Python for data analysis: Analysis and wrangling, using tools like Panda and NumPy. Reading and writing CSV, HTML, XML, JSON, MATLAB. And much m - Tony Wes

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Résumé :
It ?? n? d?ubt that python ?? ?n? ?f th? best suited ?r?gr?mm?ng languages when ?t ??m?? t? a d?t? ????nt??t. It has b??n ???k?n of t?m? ?nd ?g??n th?t Python ?? th? m??t ??mm?n programming l?ngu?g?? in ???? ?f ??m?ut?ng. But ?ft?n times, the question of wh? one should ?tud? this l?ngu?g? comes ?nt? v??w.

Here is why, you ?h?uld l??rn P?th?n, ?f you w?nt to venture ?nt? th? field of d?t? science - B???u?? P?th?n ?? a flexible l?ngu?g?, ?t ?? fr?? ?nd powerful ?l?ng w?th being ?n open source language. The language d?v?d?? th? d?v?l??m?nt time ?n h?lf b? its ??m?l??t?? ?? well ?? m?k?? ?t ???? t? r??d the syntax. With th? h?l? ?f ??th?n, ?n? can ??rf?rm m?n??ul?t??n of th? data, analysis ?f th? d?t? ?? well as ??rr? out data visualization. P?th?n br?ng? t? ?n? libraries th?t are essential f?r th? ???l???t??n? ?f machine l??rn?ng as w?ll ?? ?th?r ????nt?f?? processing ?f data.

The b??t ??rt ?b?ut l??rn?ng Python is that it ?? a h?gh level l?ngu?g? th?t ?? quite ???? t? l??rn and ?? procedure ?r??nt?d along with b??ng object ?r??nt?d.


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