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 how to plot time series data. 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: brilliant.org/cms
I've already started working on those, but it takes a long time to complete a series. I'm currently going through a move, so it will be some time unless I get moved into my new place and get my office set up. It will likely be a month until I've made good progress on the numpy and pandas series.
One day I am sure your videos will also be in the list of Top trending video dataset that you have pulled out. Amazing explanation for each and everything! Thank you so much!
Your videos helped me to learn more than I had learnt on my actual classes on Data Science. You are absolutely an awesome teached and have the capability to teach ans convey difficult knowledge in an easy and helpful manner. Thank you so much for making these videos. I am going to continue learning by watching the rest of your videos on this series.
I've been binge-watching your videos for a while now, they are very rich and concise. It gives a beginner the right foundational introduction into data visualization. I'm glad I found your videos, I can't wait to see you work with more more sophisticated plots
Great video, Corey! I'm currently doing an Astronomy-related project which involves using a scatter plot, and this was a very helpful intro for that. Thanks.
you could also look into the bokeh package. I think that would also make a great series, since it runs faster than matplotlib, but with a similar syntax
@@coreyms Thats great! Bokeh also has an easy interface for interactive plots, hovertools and capabilities to save html files, which are nice to present data as dashboard applications. Can't wait to see your series. :)
These data show how self-reinforcing TH-cam likely is. I am sure that both views and likes are factored into the algorithm. So once you start to get likes and views the algorithm will highlight you meaning you get more likes and views leading to a self-fulfilling prophecy. It is not that the video is higher quality or even more popular, but that TH-cam makes the content so through reinforcement.
The series is great! - but one question: is it possible to color code the density of points in a certain area, e.g. more dense points/ same points appear darker than less dense points?
while using plt.colorbar(), it return runtime error : No mappable was found to use for colorbar creation. First define a mappable such as an image (with imshow) or a contour set (with contourf).
Thanks Corey, great videos! Looking forward to rest of the series! I'm trying to do something like Hans Rosling's video with plotting some data points over a 10 or 20 year period to perform analysis and to better visualize my data. I see a library called plotly_express but for now I'm just going to use a more organic approach with matplotlib. Question I have is are you planning on showing how to integrate control of the event attributes to make the data more interactive? I'm thinking of taking a scatter plot and then popping up attribute information when the cursor is over a data point (assume we use axes_enter/leave_event or figure_enter/leave_event)?? Pardon me if you already covered this as I just started watching yesterday and am kind catching up still. Other graph type I'm interested in is the bar_polar to display several key metrics for a company or project, to better visualize overall performance at a glance. I really think data analytics and data visualization is hot right now, and appreciate your timing with this video series. It would be great to see this series as a foundational component and then another intermediate or more advanced series to address a variety of use cases and how we could leverage these skills we are learning here, and tweak them slightly to create even greater visualizations or interactive data analysis tools.
Hey there. I'll be covering more interactive tools in the future, but not in this series. A popular library for that is Bokeh. I'll likely do a Bokeh series after the Pandas and Numpy series.
Thanks for this Corey, really useful series. Does anyone know how you can force the z axis (like/dislike ratio plotted by colour map) limits to be between 0 and 1?
you can do one thing , assume the highest ratio to be = 1 and lower ratio to be = zero and then use the map() function to map all the csv ratio values column cheers !
Using pandas , divide the ratio column by 100 and replace it to orginal dataframe. Then Change vmin =0 , vmax = 1 in plt.scatter(df.view_counts, df.likes, c = data.ratio , vmin ,vmax). Otherwise directly divide by 100 like shown below. Plt.scatter(df.view_counts, df.likes, df.ratio/100 , ...........) Cheers!♥️☄
I have a project coming, so can anybody tell me where should I get data from? to manipulate, analyze and visualize like he got data of top trending youtube videos so where did he get from??
First of all, very nice video. I just have a question. I want to plot contours on a scatterplot, let's say that include 70%,90%, and 95% of all the points. Is there a way to do that. I couldn't find anything. I will appreciate any help. Thanks
question, you import both matplotlib and pandas, but pandas already contains the matplotlib “inside”, how to use all methods matpotlib without it import using just pandas?) e.g. style thanks
Please sir help me I am scrapping a web and there is JavaScript on it for infinite scrolling page and I need to scrape data using requests_html but render is not working Can you provide more tutorials on it
Anyone that got this warning "MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first." Use plt.rcParams['axes.grid'] = False
![[ ออกกอง ] วัยหนุ่ม 2544 โลกหลังลูกกรง..ทัวร์กองถ่ายหนังใน "คุกของจริง" | JUSTดูIT.](http://i.ytimg.com/vi/vB--aOkZCpw/mqdefault.jpg)
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 how to plot time series data.
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:
brilliant.org/cms
It would be interesting to have a video about boxplots and outliers.
Just what I've been waiting for!!!!! Time series plots!!!!
So sir you will not tell when you will start with numpy and pandas?
