Matplotlib Tutorial (Part 2): Bar Charts and Analyzing Data from CSVs

[@Sharmapawan98]

Who needs python docs when you have such an amazing teacher

[@seanli75]

True:

[@niteshprajapat7918]

Exactly Brother

[@JoshKonoff1]

Where is the CSV for this? I don't see it in the description. Thank you!

[@SimonYells]

True

[@OT-tn7ci]

the teacher

[@ishanpand3y]

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.

[@jaxnaur218]

Nice! Thanks form 2years later!

[@jeffery_tang]

alt + left mouse in vs code

[@damalkkoklannou1620]

thanks u @@jeffery_tang

[@MrBuion]

These series is much better than the curses in Udemy I paid for. Thank you very much.

[@DendrocnideMoroides]

what "curses"

[@iscoto4914]

@@DendrocnideMoroides wannabe savage

[@TheShubham67]

This series with pandas one has taken my skills to a new level.

[@sunshadow9704]

Corey, you are great teacher. You have rare ability to explain calmly. Much appreciating your efforts.

[@fangshizhu9383]

At 8:12, when you selected multiple locations and simultaneously type the same code to multiple lines, my world just expanded!

[@bmwmhamam]

No body teaches like you. You are the best. Amazing delivery of information, truly useful tutorials. Thank you so much.

[@Ghasakable]

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.

[@coreyms]

Thanks! That's very kind of you.

[@apoorvwatsky]

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)))

[@costasvas341]

Really nice! Could you please explain what the "*" symbol does?

[@paklong2556]

nice

[@jg9193]

Or just: list(zip(*language_counter.most_common(15))). Map is unnecessary as list() automatically maps over an Iterable

[@corben3348]

@@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

[@jg9193]

@@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

[@shadowmasked7188]

Thank you very much bro, Greetings from Azerbaijan.

[@borhansiddiki7079]

I think your videos are more understandable than rest of the youtube channels

[@SahilKhan-rv9xb]

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

[@Alejandro-ry9ny]

jaja that was very useful, Thanks!

[@shashankbanakar8766]

Thanks so much!

[@abhishek_raj]

Right from reading data from a csv file to plotting it, you helped a lot of people.

[@KienDoanTrung168]

such a great Python instructor with an angelic voice. Thank you so much 😊

[@nicholasmaloof8378]

2 weeks later and still not a single dislike on this video

[@shuklarahul17]

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)

[@djadamkent]

Another great video, thank-you. A Pandas series of videos would be awesome!

[@introduction_official6547]

Very informative video, good job Mr Corey

[@akunnaemeka395]

thank you Brilliant for supporting Corey

[@ericfricke4512]

Programming is so fun.

[@miosz952]

The great thing about your tutorials is that despite main topic, you learn a lot useful tricks, modules etc.

[@dalanxd]

Corey Schafer saves my life once again... Deep gratitude for your work, man!

[@lalu225]

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.

[@manosmakris8308]

You can also do this for geting the languages and popularity lists. languages = list(map(lambda x: x[0], language_counter.most_common(15))) print(languages) popularity = list(map(lambda x: x[1], language_counter.most_common(15))) print(popularity)

[@Thedevineforce]

@Corey Schafer .. I came up with below function which will handle the bar widths for multiple bar plots by itself. Just in case anybody wants to use it : ages_x = np.asarray([25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]) count = 5 width = 0.8/count def width_cal(position): shift = np.array([]) if count < 2: return ages_x if count % 2 == 0: for i in range(1, count, 2): shift = np.append(shift, (width/2 * i)) shift = np.sort(np.append(shift, np.negative(shift))) else: for i in range(0, count, 2): shift = np.append(shift, (width/2 * i)) shift = np.unique(np.sort(np.append(shift, np.negative(shift)))) shift = np.around(shift, decimals=3) return ages_x + shift[position] plt.bar(width_cal(0), dev_y, width=width, color='#444444', label="All Devs")

[@ahmedskasmani]

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 !!!

