Introduction to Plotly.

In this new tutorial we are learning the basic of another python interactive visualisation library: plotly. We will learn how to create the four main visualisation plot:

Pie chart
Lineplot
Barplot
Heatmap

Data was extracted from the website Paris forum fintech. This is one of the main event in the Fintech industry. You can find the like of Revolut or Klarna but also some big players such as BNP.

My initial plan was to extract the nameS of all the companies attending this event and then I decided to share with you some of the visualisation graph from the project. Let's get started 📖!

The companies

How many countries represented ?

We can visualize the percentage of companies by country of origin that was present to the event using a pie chart.

Now let's put some numbers on these countries share. Let's visualise the distribution of companies per countris using a barplot.

The speakers

It's good to know how many companies was invited to the event. Here we are getting some insights on who are the speakers. Let's extract the speakers' name from the following url.

What is the ratio of man versus women ?
What are the speakers job title ?
Who are the most popular speakers ?

Speakers overview

The speaker audience was composed of

304 speakers
47 differents job title
35 different nationalitites represented
203 of them had a twitter profile
66 of them a linkedin profile

Speakers gender gap

We used a python library that asses the gender of a name. Unfortunately gender gap that exists in the Finance Industry also appears in this event.

Speakers job title

A panel of high quality, where most of the companies' CEO were invited.

Jobtitle and gender repartition

Speakers' twitter profiles

To make this tutorial even more relevant we extract the top 5 most popular speakers of the events. Popularity is based on the number of followers they have on twitter.😝

The speaker with the highest number of followers are Cédric O working for the French Goverment, and Yoni Assa Founder&Ceo of eTorro. In a first part we extract some user behavorial pattern based on their last 100 tweets. In a second part,since Cedric is french and mostly tweeting in french, we will be analyzing what Yoni is tweeting about.

Who tweet the most ?

With no surprise it's our french politician who tweet the most. Yoni's 100 tweets period starts on January 31 2021 while for our politician it starts on March 24 2021. In another word it tooks Cedric 17 days and Yoni 65 days to publish 100 tweets...🙂.

Tweet daily planning

Our dear politician seems to be inactive during the weekend and tweeting mostly during the week. We can actually see that the closest we are from the week-end the more active Cedric is on twitter 😆. Yoni boy seems to be mainly active on Sunday and Wednesday.

Bare in mind we are drawing conclusion only based on 17 days and 65 days of users' twitter activity. Be mindful even if the conclusion looks legit 😂.

Tweet hourly planning

Cedric tweets peak hour is at lunch time while for our CEO it's around midnight. This graph gives a bit of confidence on who is in charge of the account. One could argue that they have a PR team in charge of their twitter account, but these hour pattern seem to reflect a real person rather than a team.

Weeky planning

Let's combine days and hours.

Cedric peak tweet time is friday 2 p.m, Yoni favorite time to tweets are Wednesday and Sunday 11 p.m. Now we are going to visualise what Yoni's tweet looks like.