Matplotlib Tutorial (Part 2): Bar Charts and Analyzing Data from CSVs
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- čas přidán 23. 07. 2024
- In this video, we will be learning how to create bar charts in Matplotlib.
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In this Python Programming video, we will be learning how to create bar charts in Matplotlib. Bar charts are great for visualizing your data in a way where you can clearly see the total values for each category. We'll learn how to create basic bar charts, bar charts with side-by-side bars, and also horizontal bar charts. We will also learn how to load our data from a CSV file instead of having it directly in our script. Let's get started...
The code from this video (with added logging) can be found at:
bit.ly/Matplotlib-02
CSV Tutorial - • Python Tutorial: CSV M...
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#Python #Matplotlib
Who needs python docs when you have such an amazing teacher
True:
Exactly Brother
Where is the CSV for this? I don't see it in the description. Thank you!
True
the teacher
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 create pie charts.
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:
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As usual lovely!!!!!!!
It's a great tutorial; the only thing I was missing is to add total values on the top of each bar charts (can be trickier for stacked bar chart)
Thank you, sir, for providing top-class tutorials for free.
Hello Corey!
Please can you advise:
1. how did you the clean the data within the column " LanguageWorkedWith" so that you can generate this clear data?
2. After I have split it and save it to another csv file a part from the main, the is the output: [(" 'JavaScript'", 53020), (" 'HTML/CSS'", 39761), (" 'Java'", 29863), ("['Bash/Shell/PowerShell'", 28340), (" 'SQL']", 28178), (" 'Python'", 26185), (" 'PHP'", 20394), (" 'SQL'", 19094), (" 'TypeScript']", 16091), ("['HTML/CSS'", 15322)]
[Finished in 33.6s]
3. According the below output , how will I do so that it can bring the sum exact of the occurrence of the languages as it look like not doing it?
Thank you,
Where is the CSV for this? I don't see it in the description. Thank you!
In case you don't know, the shortcut for 8:13 in jupyter notebook is *Ctrl + left mouse click* on the different lines one by one. You can write at different lines at the same time.
Nice! Thanks form 2years later!
alt + left mouse in vs code
thanks u
@@jeffery_tang
These series is much better than the curses in Udemy I paid for. Thank you very much.
what "curses"
@@DendrocnideMoroides wannabe savage
No body teaches like you. You are the best. Amazing delivery of information, truly useful tutorials. Thank you so much.
Corey, you are great teacher. You have rare ability to explain calmly. Much appreciating your efforts.
Man, you are awesome, everything I have learned about python started from your channel, I wish you the very best all success, as you make everyone happy, keep up the excellent work, we all heavily rely on you.
Thanks! That's very kind of you.
Excellent tutorial Corey! Real life stuff and practical, including the use of Counter. It's important to show these data preparation steps. Very helpful indeed, thank you.
This series with pandas one has taken my skills to a new level.
such a great Python instructor with an angelic voice. Thank you so much 😊
Right from reading data from a csv file to plotting it, you helped a lot of people.
23:40 here's that one liner if anybody's interested. Personally, I like this more.
languages, popularity = map(list, zip(*language_counter.most_common(15)))
Really nice! Could you please explain what the "*" symbol does?
nice
Or just: list(zip(*language_counter.most_common(15))). Map is unnecessary as list() automatically maps over an Iterable
@@jg9193 but if you don't use map(list, iterable) then languages and popularity will be tuples so you cannot use reverve() for the rest of the tutorial. Or languages, popularity = [list(e) for e in zip(*language_counter.most_common(15))] without map
@@corben3348 Fair point, I didn't think of that. That said, he could just do languages[::-1] instead of languages.reverse() to reverse a tuple
Then again, using list() would even be unnecessary if he did that
I can't express how amazing this video is. What a great teacher you are. 🔥🔥
The great thing about your tutorials is that despite main topic, you learn a lot useful tricks, modules etc.
Another great video, thank-you. A Pandas series of videos would be awesome!
Amazing content Corey. The way you simplify the material and explain is awesome, many thanks. Can you please also do a video showing your setup and how you make video's. Thanks !!!
What I really like is your videos, Corey. I can learn Python and English ;D
Thanks!!
At 8:12, when you selected multiple locations and simultaneously type the same code to multiple lines, my world just expanded!
This is gold! Thank you very much for doing this, you have incredible talent to explain complicated stuff in an easy manner, keep up good work :)))
Thank you man, appreciate the effort and time you've put in creating such amazing content as these.
Another great video form you, Corey. Thank you, you made my day everyday!!
Your videos are just sprinkled with little golden nuggets! I love it ❤
Thank you for your work. I enjoy every lesson.
Thanks a lot Corey. Really your videos are endless treasure.
Just a way for plotting bar charts for more than one dataset on the same plot without need to numpy. Just use built-in map function.
width = 0.25 #Width of bar
plt.bar(list(map(lambda x: x-width/2, age_x)), salaries1, color = 'k', width = width)
plt.bar(list(map(lambda x: x+width/2, age_x)), salaries2, color = 'r', width = width)
Really nice work over here, the most important man on youtube for me.
