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Hi, welcome back.

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And this lecture, you will learn how to visualize the data that you from grabbing of it, as we said

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before, firstly, we will involve pandas as we then import mateparae the plot as builtin, then we

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will run the self as a following.

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Secondly, we will use pandas to read the HTML file from our webpage, then bring that data.

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And finally, we will restore the important part of that data in a data frame, for example, called

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D.F..

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So the factual data between two square brackets zero.

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Then we will present the data frame by type D.F. and Excel and run that.

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So now we will use matplotlib by plot module to visualize that data as the following assign website's

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variable to the EFF website column.

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Then we do that for the second column.

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We want to visualize popularity.

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So we have now two variables websites and unique visitors per month and ready to be.

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Then if we want to add a great effect to our short, which will be a pie chart, we will use explode

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or explosion Caywood.

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As the following, but firstly, as fines explode values to a variable called AXP, as we will choose

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the first three important values to be.

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Four point twenty five exploded far from our pie chart and the rest of values are zeroes.

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Then we will write the code for the blood method as the following e x, the equality between two square

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brackets, four point twenty five point one in five point twenty five and comma between them, then

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comma zero zero zero zero zero zero zero zero zero zero.

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So we will complete that 13 13.

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Websites, all 16 volumes of our columns as the following by exploded Xeros bellati dot by between two

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brackets, unique, underscore, visita, underscore, bear, underscore months and labels Werbe website

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schedule will be through, radius will be two and Utterback will be percentage two point one f centage

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percentage between to Prentice's and explode equal Yaqubi and DLT Duchow.

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From this, could we observe that we have unique visitors per month variable as the values of the bytecode

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and the labels for that values will be the website's variable values?

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Also that we choose to shadow our pie chart as shadow equal.

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True then to percentage of every value of unique visitors for every website we will add up to baked.

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World as the following as.

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Percentage two point one percent if presented with a sentence.

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Lastly, we add explosion to our pie chart by using explode Caywood as we discussed before.

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The last episode in the sale of data visualization using matplotlib block by block module as the methods

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as you see VLT, Duchow then runs the cell and we get our Bichard.

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Please look at this bite chart and write your conclusion and you will compare your conclusion with my

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final conclusion.

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Our final conclusion will be as the following Zumwalt's autosite, a number of unique visitors as Google

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and the most second two sites and a number of unique visitors are Facebook and YouTube.

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JavaScript is the most wanted programming language in these tech companies.

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Most database management system in these companies is Maria De.

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At this point, we reach the end of this lecture.

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I hope you enjoyed this lecture and get all of that.

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Thank you for being here.

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And please don't forget to stop the video and make your observation about the data visualization and

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make conclusions that better than the final conclusion or convey our conclusion with my final conclusion

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as data analysis.

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Final conclusion of report differ from person to person according to data, but not differ.

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And in fact, this differ in expressions.

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So try to write.

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You'll find a conclusion by yourself.

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Thanks for watching.

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See you next with you.