From the course: Practical Python for Time Series Analysis
Join today to access over 25,500 courses taught by industry experts.
Interactive Plotly heat matrix - Python Tutorial
From the course: Practical Python for Time Series Analysis
Interactive Plotly heat matrix
- [Instructor] To have an interactive visualization with Plotly of these indicators throughout the years, we can apply the same Resample function where we get these results and then import the Plotly library using the function imshow with the information inside the DataFrame. However, there are many things we can improve, because instead of working with the data directly from the resample, we can transpose it and have the information for each one of the rows differently. Now, in case we'd like to have a ranking, we can also apply the same function we had earlier. Let me save this back into r, and then from here we can apply the sum, but be careful because if we do it in this way, we are mixing the indicators for each one of the dates, so we must apply axis=1 to sum each one of the indicators separately. Now, we sort the values using ascending=False, although in this case, the sum doesn't make sense, better to use…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.