Matplotlib Full Python Course - Data Science Fundamentals
Вставка
- Опубліковано 8 лип 2024
- In this video we do a complete Matplotlib crash course in Python.
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Timestamps:
(0:00) Intro
(2:42) Installation
(5:52) Scatter Plots
(12:04) Line Plots
(16:50) Bar Plots
(20:29) Histograms
(24:29) Pie Charts
(29:22) Boxplots
(33:25) Plot Customization
(40:10) Legends & Multiple Plots
(44:02) Plot Styling
(45:50) Multiple Figures
(47:39) Subplots
(50:47) Exporting Plots
(54:00) 3D Plotting
(59:30) Animating Plots
(1:02:08) Outro - Наука та технологія
![ОРБАН приехал к ПУТИНУ и "отчитался" о поездке в Киев 😁 [Пародия]](http://i.ytimg.com/vi/_0ukDovOWq8/mqdefault.jpg)
I actually had another video for matplotlib open but then I saw yours on the side panel and immediately felt the need to watch it, best decision, you just explain it better than anyone else. Thank you
Thank you so much for the course. You have no idea how much of a difference you've made.
It was a pleasure watching this short tutorial. I got ideas for my own thing from it.
WOW, That was amazing. You covered most of the fundemntals in an hour. I really learned a lot.
Sehr schönes und einfach erklärtes Video. Ist für mich wie ein animiertes Cheatsheet 🙂
Please make crash course of pandas
This video was simple to understand and contain important powerful content for me to learn Matplotlib for the very first time. The best fact about this video is that it was SHORT yet the information showed years of experience and knowledge. Thank you so much for making Data Science accessible to people like me who are very new to coding and data science. Keep up the brilliant work and making your explanations simple for people like me to understand. Many thanks for an incredible crash course!
Thanks a lot for bringing in such a content. Would love to see a crash course on pytorch or something like this
Super cool video, refreshed a lot of concepts I haven't used in a while. Subscribed and will watch more!
Thank you for your time and effort. You have made it so easy to understand these concepts in such a short video. Thank you once again.
great video, thanks man
this is something data scientists should have as compulsory course
Honestly amazing video - I learnt so much and was engaged throughout.
See your chanel first time and what to leave a comment. English is not my native language I have Intermediate level of English but I completely understand every take of your video. I understood everything thanks to your way of expressing your thoughts and the examples you provided. I also liked that there was nothing superfluous. I wish prosperity and growth to your channel
Amazing video. Followed every step! Thanks.
It was an amazing course, understands how the matplotib only in a single video !!
Excellent style of making me understand. Thanks for this
Nice, I learned about the pause function in plotting :)
That was an amazing video, with a great explanation! Thanks for this rich content.
thank you for wonderful video we really appreciate
thank youuuu sooo much for this amazing tutorial
How.. How is every video a banger?
as a spanish speaker.
i been spend 4 long years to be bilingual so i understand the 90% what you said.
so i have some grammatic mystakes in my sentences.
many thanks for your tutorial bro.🎉😊
Thank you this was very helpful !
Awesome explaination !
Thanks brother, amazing video
Super Video! Habs grad durchgemacht und mir mit Phyinstaller ein Exe File der Demos gebaut. Nur bei dem Log Beispiel kommt ne Division durch Null Warnung, und am Schluss die Animation mit den 100000 Durchläufen ist etwas lang 😂 und muss dann Abgeschossen werden.
Jetzt wäre in dem Zusammenhang interessant wie man echte Daten aus zB Textdateien / Exceldateien / Datenbanken zb SQlite einlesen und Visualisieren kann. Vielleicht auch noch ein File mit Plot Konfigurations Daten.
¡Amazing course! Thanks a lot.
i look the video maybe the best youtube chanel in my opinion
bro is loving popos. thank you btw
super helpful. Thanks!
Thank you so much for this
absolutely perfect
Your explanation is very good..Very informative and useful for presentation we need at office
Thank you so much!
Such a excellent video.....
Banger content as usual
Thanks for the educational video
Thank you !
It was very helpful for beginner like me. Thabk you very much. Now please make another for with details on heat maps, meshgrids please, topography.
Thank you a lot.
