Python Pandas - Comprehensive Course With Theory, Examples, And Practice Problems

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Complete course explaining how to use Python Pandas for data wrangling. You should have a basic understanding of Python and NumPy prior to taking this course.

0:00 - promo
1:26 - 1.1 introduction
2:15 - 2.1 Series creation
8:48 - 2.2 Series basic indexing
19:38 - 2.3 Series basic operation
22:51 - 2.4 Series boolean indexing
26:19 - 2.5 Series missing values
31:41 - 2.6 Series vectorization
33:45 - 2.7 Series apply()
35:59 - 2.8 Series view vs copy
40:24 - 2.9 challenge: baby names
42:12 - 2.10 challenge: bees knees
43:39 - 2.11 challenge: car shopping
46:08 - 2.12 challenge: price gouging
48:14 - 2.13 challenge: fair teams
50:34 - 3.1 DataFrame creation
52:51 - 3.2 DataFrame to and from CSV
56:00 - 3.3 DataFrame basic indexing
1:02:13 - 3.4 DataFrame basic operations
1:03:58 - 3.5 DataFrame apply()
1:07:53 - 3.6 DataFrame view vs copy
1:10:22 - 3.7 DataFrame merge
1:18:16 - 3.8 DataFrame aggregation
1:22:01 - 3.9 DataFrame groupby()
1:32:56 - 3.10 challenge: hobbies
1:35:40 - 3.11 challenge: party time
1:38:28 - 3.12 challenge: vending machines
1:39:23 - 3.13 challenge: cradle robbers
1:41:25 - 3.14 challenge: pot holes
1:44:03 - 4.1 strings
1:47:41 - 4.2 dates and times
2:05:57 - 4.3 Categoricals
2:11:00 - 4.4 Multiindex
2:16:38 - 4.5 DataFrame reshaping
2:23:49 - 4.6 challenge: class transitions
2:25:34 - 4.7 challenge: rose thorn
2:27:41 - 4.8 challenge: product volumes
2:30:24 - 4.9 challenge: session groups
2:34:56 - 4.10 challenge: obgym
2:37:20 - 5.1 challenge: covid tracing
2:40:01 - 5.2 challenge: pickle
2:41:46 - 5.3 challenge: tv commercials
2:43:30 - 5.4 challenge: family iq
2:47:36 - 5.5 challenge: concerts

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Loved your numpy comprehensive course - so now I moved on to pandas, and with you as a coach - I bet it will just be as good and well explained. Here I go! ( :

loklishplays
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I will be sharing this w everyone who wants to learn pandas. By far the best source I've found

brucemurdock
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at first I did not enjoy the music in the background, but after warming up to it I love it!

cadehaak
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Amazing tutorial series! If I can have one little addition to make, it would be nice if there were problem solution examples, as I have sometimes interpreted the question wrong and ended up with a different answer than yours.
Still, great series and it's a great help!

Watashiwapitadesu
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@18:55, I am not getting the result as described in the video. It gives this error. "ValueError: cannot set using a slice indexer with a different length than the value". I am running this line. x.iloc[:2] = y

END-ch
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Awesome tutorial! Question regarding @1:01:00
Wouldnt df[['shrimp', 'red fish']].iloc[:3] be way more convenient? Or is there a downside to this approach

PART
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How in hell does this only have ~800 views?

arsnocturnaaudio
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anti join exist in dplyr why can't panda just add this one

xiaoranmo
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Check out these [updated] problems in written form @

gormanalysis
visit shbcf.ru