[@micheliwrmg]

sad fact, if you want to open csv file in PYcharm , you have to pay for PYcharm Professional(~$230) :( btw you are the best teacher I've ever seen

[@dhssb999]

best matplotlib tutorial ever!

[@SM-vu6fm]

Counter() is the best thing I learned today

[@luiggitello8546]

This is the best content on KZbin, thank you for so much

[@storiesshubham4145]

I can't express how amazing this video is. What a great teacher you are. 🔥🔥

[@58_yesilgul]

What a perfect lesson, fast and insightful pieces of knowledge...

[@mohammedismail308]

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)

[@Anon282828]

thank you for always showing the clear code before abbreviating

[@rotrose7531]

Thank you very much. Please, please come back!

[@dgh25]

Your videos are just sprinkled with little golden nuggets! I love it ❤

[@brumarul7481]

This is pure Gold .

[@rahil1575]

you are a life saviour for people like me

[@ItzSenaCrazy]

What I really like is your videos, Corey. I can learn Python and English ;D Thanks!!

[@MagnusAnand]

I can't believe we need this hack to make a bar chart. Great video.

[@eziola]

Would still love to see a video on counters and DefaultDict!

[@dhairyaoza5422]

thank you so much sir,really glad i found ur playlist and didn't waste time on other platforms

[@gamengine1176]

Very helpful video. The pandas method is much simpler and easier to understand. Thanks Corey!

[@pratikarai8115]

Your explanation is awesome...thank you so much ...A great teacher for a lifetime...

[@markkennedy9767]

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

[@muzaianghanem5644]

That's true......you are an amazing teacher. This was very helpful

[@androkranjcevic1988]

Really nice work over here, the most important man on youtube for me.

[@redferne01]

Thank you for your work. I enjoy every lesson.

[@luiscesar_agais]

Very nice your explanations. Congratulations.

[@LashaGoch]

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 :)))

[@eliesawan9513]

you are amazing, waiting for your data science ( ML, AI ) course...... THANKS A LOT!

[@Lucas-wn5wm]

I jus found the python legend . Thank god

[@KC-rl8ub]

hi Corey....god bless you

[@niceday2015]

for i in range(1,365): print("Thank you very much")

[@edcoughlan5742]

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.

[@kabongontumba9492]

You're right

[@Linshark]

I just came across this series of videos. They are extremely good :-)

[@brucegwon]

This is the best fantastic lecture for the relation of Python and Pandas I've ever seen!!!!!!!!!!!!!! Xie Xie!!!

[@SandeepChaudhary-vx9zy]

Great explanation...thanks a lot Corey sir

[@ronaldjohnson4470]

Corey, I went back to the documentation, and changed by code to ax=plt.subplot() ax.set_xticks(x_indexes) ax.set_xticklabels(ages_x) It worked, but I received a message : MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance. In a future version, a new instance will always be created and returned. Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance. warnings.warn(message, mplDeprecation, stacklevel=1)

[@KumarGauravhi]

Hi Corey, thank you for the wonderful session , I have stuck at this point with the last example :-import csv import numpy as np import pandas as pd from collections import Counter from matplotlib import pyplot as plt plt.style.use("fivethirtyeight") data = pd.read_csv('data.csv') ids = data['Responder_id'] lang_responses = data['LanguagesWorkedWith'] language_counter = Counter() for response in lang_responses: language_counter.update(response.split(';')) languages = [] popularity = [] for item in language_counter.most_common(15): languages.append(item[0]) popularity.append(item[1]) languages.reverse() popularity.reverse() plt.barh(languages, popularity) plt.title("Most Popular Languages") # plt.ylabel("Programming Languages") plt.xlabel("Number of People Who Use") plt.tight_layout() plt.show() ### I am getting an error like AttributeError: 'float' object has no attribute 'split' ...Please explain..

[@Coney_island23]

thank you!!!! you ar an excellent teacher

[@oscar.kiamba]

The best in you tube .👏

[@franklinlima2571]

Great video! Thank you man

[@mamathakavety6529]

Please do a tutorial on numpy as well, it would be super helpful, by the way awesome content😁

[@AbubakerMahmoudshangab]

Corey. Million thanks bro

[@jsceo]

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

[@akashdeepchauhan5]

You're making machine learning interesting, thank you

[@hayetchekired462]

great instructor

[@fourdaysdead]

thank you very much, very clear and straight to the point!

