- High Level description of your data (min, max, mean, std dev, etc.)(00:15:47 - 00:16:24) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- High Level description of your data (min, max, mean, std dev, etc.)(00:15:47 - 00:16:24)
Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

Data & code used in this Tutorial: https://github.com/KeithGalli/pandas
Python Pandas Documentation: http://pandas.pydata.org/pandas-docs/stable/

Let me know if you have any ...
Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

Data & code used in this Tutorial: https://github.com/KeithGalli/pandas
Python Pandas Documentation: http://pandas.pydata.org/pandas-docs/stable/

Let me know if you have any questions!

In this video we walk through many of the fundamental concepts to use the Python Pandas Data Science Library. We start off by installing pandas and loading in an example csv. We then look at different ways to read the data. Read a column, rows, specific cell, etc. Also ways to read data based on conditioning. We then move into some more advanced ways to sort & filter data. We look at making conditional changes to our data. We also start doing aggregate stats using the groupby function. We finished the video talking about how you would work with a very large dataset (many gigabytes)

I realized as I upload this video there are some additional things I want to talk about in a later video. The first thing that comes to mind immediately is using the apply() function on a dataframe to alter the data using a custom or lambda function. If you have questions on this or anything else before I get around to making a part 2, feel free to write me a note in the comments.

If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos!

Thanks for watching friends! Happy coding! :)

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Link to original source of data from Kaggle: https://www.kaggle.com/abcsds/pokemon

---------------------------------------------
Video Outline!
0:00 - Why Pandas?
1:46 - Installing Pandas
2:03 - Getting the data used in this video
3:50 - Loading the data into Pandas (CSVs, Excel, TXTs, etc.)
8:49 - Reading Data (Getting Rows, Columns, Cells, Headers, etc.)
13:10 - Iterate through each Row
14:11 - Getting rows based on a specific condition
15:47 - High Level description of your data (min, max, mean, std dev, etc.)
16:24 - Sorting Values (Alphabetically, Numerically)
18:19 - Making Changes to the DataFrame
18:56 - Adding a column
21:22 - Deleting a column
22:14 - Summing Multiple Columns to Create new Column.
24:14 - Rearranging columns
28:06 - Saving our Data (CSV, Excel, TXT, etc.)
31:47 - Filtering Data (based on multiple conditions)
35:40 - Reset Index
37:41 - Regex Filtering (filter based on textual patterns)
43:08 - Conditional Changes
47:57 - Aggregate Statistics using Groupby (Sum, Mean, Counting)
54:53 - Working with large amounts of data (setting chunksize)

-------------------------
If you are curious to learn how I make my tutorials, check out this video: https://youtu.be/LEO4igyXbLs

*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

#KGMIT #Keith Galli #MIT #Python 3 #Python Programming #Data Science #Python Pandas #Pandas #Pandas Library #pd #python data science tutorial #Excel #Csv #Reading CSV in Python #Data Science in Python #Python Pandas tutorial #Data analysis in python #how to do data analysis using python #Numpy #Reading excel files with python #sorting data #pandas library tutorial #simple #easy #best #groupby in python pandas #reset index pandas #index python pandas #stats in python #python statistics
- Why Pandas? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Why Pandas?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:00:45 - 00:01:46
- Installing Pandas - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Installing Pandas

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:01:46 - 00:02:03
- Getting the data used in this video - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Getting the data used in this video

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:02:03 - 00:03:50
- Loading the data into Pandas (CSVs, Excel, TXTs, etc.) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Loading the data into Pandas (CSVs, Excel, TXTs, etc.)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:03:50 - 00:08:49
#####--- adding  (10 not included) columns to new column Total ---####li_columns = df.columns.tolist()df['Total'] = 0 - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

#####--- adding (10 not included) columns to new column Total ---####li_columns = df.columns.tolist()df['Total'] = 0

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:04:10 - 00:04:10
for element in li_columns[]:
 #From HP to Speeddf['Total'] = df['Total'] + df[element]print(df.head(5)) #Print first 5 rows - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

for element in li_columns[]: #From HP to Speeddf['Total'] = df['Total'] + df[element]print(df.head(5)) #Print first 5 rows

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:04:10 - 01:00:27
Just wanna make sure that this one doesn’t go ignored haha @ - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Just wanna make sure that this one doesn’t go ignored haha @

