information later on.

Step 6 - Set Template

Now that we have our powerpoint template, we need to tell the library where to find this file. Do this with the following:

Step 7 - Define Charts

Here is where the work is done. Creating slides with charts is done by defining an array of dictionary objects. Each object represents one slide. Everything must be represented as a string except your dataframe object. Additionally, this library automatically groups every dataframe down to the level needed for the specific chart. Therefore, you don't have to create a new dataframe for each chart. As long as your df has the right data in it, this function will do the rest.

As a start, I will define two basic charts:

I will go into more detail on each one of these variables in a later section.

Step 8 - Run Function

This will output a file called output.pptx . I suggest you do not make this your final file, as each time you run this function you will overwrite the powerpoint. Create a copy of this file and start to create your analysis/report there. From here, you can use output.pptx as a slide library, where you can include or delete any chart you create.

• Jupyter Notebook 52.7%
• Python 47.3%

plotlyPowerpoint 1.2.17

pip install plotlyPowerpoint Copy PIP instructions

Released: Nov 22, 2022

A library using Plotly and Powerpoint to easily generate slides with plotly charts in them

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License: MIT License

Author: Jon Boone

Requires: Python >=3.6

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• OSI Approved :: MIT License
• OS Independent
• Python :: 3

Project description

Plotly & powerpoint.

A library used to create powerpoint slides including plotly charts. Use this to automate powerpoint creation including certiain charts/visualizations.

Getting Started

Below is a quick tutorial taking you through how to setup and use this library. I will use public data to showcase how it works.

Step 1 - Install Dependencies

I have yet to figure out how to install required packages with the install of this library. Therefore, please ensure you have installed the following packages. For plotly, please refer to the getting started page to learn how to install everything properly.

• plotly.express
• plotly.graph_objects
• plotly.subplots
• scipy.stats

Additionally, if you want to be able to visualize plotly charts, you may have to install additonal requirements. Refer to the plotly getting started page and scroll down for your proper IDE (Jupyter Notebook, Lab, etc.).

Step 2 - Install Package

Step 3 - prepare your powerpoint.

The main function of this library is meant to generate slides which include a plotly chart. In order to do this, you must prepare a powerpoint template with the proper layout. You can design any layout you desire, but make sure that each element you desire to fill with python is created as a placeholder. You can use a powerpoint template I've included in my source code to make things easy (assets/powerpoint_templates/template.pptx).

In order to do this, open up your desired powerpoint and go into the slide master. Insert a new slide or use a current one already created. I recommend to drag this to be first in the order, this will make your life easier later down the road. Now insert the proper elements and arragne them as you please. For the chart, insert an image placeholder and make the apsect ratio similar to a laptop screen. Most images created are in landscape view but not too wide.

Step 4 - Load Library and Prepare Data

If you want to follow along with my tutorial, feel free and copy/paste my code. However, ensure you have pydataset installed before you do.

Step 5 - Find Your Powerpoint Elements

In order for this library to know where to place each element, you must give it each element index. See the following code to learn how to do this:

You will need this information later on.

Step 6 - Set Template

Now that we have our powerpoint template, we need to tell the library where to find this file. Do this with the following:

Step 7 - Define Charts

Here is where the work is done. Creating slides with charts is done by defining an array of dictionary objects. Each object represents one slide. Everything must be represented as a string except your dataframe object. Additionally, this library automatically groups every dataframe down to the level needed for the specific chart. Therefore, you don't have to create a new dataframe for each chart. As long as your df has the right data in it, this function will do the rest.

As a start, I will define two basic charts:

I will go into more detail on each one of these variables in a later section.

Step 8 - Run Function

This will output a file called output.pptx . I suggest you do not make this your final file, as each time you run this function you will overwrite the powerpoint. Create a copy of this file and start to create your analysis/report there. From here, you can use output.pptx as a slide library, where you can include or delete any chart you create.

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How to create powerpoint files using Python

Introduction.

We’ve all had to make PowerPoint presentations at some point in our lives. Most often we’ve used Microsoft’s PowerPoint or Google Slides.

But what if you don’t have membership or access to the internet? Or what if you just wanted to do it the “programmers” way?

Well, worry not for Python’s got your back!

In this article you’ll learn how to create a PowerPoint file and add some content to it with the help of Python. So let’s get started!

Getting Started

Throughout this walkthrough, we’ll be using the python-pptx package. This package supports different python versions ranging from 2.6 to 3.6.

So, make sure you have the right version of Python installed on your computer first.

Next, open your terminal and type −

Once the module is successfully installed, you are all set to start coding!

Importing the Modules

Before we get into the main aspects of it, we must first import the right modules to utilise the various features of the package.

So, let’s import the presentation class that contains all the required methods to create a PowerPoint.

Now, we are all set to create a presentation.

Creating a Presentation

Let us now create an object of the Presentation class to access its various methods.

Next, we need to select a layout for the presentation.

As you can see, there are nine different layouts. In the pptx module, each layout is numbered from 0 to 8. So, “Title Slide” is 0 and the “Picture with Caption” is 8.

So, let us first add a title slide.

Now, we have created a layout and added a slide to our presentation.

Let us now add some content to the first slide.

In the above lines, we first add a title to the “first slide” and a subtitle using the placeholder.

Now, let us save the presentation. We can do this using the save command.

If you run the program, it will save the PowerPoint presentation in the directory where your program is saved.

You have successfully created your PowerPoint presentation.

Creating a second slide and adding some content

Firstly, you’ll need to import additional methods to add content.

Let us first create and add the second slide.

Adding title for the next slide,

Now, we must create a textbox and move its layout to suit our needs.

Let us position it and adjust its margins in inches.

The above line of code will place a textbox 3 Inches from left and 1.5 Inches from the top with a width of 3 Inches and height of 1 Inch.

Once we have the layout and position fixed, time to create a textframe to add content to.

Now to add a paragraph of content,

Finally, save the presentation again using the save method.

That’s it! You can now create your own presentation with the help of Python.

And there are a lot more features within the pptx package that allows you to completely customise your presentation from A-Z just the way you do it in GUI.

You can add images, build charts, display statistics and a lot more.

You can go through python-pptx official documentation for more syntaxes and features.

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