I've already started working on those, but it takes a long time to complete a series. I'm currently going through a move, so it will be some time unless I get moved into my new place and get my office set up. It will likely be a month until I've made good progress on the numpy and pandas series.
@@coreyms i have search for numpy in a chaneel but there no vedios, when i expect numpy tutorials
One of the best Python instructor in the TH-cam.. !!
the best
You are such a great teacher. I can not thank you enough. From Ethiopia 🇪🇹
Dude I cannot believe you offer this for free. I swear I will donate as soon as I am capable of it, this helps so much.
Thanks Corey, this was a great help for my thesis!
One day I am sure your videos will also be in the list of Top trending video dataset that you have pulled out. Amazing explanation for each and everything! Thank you so much!
Lovelyyyyyy. Too good once more. You’re doing a very noble job sir. God Bless! Love from India....
Great content Mr.corey. can you make series of tutorials on pandas n numpy modules. That will helpful for alot of people. Love n respect from INDIA..
Your videos helped me to learn more than I had learnt on my actual classes on Data Science. You are absolutely an awesome teached and have the capability to teach ans convey difficult knowledge in an easy and helpful manner. Thank you so much for making these videos. I am going to continue learning by watching the rest of your videos on this series.
One more useful video. For me, as for beginning data scientist, it's VERY useful! Thank you so much 👍
Soo true!☄
Thank you Corey. You're such a great teacher. Greetings from Ecuador
Hands down the best Python tutorial series on the internet
I've been binge-watching your videos for a while now, they are very rich and concise. It gives a beginner the right foundational introduction into data visualization. I'm glad I found your videos, I can't wait to see you work with more more sophisticated plots
Great video, Corey! I'm currently doing an Astronomy-related project which involves using a scatter plot, and this was a very helpful intro for that. Thanks.
Thank you so much sir. As a newbie, I find these videos so easy to understand. Thank you again. Hope you continue to make videos like this.
INSTANT SUB!!!!
Tysm, my man. Exactly what I needed. Concise but thorough :)
Proper data analytics, great tutorial!
Excellent content, simple explanations, really easy to follow. Great work
Thanks, Corey. I have learned a lot from your video.
I'm here after finishing Corey's pandas tutorial. Thank you for these amazing series!
Watching these videos has been immensely helpful. Thank you very much for sharing your knowledge!
Thanks Corey, you do a great job with your videos, nothing identifiably spectacular, nonetheless effective and enjoyable.
Thank you so much! Exactly what I needed.
Excellent series!
Good stuff Corey appreciate the information!!!
Thank you Schafer from Taiwan
Great series, one more humble request - can you do a series on 3D plots.
15:00 didn't expect old town road to show up here, totally makes sense
Very clear. Well-done!
Thank you Corey for this video! It was very well planned in the sense that it transitioned well from basic to more intermediate stuff (like cmap!)
Gold Mine 👌
great work!
You are a saviour man!
please make seaborn tutorial too
Thank you very much for the video!
I love that outlier:)
Thank you. it was very useful for me.
Thank you for this video.
Thank you so much for the video !!!
you could also look into the bokeh package. I think that would also make a great series, since it runs faster than matplotlib, but with a similar syntax
Yes, I'll be covering Bokeh in a future series
@@coreyms Thats great! Bokeh also has an easy interface for interactive plots, hovertools and capabilities to save html files, which are nice to present data as dashboard applications. Can't wait to see your series. :)
@@coreyms Please consider Plotly and/or Dash as well!
Great video thanks a lot!!!
Thank you so much for everything
Thanks to you dude. Ive managed to keep my hair on my head
Nicely done. How about covering the plot_date() and including color gradients?
I know this has been posted a lot, but a pandas series (as well as some of the other popular data science libraries) would be awesome
Also - super excited for that TH-cam API video :)
All the pointless to watch scatterplot videos for my KNN assignment question. Thank God for this video
Thanks man!!
Old Town Road💖💖💖😂
thank you :)
Thanks for the vid :D. YT algo please love this guy
Hello Corey, Thank you very much for this great series. Can you please tell me how slicing works in scatter plot?
Please make a video on curve fitting and regression lines
Awesome series! Can we use Log scale for the colorbar as well?
Is there a way to invert cmap='summer' so that the ratio changes from red to green?
@mcmormus Yes, there is. You only need to add “_r” in the end of your chosen colormap.
example: Using “jet” colormap
cmap = “jet”
cmap = “jet_r”
Thanks for the series. I really enjoyed all the videos. A question I have is what libraries would you use to allow user interactions.
A popular library for interactive plots is Bokeh. I'll be doing a series on that in the near future as well.
Thank you
Thanks corey!! how to verify the plotted points are exactly plotted.
These data show how self-reinforcing TH-cam likely is. I am sure that both views and likes are factored into the algorithm. So once you start to get likes and views the algorithm will highlight you meaning you get more likes and views leading to a self-fulfilling prophecy. It is not that the video is higher quality or even more popular, but that TH-cam makes the content so through reinforcement.