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:06:30 - 01:00:27
- Reading Data (Getting Rows, Columns, Cells, Headers, etc.) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Reading Data (Getting Rows, Columns, Cells, Headers, etc.)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:08:49 - 00:13:10
, why the double third bracket in [[ 'Name' , 'Type 1' , 'HP']] ? Why not just [ 'Name' , 'Type 1' , 'HP'] ? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

, why the double third bracket in [[ 'Name' , 'Type 1' , 'HP']] ? Why not just [ 'Name' , 'Type 1' , 'HP'] ?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:11:15 - 01:00:27
- Iterate through each Row - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Iterate through each Row

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:13:10 - 00:14:11
For , refer https://stackoverflow.com/questions/16476924/how-to-iterate-over-rows-in-a-dataframe-in-pandas - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

For , refer https://stackoverflow.com/questions/16476924/how-to-iterate-over-rows-in-a-dataframe-in-pandas

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:13:16 - 01:00:27
usefor index, row in df.iterrows():print(index, row['Name']) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

usefor index, row in df.iterrows():print(index, row['Name'])

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:14:10 - 01:00:27
- Getting rows based on a specific condition - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Getting rows based on a specific condition

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:14:11 - 00:15:47
In , what if i want to select both 'Grass' and 'Fire', could you show me how can I do that? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

In , what if i want to select both 'Grass' and 'Fire', could you show me how can I do that?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:15:26 - 01:00:27
- High Level description of your data (min, max, mean, std dev, etc.) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- High Level description of your data (min, max, mean, std dev, etc.)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:15:47 - 00:16:24
- my bookmark so I can return with the stats function - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- my bookmark so I can return with the stats function

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:15:53 - 01:00:27
- Sorting Values (Alphabetically, Numerically) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Sorting Values (Alphabetically, Numerically)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:16:24 - 00:18:19
- Making Changes to the DataFrame - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Making Changes to the DataFrame

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:18:19 - 00:18:56
- Adding a column - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Adding a column

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:18:56 - 00:21:22
If You have too many columns to add, as he has at  and even more, use this: - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

If You have too many columns to add, as he has at and even more, use this:

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:19:33 - 00:04:10
- Deleting a column - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Deleting a column

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:21:22 - 00:22:14
at  you could do like this :df.drop(columns=['Total'], inplace=True) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

at you could do like this :df.drop(columns=['Total'], inplace=True)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:22:00 - 01:00:27
- Summing Multiple Columns to Create new Column. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Summing Multiple Columns to Create new Column.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:22:14 - 00:24:14
Hi Keith,Amazing work. thanks for the Tutorial,however I got an error after i execute the .iloc method at  in the video.Can you pls explain how to get rid of the error "Indexing error:Too many Indexers".Thanks in advance - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Hi Keith,Amazing work. thanks for the Tutorial,however I got an error after i execute the .iloc method at in the video.Can you pls explain how to get rid of the error "Indexing error:Too many Indexers".Thanks in advance

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:23:24 - 01:00:27
at  when i put pokemon['Total'] = df.iloc[:, 4:10].sum(axis=1),  bulbasaur's total is 591. but when i put pokemon['Total'] = df.iloc[:, 4:5].sum(axis=1), the total is correct at 318. What happened here? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

at when i put pokemon['Total'] = df.iloc[:, 4:10].sum(axis=1), bulbasaur's total is 591. but when i put pokemon['Total'] = df.iloc[:, 4:5].sum(axis=1), the total is correct at 318. What happened here?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:23:50 - 01:00:27
- Rearranging columns - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Rearranging columns

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:24:14 - 00:28:06
Best Pandas tutorial on YouTube, especially - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Best Pandas tutorial on YouTube, especially

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:24:25 - 01:00:27
XD *SPAM IT* - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

XD *SPAM IT*

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:24:28 - 01:00:27
to 24:33 is essential. The other stuff is good too. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

to 24:33 is essential. The other stuff is good too.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:24:28 - 01:00:27
Hi Keith, this is a very helpful introductory course for pandas and thanks a lot! I see a very interesting edit to your video though - at  there is `cols = list(df.columns.values)` but a second later at 26:40 it became `cols = list(df.columns)`. What happened here? Why did you remove the `.values`? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Hi Keith, this is a very helpful introductory course for pandas and thanks a lot! I see a very interesting edit to your video though - at there is `cols = list(df.columns.values)` but a second later at 26:40 it became `cols = list(df.columns)`. What happened here? Why did you remove the `.values`?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:26:39 - 01:00:27
The correct or a better approach for mistake in . Will be to use cols[-1:] - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