[@frankconte2457]

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'.

[@thebuggser2752]

Another great video. Thanks!!

[@abhishek_raj]

You explain things really well, kudos!

[@shreddersengupta7384]

we can also use the dictionary's keys() and values() for getting x and y axis. x_axis = list(dict.keys())

[@Eric-ii4vj]

you can just use : plt.barh(list(reversed(df['language'])),list(reversed(df['popularity'])))

[@minghaotao6259]

Thank you for sharing your knowledge!

[@adirbarak5256]

for unpacking counter.most_common(x) you can use: for a,b in counter.most_common(x) or for a,b in counter.items(): cause they are the same, they are a list of tuples, which is "zipped" already = meaning you can iterate of it simultaneously (a is tuple[0]. b is tuple[1]) I hope it helps you, yea you out there.

[@PaoloCondo]

Thank you for the series of video! :)

[@kerimabdul2263]

great video.

[@alexanderten5497]

Thank you very much.its a great tutorial as always

[@chandansarkar1123]

We can not thank you enough..still thanks a ton Corey. I have an interesting observation @9.48. In the plt.xticks(...) method when I use the ticks and labels keywords it gives me AttributeError. It works when I pass the arguments without using keywords. Perhaps it has something to do with my Matplotlib version...

[@nikhiledu7556]

Same happened with me

[@asas-jf5iz]

yes, some old version matplotlib will have this problem.

[@kabongontumba9492]

Thank you guy, I had the same problem

[@questscape]

For PANDAS folks:- import pandas as pd from collections import Counter df = pd.read_csv('data.csv', index_col=['Responder_id']) language_counter = Counter() for response in df['LanguagesWorkedWith']: language_counter.update(response.split(';'))

[@abhishek_raj]

just a suggestion for people with large samples, Use seaborn style, this 538 gets screwed when number of labels is more.

[@FerdinandCoding]

thank you for python tutorial

[@DeepakKumar-uz4xy]

thank you professor. love from india. u know what i dont like to read those documentation. when i saw your videos.

[@lillyclive2641]

Such a great help, thankyou so much!

[@DidaKusAlex]

great tutorial! the best!! thanks for teaching us!

[@rnytpl]

Thank you man, appreciate the effort and time you've put in creating such amazing content as these.

[@guyindisguise]

At 9:30 you correct the numbers of the x-axis with plt.xticks() Couldn't we just have circumvented that problem by saying x_indexes = np.array(ages_x) instead of x_indexes = np.arange(len(ages_x)) Since that would have given us an array with the original numbers that we could add/subtract the width to/from? Is there any benefit to the plt.xticks() solution (other than seeing how xticks work)?

[@johannesherbert4943]

I thought the exact same thing, why is he making his life more complicated than necessary? There is no problem with adding/subtracting offsets directly from the ages np.array, it just works. It makes it less hacky, too.

[@tongliu1076]

Great video as always! Really helpful for detailed explanation.

[@johnjones5659]

Thanks you and Brilliant

[@shazkingdom1702]

This is the best Corey; Thank you very much from my 🧠 and ❣

[@rajivswargiary1536]

Great tutorial sir

[@rahulp1985]

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)

[@VishalSharma-rn7mt]

Great, amazing video

[@Martin-ij2fp]

Great video!

[@hatemsabrey]

Corey, my online teacher, where is the counter video ??? million thanks for your efforts

[@randiarisman2419]

Another great video form you, Corey. Thank you, you made my day everyday!!

[@OT-tn7ci]

it might be a better idea to reverse the list of tuples inside the for loop or before that hehe. Also thanks for pointing out the inline zip function, its much easier for my eyes. Thanks a lot

[@timeforrice]

could you do more videos about data cleaning? Thank you and I love your blog.

[@emmanueljimawo5595]

Great videos. I'm so grateful...