Matplotlib Crash Course

Learn the basics of Matplotlib in this crash course tutorial. Matplotlib is an amazing data visualization library for Python. You will also learn how to apply Matplotlib to real-world problems.

Install libraries Needed for this video:
Option 1:
Open up a terminal window and type
pip install matplotlib
pip install numpy
pip install pandas

Option 2:

--

[Ricocase]

"Let's just jump into it" = immediate upvote

[leixun]

*My takeaways:*
*1. Line chart* 2:11
1.1 Potting a line chart using *plot* and *show* 3:27
1.2 Adding a title using *title* 5:21
1.3 Adding labels to x and y axes using *xlabel* and *ylabel* 6:24
1.4 Changing the font of title and labels. Resizing title and labels using *fontdict* 7:02
1.4 Editing tick marks using *xticks* and *yticks* 8:50
1.5 Adding a legend using *legend* 11:04
1.6 Changing line style by passing parameters to *plot* 12:14
1.7 Adding a 2nd line 17:33
1.8 Resizing a chart using *figure(figsize(), dpi=)* 21:55
1.9 Saving a chart using *savefig* 24:34
*2. Bar chart* 26:48
2.1 Potting a bar chart using *bar* and *show* 27:40. The size of a bar chart can be changed using *figure(figsize(), dpi=)* as well
2.2 Setting bar patterns using *set_hatch* 28:50
*3. Real world Matplotlib examples* 31:10
3.1 Example 1 - line chart 34:36. Input .csv data file using *pandas pd.read_csv()*
3.2 Example 2 - histogram 52:35. Potting a histogram using *hist* and *show* . Setting bins.
3.3 Example 3 - pie chart 1:00:08. Potting a pie chart using *pie* and *show* . Looking for a condition in the data using *pandas loc* . Adding labels for pie chart using a list. Changing colour. Show percentage using *autopct*
3.4 Example 4 - another pie chart 1:07:20. Converting string data to integer data using *strip* . Changing the pie chart style using *style.use* . Using *pctdistance* to define the positions of percentage. Using *explode* to split the pie chart.
3.5 Example 5 - box plot 1:18:33. Potting a box plot using *boxplot* and *show* . Using *set* to set colour and linewidth

[MrVovik]

Much better than lots of those paid courses out there! Lean, clean and straightforward! Thanks a lot and please please record more videos on other data Science and python related topics in the same manner you did this course!

[rishabhmediratta]

plt.figure(figsize = (12, 7))


for c in gas.columns[1:]:
plt.plot(gas['Year'], gas[c], label=c, marker='.')

plt.legend()



plt.show()



This worked for me while plotting the line graph for all countries!
(Note : Include the import statements and read the csv first, haven't included that here.)
Thank you for the tutorial! This channel is basically where I have started picking up things.

[saurabhsamdani]

I think keeping documentation window open was such a great advice. My struggles with matplotlib have gone down once I Put that tip in practice.

[yudhisthirsingh]

Great teacher you are man. I have watched all your data visualization videos they all are amazing...

[softyo]

i cant believe this is free of you so i have also watched your numpy and pandas tutorials and enjoyed them very much!!! thank you for doing this, you are making such a difference.

[nikitaizmaylov]

I can easily tell that Keith is very keen on FUT and probably has like the best Ultimate team in FIFA 21 ahahahha. Really enjoyed your course, very coherent and simple. Thank you!

[adithyavikramrajgaroju]

Thanks a lot Keith, very crisp explanation!

[RahulSingh-ilsz]

exactly what I was about to start. Thank you.

[jameshuang]

Very quick, clear and concise highly recommended

[pi_r_mlm]

Wow ! It's a superb course ! I learnt tons of things ! Also, at 59:00, you can use log=True option to make y log scale
You're doing great ! Carry on !

[RabiulIslam-twqc]

Thank you very much for your wonderful teaching and real-world example. Nice course for learning.

[upgraduate]

Thank you so much for your great tutorials.

[dhanushkamadhusanka]

Thank you, Highly appreciate... most important thing is, this is free for every one.. this course much better than paid courses...

[anmolmaitra]

Thank you so much for your great tutorials. Can you do a tutorial on tableau please?

[CodyBanks]

Great introductory course to Matplotlib.

[kostiantynkarzhanov]

Very well explained! Thank you very much! 💛

[bhanutejachittabathini]

thank you so much man .much appreciated

[shashankgsharma]

Okay, it took me a lot of time to complete numpy, pandas and matplotlib from you keith, but I think it was worth it. Although, I remember NULL.