The correct or a better approach for mistake in . Will be to use cols[-1:]

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:26:49 - 01:00:27
Hey, thank You very much for this tutorial, but I'm wondering what happens with "Total" column on  ? Numbers became more than twice bigger. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Hey, thank You very much for this tutorial, but I'm wondering what happens with "Total" column on ? Numbers became more than twice bigger.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:27:09 - 01:00:27
why the total changes? the first row was 318, but in this moment change to 864 - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

why the total changes? the first row was 318, but in this moment change to 864

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:27:12 - 01:00:27
It seems that the dataframe got scrambled up a bit there, most likely from having the cell running multiple times. Even when there was an error message, it appears that either the Total or the Legendary column was moved to the left of HP. Upon running the cell again (with the corrected version?) it calculated a new Total adding the previous values and generating corrupted results. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

It seems that the dataframe got scrambled up a bit there, most likely from having the cell running multiple times. Even when there was an error message, it appears that either the Total or the Legendary column was moved to the left of HP. Upon running the cell again (with the corrected version?) it calculated a new Total adding the previous values and generating corrupted results.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:27:15 - 01:00:27
I really appreciate your work, thank you so much :) - bookmark - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

I really appreciate your work, thank you so much :) - bookmark

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:27:21 - 01:00:27
Very nice tutorial. Might be worth it to demo how to reorder columns by using indices as you allude to starting around .  That would be something a newbie might like to see illustrated - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Very nice tutorial. Might be worth it to demo how to reorder columns by using indices as you allude to starting around . That would be something a newbie might like to see illustrated

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:27:50 - 01:00:27
- Saving our Data (CSV, Excel, TXT, etc.) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Saving our Data (CSV, Excel, TXT, etc.)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:28:06 - 00:31:47
the totals are all messed up and way too high though - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

the totals are all messed up and way too high though

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:28:10 - 01:00:27
there was a bug, each time you run your code the columns will be in different indexes and that because you set the rearrange line to the same variable which is "df", I solved this problem by setting a new variable to the rearrange line then save it to that new variable, each time I run the code now the result is the same. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

there was a bug, each time you run your code the columns will be in different indexes and that because you set the rearrange line to the same variable which is "df", I solved this problem by setting a new variable to the rearrange line then save it to that new variable, each time I run the code now the result is the same.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:29:00 - 01:00:27
is where he's getting texts from actual pandas - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

is where he's getting texts from actual pandas

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:29:19 - 01:00:27
@Kevin - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

@Kevin

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:29:30 - 01:00:27
- Filtering Data (based on multiple conditions) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Filtering Data (based on multiple conditions)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:31:47 - 00:35:40
You don't have to use 'loc' for filtering - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

You don't have to use 'loc' for filtering

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:32:07 - 01:00:27
When I try to do the operation at  I get a warning "future warning:element wise comparison failed, returning scalar instead, but in the future will perform element wise comparison" - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

When I try to do the operation at I get a warning "future warning:element wise comparison failed, returning scalar instead, but in the future will perform element wise comparison"

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:32:58 - 01:00:27
Hi Keith! thanks for this helpful video. How do you do the filtering data with different conditions (i.e. at  min in the video) for a data frame without headers and just based on position. I tried your example with iloc and it doesn't work. I searched for the solution but was not successful. I hope you see my comment and answer it pls! Thanks in advance for your help. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Hi Keith! thanks for this helpful video. How do you do the filtering data with different conditions (i.e. at min in the video) for a data frame without headers and just based on position. I tried your example with iloc and it doesn't work. I searched for the solution but was not successful. I hope you see my comment and answer it pls! Thanks in advance for your help.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:33:18 - 01:00:27
I think Pandas and NumPy (When using arrays) implement a "C" language style syntax when doing boolean and a few data structures. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

I think Pandas and NumPy (When using arrays) implement a "C" language style syntax when doing boolean and a few data structures.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:33:28 - 01:00:27
I tried to do it with and operator but I got an Error.I tried it with & operator but I got a KeyError: FalseI did it in the PyCharm. Therefore, should I install Anaconda and use it instead of PyCharm? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