It help me a lot
Interesting outlier
How would you plot the x y scatter as well as say a polynomial line that is the best fit line for the data points?
Great...
Maybe it is updated but when I use the start code, it says "'tuple' object is not callable".
The series is great! - but one question: is it possible to color code the density of points in a certain area, e.g. more dense points/ same points appear darker than less dense points?
gracias
Great Video! Can you tell me how I can display images instead of points in the plot?
using imshow() method for data with images instead of show() method
while using plt.colorbar(), it return runtime error : No mappable was found to use for colorbar creation. First define a mappable such as an image (with imshow) or a contour set (with contourf).
Have you tried copy pasting, final code given by Corey on github?
Thanks Corey, great videos! Looking forward to rest of the series! I'm trying to do something like Hans Rosling's video with plotting some data points over a 10 or 20 year period to perform analysis and to better visualize my data. I see a library called plotly_express but for now I'm just going to use a more organic approach with matplotlib.
Question I have is are you planning on showing how to integrate control of the event attributes to make the data more interactive? I'm thinking of taking a scatter plot and then popping up attribute information when the cursor is over a data point (assume we use axes_enter/leave_event or figure_enter/leave_event)?? Pardon me if you already covered this as I just started watching yesterday and am kind catching up still.
Other graph type I'm interested in is the bar_polar to display several key metrics for a company or project, to better visualize overall performance at a glance.
I really think data analytics and data visualization is hot right now, and appreciate your timing with this video series. It would be great to see this series as a foundational component and then another intermediate or more advanced series to address a variety of use cases and how we could leverage these skills we are learning here, and tweak them slightly to create even greater visualizations or interactive data analysis tools.
Hey there. I'll be covering more interactive tools in the future, but not in this series. A popular library for that is Bokeh. I'll likely do a Bokeh series after the Pandas and Numpy series.
Query here !!
been doing as you instructed but while plotting on Y-axis it's showing 1,2,3,4 rather then orignal value.
How to resolve it
Hi Corey, how to set label to each point on scatter plot?
Green is Corey’s favourite color.
Thanks for this Corey, really useful series.
Does anyone know how you can force the z axis (like/dislike ratio plotted by colour map) limits to be between 0 and 1?
you can do one thing , assume the highest ratio to be = 1 and lower ratio to be = zero and then use the map() function to map all the csv ratio values column
cheers !
Using pandas , divide the ratio column by 100 and replace it to orginal dataframe.
Then Change vmin =0 , vmax = 1 in plt.scatter(df.view_counts, df.likes, c = data.ratio , vmin ,vmax).
Otherwise directly divide by 100 like shown below.
Plt.scatter(df.view_counts, df.likes, df.ratio/100 , ...........)
Cheers!♥️☄
Data which you have used is not in the description
hi what if x has 2 attributes and y is the label how can i plot this please
How its possible set legend to my data at scatter plot? ie male and female are groups inside this graph visualization
How can I plot two datasets within the same scatterplot? I don’t know how to define the y & x axis…
I have a project coming, so can anybody tell me where should I get data from? to manipulate, analyze and visualize like he got data of top trending youtube videos so where did he get from??
First of all, very nice video. I just have a question. I want to plot contours on a scatterplot, let's say that include 70%,90%, and 95% of all the points. Is there a way to do that. I couldn't find anything. I will appreciate any help.
Thanks
the outlier rode till it couldn't no more
How u get all this data corey? By the way your video are very nice!!!
Stackoverflow
question, you import both matplotlib and pandas, but pandas already contains the matplotlib “inside”, how to use all methods matpotlib without it import using just pandas?) e.g. style
thanks
one doubt on this video
the data is about youtube trend's likes,viewcount and ratio
then how did you get dislike ratio???
Please sir help me I am scrapping a web and there is JavaScript on it for infinite scrolling page and I need to scrape data using requests_html but render is not working Can you provide more tutorials on it
How would I do a scatter plot in real time?
Video on boxplots?
getting a value error on the data @corey schafer could you help me out here.
cbar = plt.colorbar(orientation='horizontal') in case you want it to be horizontal
careful: correlation only models a linear relationship. The correlation may be zero even if the variables are stochastically dependent!!!
Would have been good to have seen one colour per series of data.
again same day (16 jun) but 1 year later :))
date: 16. 6 . 2020
3 months and 2 days from the same day as last year.
missed opportunity to make the like/dislike ratio colormap to be green to red
"I'm gonna take my horse to the old town road"
At this point in time, I'm trying to figure out how to plot a regression line on my scatter plot, anyone?
Nice video though, thanks.
00:02
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
No longer works!? Python is such a volatile mess...
this look like R shiny content
Honestly I am really disappointed you didn't talk about regression line!
watching this in 2020-05-31 aint that cool?..
Anyone that got this warning
"MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first."
Use
plt.rcParams['axes.grid'] = False