Solving 100 Python Pandas Problems! (from easy to very difficult)

In this tutorial, you'll gain hands-on experience with the python pandas library, building experience with data manipulation and analysis skills important for data science. You'll learn how to create, modify, and analyze DataFrames, handle missing data (NaNs), clean messy data, and generate some visualizations. By tackling a variety of problems, from basic data handling to advanced DataFrame techniques, you'll build a solid foundation in managing and interpreting real-world data sets using pandas.

Repo we're working off of (credit to Alex Riley who put repo together):

My code solutions (use repo above for blank starting template):

Hope that you enjoy this video. If you do, make sure to like it and subscribe to not miss future videos like this!

Video Timeline!
0:00 - Intro & Setup
2:14 - Problems (1-3) Initial pandas setup
4:42 - Problems (4-10) DataFrame operations
4:52 - 4) Create a dataframe from dictionary
5:24 - 5) Display dataframe summary
5:41 - 6) First 3 rows of the dataframe
6:02 - 7) Select ‘animal’ and ‘age’ columns
7:42 - 8) Data in specific rows and columns
9:06 - 9) Rows with visits greater than 3
9:57 - 10) Rows with NaN in age
10:56 - 11) Cats younger than 3 years
11:35 - 12) Age between 2 and 4
12:45 - 13) Change age in row ‘f’
15:56 - 14) Sum of all visits
16:41 - 15) Average age by animal
20:21 - 16) Modify and revert rows
24:06 - 17) Count by animal type
25:28 - Quick review
26:17 - 18) Sort by age and visits
28:07 - 19) Convert 'priority' to boolean
29:42 - 20) Replace 'snake' with 'python'
30:53 - 21) Mean age by animal and visits
33:49 - Advanced DataFrame techniques
33:57 - 22) Filter duplicate integers
43:18 - 23) Subtract row mean
45:42 - 24) Column with smallest sum
50:39 - 25) Count unique rows
53:17 - 26) Column with third NaN
1:10:27 - Solution review for 26
1:17:13 - 27) Sum of top three values
1:24:01 - 28) Sum by column condition
1:40:11 - Recent problem review
1:42:53 - 29) Count differences since last zero
1:56:19 - 30) Locate largest values
2:08:38 - 31) Replace negatives with mean
2:17:43 - 32) Rolling mean over groups
2:23:10 - Series and DatetimeIndex
2:23:12 - 33) DatetimeIndex for 2015
2:27:56 - 34) Sum values on Wednesdays
2:45:04 - 35) Monthly mean values
2:46:16 - 36) Best value in four-month groups
2:50:26 - 37) DatetimeIndex of third Thursdays
2:59:03 - Cleaning Data
2:59:40 - 38) Fill missing FlightNumber
3:02:45 - 39) Split column by delimiter
3:06:47 - 40) Fix city name capitalization
3:08:30 - 41) Reattach columns
3:13:11 - 42) Fix airline name punctuation
3:17:45 - 43) Expand RecentDelays into columns
3:27:31 - MultiIndexes in Pandas
3:27:34 - 44) Construct a MultiIndex
3:30:37 - Solution review
3:32:44 - 45) Lexicographically sorted check
3:32:58 - 46) Select specific MultiIndex labels
3:34:23 - 47) Slice Series with MultiIndex
3:35:24 - 48) Sum by first level
3:37:47 - 49) Alternative sum method
3:40:08 - Additional solution insights
3:41:22 - 50) Swap MultiIndex levels
3:45:27 - Minesweeper problems
3:45:44 - 51) Generate coordinate grid
4:00:28 - 52) Add 'safe' or 'mine' column
4:03:04 - 53) Count adjacent mines
4:27:33 - Review solution to 53
4:33:02 - Skipped problems 54 & 55
4:33:11 - Plotting
4:33:12 - 56) Scatter plot with black x markers
4:41:26 - 57) Plot four data types
4:52:50 - 58) Overlay multiple graphs
5:03:11 - 59) Hourly stock data summary
5:14:12 - 60) Candlestick plot

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Practice your Python Pandas data science skills with problems on StrataScratch!

[JatinKumar-cnwt]

Are you crazy man, 5 hour + course only for pandas, man your dedication for teaching is amazing

[raphaelmatthew]

Please guys give this video a like if you haven't, it takes a lot of work to create such a masterpiece. Welcome back Keith🎉.

[KeithGalli]

Woo!!! 5 hours of Pandas practice, what could be better. Hope you all enjoy!

[d.g]

This is what I was looking for.
Thanks Keith

[renatolippi]

Excellent! Thank you very much for this video!! Please more with this format 👏

[JW-puuk]

Dude I freaking LOVE your content. I am so stoked to see this video and have it bookmarked for the rest of my data science career lol

[Kidpambi]

It is great to have you back teaching 🎉

[vedantlssj]

This the kind of content that makes YouTube the great source of learning it is!

[ryandavis]

OMG keith you are a lifesaver! thank you!

[rrrprogram]

Subscribed.... the way you are doing is a genuine way of making mistakes and then learning

[abdulbasitnisar]

Thank you such much!! whatever you are doing actually is life changing for people like me who is self learning these! Thank you!!!

[chetan]

This video would be really helpful.
Keep up the great work!😊

[Soso]

more of this buddy enjoyed each second

[tdcode]

Man, you're crazy 🤣🤣🤣🤣🤣🤣🤣🤣🤣. This is awesome! Thanks for a colossal and great video!!!🎉🎉

[JudyLuHe]

Hi Keith, Genuinely appreciate you solving all these pandas problems. I am not sure if you already have but I was wondering if you could also do one on the 100 Numpy problems? Again, thanks for you work.

[conykuo]

5 hours pandas video is crazyyyy. Must give a thumb up!

[ngoclinhvu]

5 hours of pandas puzzles??? Just what I need!

[paraglide]

Thanks man, I was just looking for getting into Pandas.

[second]

This is awesome! can you do for other libraries too please!!!

[klausditrich]

I'm too old for all the Minecraft or Fortnight streams, so here I'm and loving it :-)