Matplotlib Tutorial (Part 9): Plotting Live Data in Real-Time

In this video, we will be learning how to plot live data in real-time using Matplotlib.

In this Python Programming video, we will be learning how to plot live data in real-time using Matplotlib. We will learn how to monitor a CSV file that is constantly being updated, and plot the values from that CSV file as they are coming in. This can be extremely useful for plotting data coming from APIs or sensors or any other source that will have frequent updates. Let's get started...

The code from this video (with added logging) can be found at:

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[coreyms]

I hope everyone finds this video helpful. The next video of the series will be posted tomorrow at the same time. The next video will cover subplots. Subplots are used to work with plots in a more object-oriented manner and also allow us to plot multiple different graphs at the same time.

I'd like to thank Brilliant for sponsoring this series. If you'd like to check them out then you can sign up with this link and get 20% off your premium subscription:

[jnce]

For those using Jupyter Notebook, adding this line at the top of the notebook will make the graph appear:
%matplotlib notebook

[BiancaAguglia]

This was another great tutorial, Corey. And yes, please do a video about plotting real time data from an API. 😊 Thank you for all your hard work.

[confidencechidiebere]

This is the toughest video in this series. I spent hours trying to figure it out but to no avail. I will pass and come back in the future. Perhaps by then, I would have gained more knowledge that will help me understand it. Excellent videos. Thank you!

[youngzproduction]

I learn a lot from your vids. Literally, a lot. I hope you keep updating your tutorial more. This clip helps me understand how the plot updating itself. Thanks million times.

[alexandreperron]

There is a special place in heaver for guys like you. Thank you so much. This is by far one of best things I saw on Youtube

[ZsoltPal]

Just simply love the idea in this video. Made it to a rolling (scrolling?) plot - if the data reaches 30+, it only plots the last 30, looks interesting. Thank you Corey, you are brilliant! Edit: changet it to 200 and added a try/except so that the plot can be started before the csv generation. I love this :) Thank you again Corey for this amazing video.

[tireldenamse]

I really love this series!
Thanks so much for your help!

[ahmedyasser]

Congrats on 300k, your videos are straight to the point and explained extremely well!

[Iknowpython]

One of the main reason why python is one of the best is because of its huge community contributing in creating libraries and matplotlib is definitely one of the finest library for data visualization

[renujain]

Whenever I got stuck then first channel I look for is Corey Schafer.... Your teaching style is something which no one seems to be matching.... So simple to understand any kind of difficult or complex topic.... Great Work :-)

[SolvingOptimizationProblems]

This is exactly what I'm looking for. It worked for me. Many thanks sir

[woodziss]

Great video.
Would be interesting to see how can one integrate this updating plot within a PyQT GUI.

[mrmuranga]

Corey, thanks...
anyone who chose to use jupyter notebooks, incase your plots are not showing especially the live plots....and getting a mesg such as "figure size 432x288 with axes 0", would recommend you save the file you want to run as py file and then run it directly from the terminal....ensure though that in your terminal you have installed matplotlib and pandas via pip....

[kevingroovy]

Dude you helped me out a lot!!! Thank you so much for taking the time to make this video. Subscribed to your channel

[clementstore]

Thank you very much. Your videos are better than most paid courses. That is a fair comment.

[luca-o-sharp]

Awesome speaker, simple explanations, huge- huge thanks!!!

[bokkenka]

Nice videos. A tip for this one that might be useful: You can slice the data follow only the last X number of entries rather than seeing all the data bunch up tighter and tighter. Let's say you only care about the last minute... Add a `[-60:]` on the end of the `x=...`, `y1=...`, and `y2=...` lines.

[freeelectron]

Great tutorial! Thanks Corey! Just subscribed :)

[rutviktak]

Thanx mman, you'r helping lot of people.learned a lot from your channel and would like to pay it forward in the future just by sharing what i learned😊