This is the best Corey; Thank you very much from my 🧠 and ❣
What a perfect lesson, fast and insightful pieces of knowledge...
Corey Schafer saves my life once again...
Deep gratitude for your work, man!
thank you very much, very clear and straight to the point!
best matplotlib tutorial ever!
I think your videos are more understandable than rest of the youtube channels
Very informative video, good job Mr Corey
This is the best content on CZcams, thank you for so much
Great video as always! Really helpful for detailed explanation.
Very helpful video. The pandas method is much simpler and easier to understand. Thanks Corey!
Your explanation is awesome...thank you so much ...A great teacher for a lifetime...
thank you so much sir,really glad i found ur playlist and didn't waste time on other platforms
Thank you for sharing your knowledge!
This is pure Gold .
I just came across this series of videos. They are extremely good :-)
Thank you very much.its a great tutorial as always
You explain things really well, kudos!
Thank you so much for your hard work! You are a great teacher and your video tutorial represent a valuable resource :)
Thank you very much bro, Greetings from Azerbaijan.
Another great video. Thanks!!
thank you Brilliant for supporting Corey
Such a great help, thankyou so much!
thank you for always showing the clear code before abbreviating
Thank you for the series of video! :)
That's true......you are an amazing teacher. This was very helpful
Great video! Thank you man
great tutorial! the best!! thanks for teaching us!
You're making machine learning interesting, thank you
I can't believe we need this hack to make a bar chart.
Great video.
2 weeks later and still not a single dislike on this video
Great explanation...thanks a lot Corey sir
thank you professor. love from india. u know what i dont like to read those documentation. when i saw your videos.
As you mentioned Zip can also be used
language = cnt.most_common(10)
language.reverse()
language_X, language_Y = list(zip(*language))
plt.barh(language_X, language_Y)
Great videos. I'm so grateful...
Great video!
thank you!!!! you ar an excellent teacher
Amazing video !
This is the best fantastic lecture for the relation of Python and Pandas I've ever seen!!!!!!!!!!!!!!
Xie Xie!!!
you are amazing, waiting for your data science ( ML, AI ) course...... THANKS A LOT!
These videos are great! Coming from R (and ggplot) I was a tad skeptical that Python could emulate R when it came to data viz, but I stand corrected.
You're right
Very nice your explanations. Congratulations.
Corey. Million thanks bro
for those wondering how to obtain the CSV file, once you've clicked on it and you see all of the data in your web browser, just right click and say save as
jaja that was very useful, Thanks!
Thanks so much!
Thanks for this. Great lesson. As you say, creating multiple bars seems extraordinarily hacky. I would have thought this would be easily dealt with by a plotting library
Amazing Tutorials Thanks soo much !
you are a life saviour for people like me
Counter() is the best thing I learned today
Another great tutorial. Thank you. However, using a Jupyter Notebook, I am having a problem with plt.bar, plt.barh. The error I receive is "unsupported operand type(s) for -: 'str' and 'float'.
Thanks you and Brilliant
great instructor
Great Matplotlib tutorial. But I feel like this is where Pandas also really comes to play, we can use sep = ; inside of the read_csv function instead of creating a custom function. Also, using iloc and loc for indexes and many more awesome built in functions
Programming is so fun.
great tutorial, thanks
Thank you so much.. It's a great vedio....
Best of the best!
Thanks!
The best in you tube .👏
hi Corey....god bless you
Fantastic video. Exactly the type of content that I was looking for to create beautiful bar graphs.
Great, amazing video
Wonderful!
Thanks a lot CMS
collins anele That probably won’t work because value_counts() won’t split the data at the semicolons, so “Python;JavaScript” would be one value instead of two.
You are right. I just realised that.
Thank you very much. Please, please come back!
great video.
Thanks man!!
Tq sir
This is for u sir
while 2 < 3:
print('thank you soo much')
How to have the percentage values also listed along the Y-axis with language names as shown in the plot in the stackoverflow website (towards the end of the video)
I love Corey's videos*(infinite).
Please do a tutorial on numpy as well, it would be super helpful, by the way awesome content😁
ty soo much .. yu are the best ..
Great tutorial sir
that feel when I paused tutorial to figure out how to extract languages and popularity from language_counter and later it turns out that you've done that exactly in the same way, lol
thank you for python tutorial
Thank you lot sir 😃
Excellent videos Corey. Thanks.Quick question
I am getting an error at this line 'plt.barh(languages, popularity)' Error is: TypeError: unsupported operand type(s) for -: 'str' and 'float'
Using Spyder 3.1.4 and Python 3.6.
Downloaded the data.csv and copied it. Cannot figure out what's going on.
Hello Corey! Instead of using x_indexes, I transformed ages_x into a numpy array and used that array in the plot function. It shows same resuts as x_indexes and moreover, I do not need to change the x-axis notations. However, I want to know, is this method correct?