I tried to do it with and operator but I got an Error.I tried it with & operator but I got a KeyError: FalseI did it in the PyCharm. Therefore, should I install Anaconda and use it instead of PyCharm?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:33:31 - 01:00:27
- Reset Index - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Reset Index

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:35:40 - 00:37:41
At the "Reset index" part in  , even after applying two methods -1) new_df = new_df.reset_index(drop=True)new_df2)new_df.reset_index(drop=True,inplace=True)new_dfMy old index column was still in the data set.So i just normally deleted that column by ' - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

At the "Reset index" part in , even after applying two methods -1) new_df = new_df.reset_index(drop=True)new_df2)new_df.reset_index(drop=True,inplace=True)new_dfMy old index column was still in the data set.So i just normally deleted that column by '

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:37:04 - 01:00:27
- Regex Filtering (filter based on textual patterns) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Regex Filtering (filter based on textual patterns)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:37:41 - 00:43:08
i was looking for .str.contains('*') filterthanks - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

i was looking for .str.contains('*') filterthanks

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:39:27 - 01:00:27
I have one comment though. When you run (at ) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

I have one comment though. When you run (at )

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:40:00 - 01:00:27
At  flags = re.I parameter in str.contains function didn't work.  Looked it up, and it should read flags = re.IGNORECASE.  Possibly this is due to a version change? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

At flags = re.I parameter in str.contains function didn't work. Looked it up, and it should read flags = re.IGNORECASE. Possibly this is due to a version change?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:41:00 - 01:00:27
just one correction: at  'pi[a-z]*'  the star means zero or more, instead of 'one or more' as said by Keith. - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

just one correction: at 'pi[a-z]*' the star means zero or more, instead of 'one or more' as said by Keith.

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:42:18 - 01:00:27
At , the following may be simpler:  new_df = df.loc[df['Name'].str.contains('^pi', regex=True, flags=re.I)] - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

At , the following may be simpler: new_df = df.loc[df['Name'].str.contains('^pi', regex=True, flags=re.I)]

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:42:33 - 01:00:27
- Conditional Changes - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Conditional Changes

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:43:08 - 00:47:57
' after 'Fire' at  ? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

' after 'Fire' at ?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:44:00 - 01:00:27
When i do multiple filtering  get this error: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead. Any suggestion ? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

When i do multiple filtering get this error: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead. Any suggestion ?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:47:33 - 01:00:27
- Aggregate Statistics using Groupby (Sum, Mean, Counting) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Aggregate Statistics using Groupby (Sum, Mean, Counting)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:47:57 - 00:54:53
at  what happens with the "Type 1" column label? I tried it here with my own data set and it seems to get lost as a label that I can query for.. How do I group exactly like this but keep the column label as is? - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

at what happens with the "Type 1" column label? I tried it here with my own data set and it seems to get lost as a label that I can query for.. How do I group exactly like this but keep the column label as is?

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:49:20 - 01:00:27
At  , how can I plot the data grouped by types , where the type with the highest total is shown from the left to right? Without losing the mapping between the type and its corresponding total value? In my barplot graph, the order doesn´t make sense when I add:  .sort_values("Total", ascending = False). - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

At , how can I plot the data grouped by types , where the type with the highest total is shown from the left to right? Without losing the mapping between the type and its corresponding total value? In my barplot graph, the order doesn´t make sense when I add: .sort_values("Total", ascending = False).

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:51:00 - 01:00:27
You can also just write the code: df.groupby(['Type 1']).count()['Name'] - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

You can also just write the code: df.groupby(['Type 1']).count()['Name']

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:52:49 - 01:00:27
you can use .size() to get the count of each Pokemon type instead of adding a new column.It would look like this:df.groupby(['Type 1']).size() - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

you can use .size() to get the count of each Pokemon type instead of adding a new column.It would look like this:df.groupby(['Type 1']).size()

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:53:30 - 01:00:27
- Working with large amounts of data (setting chunksize) - Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

- Working with large amounts of data (setting chunksize)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
2018年10月26日 
00:54:53 - 01:00:27

Keith Galli

※本サイトに掲載されているチャンネル情報や動画情報はYouTube公式のAPIを使って取得・表示しています。

Timetable

動画タイムテーブル

動画数:84件

- Video Overview & Reference Material - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Video Overview & Reference Material