*Can you show us what is the best way to transfer a py file to exe? Im talking about huge programs contains many modules… thanks in advance*
thank you so much :)
Thanks man !
Hey, that's an awesome tutorial but I had to say you completely disregarded polar plots for some reason, being the reason I came here in the first place I was kinda left unsatisfied but overall always some awesome content !
thank you!
Thank you, excellent
excellent as alwayas.
You're really good
Thank you!!
bro doesn't blink whatsoever
Loved it
Thank you🙏
hey i have a question, i was using ggplot2 in R for a while and it contain a interactive interface for ploting data, called esquisse. I wanna know if there's a similiar thing in matplotlib library?
great video
Also do for plotly
how did u make your plt console black? not the backgroud, i want to make console black
so helpful
Thanks
WOW!!! THX
thanks
Your video is excellent with some great tips. Your faded white characters on a dark gray background make it tedious to follow your code. A slightly larger font would also be appreciated.
How difficult would it be to open a csv file, and loop thru each column, and if it's the desired column, then plot it?
I was thinking something like
# for each column loop:
# axIdx = ax1.twinx()
# axIdx.plot(time, column_data,color=UUUUUUU, label=ZZZZZZ)
# axIdx.legend(loc='upper right', bbox_to_anchor=(XXXXX, YYYYY), ncol=2, borderaxespad=0)
# axIdx++
where axIdx would have to be a variable that is being generated as it processes the file? Similarly, the color (UUUUUU), label (ZZZZZZ), and position where to put that data's legend (XXXX/YYYY) would need to be variables based on the column being processed, and the number of items already plotted?
Or thoughts on how one might solve this kind of plot?
Wonderful lesson!!! Would you be interested on a project for healthcare? Perhaps a 1:1 conversation. Pls let me know. Tks
how are you able to rotate the 3d plot ?
Could you please share this file ? Or which platform this?
I love see tutorials on english xD
What IDE do you use?
thnx
Make a course on scikit learn
It would be better if the explanation was on dataset rather than a lists of values
Great video, easy to follow for beginners like me
please make crasg course of pandas
Thx_.
good
Hey I was wondering If I could get your help. This is from the 3d section of your video I believe and the code doesn't work, I tried to fix it for newer version but it still isnt' working 100 percent. Here what I did to edit your code for this section
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-5,stop=5, num=100)
y = np.linspace(-5, stop=5, num=100)
x, y = np.meshgrid(x,y)
z = x * y
fig = plt.figure(figsize=(14,6))
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(x, y, z, cmap='viridis')
ax.set_title('3D Plot')
ax.set_xlabel('X-Axis')
ax.set_ylabel('Y-Axis')
ax.set_zlabel('3D Plot')
plt.show()
❤👍
Bro to learn machine learning and deep learning should I learn maths in depth?
I'm feeling difficulties in maths😢
Matplotlib didn't work please help me.
Nah, I would avoid using Matplotlib. HvPlot or Plotly Express are way simpler and also interactive.
Yes thats true, but they are R libraries and thus better suited in R than python. Thats why everybody uses matplotlib instead of plotly or gplot in python.
U skipped stack plot.
Thanks a lot. kindly share the source code
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Great Cake for breakfast but waiting for dinner 😁🏆
20:55
"1 for Java" 💀
Lmfao
20:00
33:21
Please make a crash course of pandas
At least incease the font size or use the zoom feature of the screen recorder or do both like other tutorials. You have a good tutorial but it seems like a waste when you don't even bother to take into consideration your viewers who are watching the video.
What can be a reason to not have titles displayed in the Subplots part, nor "test" label?
just in case copying my code here
x = np.arange(100)
fig,axs = plt.subplots(2,2)
axs[0,0].plot(x, np.sin(x))
axs[0,0].set_title("Sine Wave")
axs[0,1].plot(x, np.cos(x))
axs[0,1].set_title("Cosine Wave")
axs[1,0].plot(x, np.random.random(100))
axs[1,0].set_title("Random Function")
axs[1,0].set_label("test")
axs[1,1].plot(x, np.log(x))
axs[1,1].set_title("Log Function")
axs[1,1].set_label("test")
plt.show()
it's ok for labels, but doesn't work for title, not for suptitle