Wit Plotly we can already create interactive plots and find the data points we are interested in. Would it not be great if we could add some more interactivity and combine multiple plots to a dashboard? Luckily for us, we can do exactly that with Dash.
So far, we saved our plots with the camera icon of the plot preview. If we want to automate the creation of our plots, this manual step will not be sufficient, and we need to have an alternative that we can call from our code. Unfortunately, there is a catch that you need to be aware of.
There is still more to customise with Plotly than the colours or the templates. In this post we go through the few parts that Plotly does automatically but not always to our satisfaction.
While colours are one of the most notable things we can change in Plotly, there are many more knobs we can turn to influence the visual aspects of our plots. In this post we explore how templates for Plotly work and what we need to create our own.
As we have seen in the last post, Plotly does not always use colours with a high enough contrast. In this post we explore the different options we have to choose better colours.
Last week we figured out how we can create our well-known plots with Plotly. In this post we explore the diagrams that are specific to Plotly and may help us to find another approach to visualise our data.
After our first steps with the interactive plots of Plotly, we will now explore the different diagrams we can use to visualize our data.
We came a long way with data visualisation over the last few months. But so far, all plots we created were static. Now it is time to change this and look at interactive plotting libraries.
Creating graphs with numerical and categorical data is something we got comfortable with over the last months. But how can we visualize a text to spot the common words and get a hint of the topic? Let us figure out how we can tackle such a challenge.
Last week we formulated our thesis and went on to capture the data to (dis-) prove our assumption. Today we clean the data file, turn it into a graph and check the merit of our thesis.