Exploring Twitter API and Data Using Tweepy, Pandas and Matplotlib. — Part 2

I started the first part of this article here. This is a continuation where I explain how I displayed both my dataframes and the plots in a web page using Flask — a web application framework for Python.

First, I had to install flask. I make sure my virtual environment within my folder is still activated. Then I installed Flask — pip install flask. In a new file I called show_analysis.py, I will add the following code to import the necessary libraries and create the application object.

Showing Dataframes:

Next I used decorators to link my index function to the base url.

What this code does is that on page load, on the index.html page, the dataframes returned as a result of calling the analyze() function will be converted to html table form. To display it, I created a templates folder within my project folder and created an index.html file with the emmet html broiler code. Within my html body, I added the following code:

When I run my show_analysis.py script, and visit this is what my web page looks like:

Web page showing dataframes as tables

Showing Charts

To show the plots from my analyze() function, I will use decorators to link the function that will create each image to their respective image urls. For example, to draw a bar chart of the number of twitter fans by housemates, I called my url /fans_by_hm_bar_chart/ then create a function called fans_by_hm_bar_chart().

In this function, I get the figures from the plot_graphs() function I imported at the top then pick the first figure because figures is a list and items are added accordingly. I then proceed to draw the image and then send the image to the web page when the function is called.

In my index.html, I add the following:

I do similarly to draw the fans by location bar chart and call app.run() in if __name__ == “__main__”:.

I also have to update the index.html with the url for the image. When this url is fetched, the function associated with it is run and the image is displayed.

When you run the script again, the rest of the page looks like this:

Web page with Bar Charts

Well this is how much I have done so far with this project. It tool me quite sometime to figure out how to show the images sequentially on the web page but after hours of google searches and scanning through tons of documentation and stack overflow pages I was able to do it. Nonetheless, I had so much fun doing this and I still look forward to doing more with this. Possibly getting the ratio of fans of each housemates that are verified twitter handles, the tweets with the highest retweet count etc.

The codes for this project can be found here: Tweet Streamer Analyzer.

If you enjoyed this article, don’t forget to share with your friends. Till next time!


  1. Passing dataframe to a web page.
  2. Passing Plots to a web page.
  3. Flask
  4. Flask Documentation
  5. Bytes IO



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