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:00:00 - 00:03:05
-  Data & Code Setup - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Data & Code Setup

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:03:05 - 00:05:04
- Task #0: Configure LLM to use with Python (OpenAI API) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #0: Configure LLM to use with Python (OpenAI API)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:05:04 - 00:20:10
- Task #0 (continued): LLM Configuration with Open-Source Model (LLama 2 via Ollama) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #0 (continued): LLM Configuration with Open-Source Model (LLama 2 via Ollama)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:20:10 - 00:27:39
- Task #1: Use LLM to Parse Simple Sentence Examples - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #1: Use LLM to Parse Simple Sentence Examples

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:27:39 - 00:41:22
- Sub-task #1: Convert string to Python Object - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Sub-task #1: Convert string to Python Object

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:41:22 - 00:44:29
- Task #1 (continued): Use Open-Source LLM to Parse Sentence Examples w/ LangChain - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #1 (continued): Use Open-Source LLM to Parse Sentence Examples w/ LangChain

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:44:29 - 00:56:24
- Quick note on a benefit of using LangChain (easily switching between models) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Quick note on a benefit of using LangChain (easily switching between models)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:56:24 - 00:58:06
- Task #2 (warmup): Grab Apprenticeship Agreement rows from Dataframe - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #2 (warmup): Grab Apprenticeship Agreement rows from Dataframe

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:58:06 - 01:06:22
- Task #2: Connect Pages that Belong to the Same Documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #2: Connect Pages that Belong to the Same Documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
01:06:22 - 01:56:36
Fantastic real world problem as a lot of your other videos. I've got to say that all models on Ollama absolutely stink in comparison to OpenAI. However I have been using a preprocessing text function I created for using in a news article project I'm working on using Spacy. I have been able to pass the transcription_text's through my function with some minor tweaking and have been able to recreate what the LLM's are doing just through code, by using the doc.ents functionality. Only  through the video at the moment and perhaps you use something similar later on, but  Spacy has been a bit of a godsend if you don't/can't pay for OpenAI - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

Fantastic real world problem as a lot of your other videos. I've got to say that all models on Ollama absolutely stink in comparison to OpenAI. However I have been using a preprocessing text function I created for using in a news article project I'm working on using Spacy. I have been able to pass the transcription_text's through my function with some minor tweaking and have been able to recreate what the LLM's are doing just through code, by using the doc.ents functionality. Only through the video at the moment and perhaps you use something similar later on, but Spacy has been a bit of a godsend if you don't/can't pay for OpenAI

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日  @MaxwellSmi41483 様 
01:27:00 - 02:39:33
- Task #3: Parse out values from merged documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #3: Parse out values from merged documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
01:56:36 - 02:12:44
- Task #4 (setup): Analyze Results - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #4 (setup): Analyze Results

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:12:44 - 02:17:52
- Fixing up our results from task #3 quickly - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Fixing up our results from task #3 quickly

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:17:52 - 02:20:41
- Task #4: Find the average age of apprentices in our merged contract documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #4: Find the average age of apprentices in our merged contract documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:20:41 - 02:30:59
- Other analysis, wlho had the most apprentices? - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Other analysis, wlho had the most apprentices?

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:30:59 - 02:39:33
- Introduction - How to make your GitHub more impressive to Employers! (5 simple tips)

- Introduction

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:00:00 - 00:01:50
- Tip 1: Show Private Repository Activity - How to make your GitHub more impressive to Employers! (5 simple tips)

- Tip 1: Show Private Repository Activity

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:01:50 - 00:02:57
- Tip 2: Highlight best work using pins - How to make your GitHub more impressive to Employers! (5 simple tips)

- Tip 2: Highlight best work using pins

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:02:57 - 00:04:13
- Tip 3: Create a Profile README - How to make your GitHub more impressive to Employers! (5 simple tips)

- Tip 3: Create a Profile README

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:04:13 - 00:11:32
- Tip 4: Fill in all Profile Details - How to make your GitHub more impressive to Employers! (5 simple tips)

- Tip 4: Fill in all Profile Details

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:11:32 - 00:13:45
- Tip 5: Fill in READMEs on highlighted repos - How to make your GitHub more impressive to Employers! (5 simple tips)

- Tip 5: Fill in READMEs on highlighted repos

How to make your GitHub more impressive to Employers! (5 simple tips)
2024年02月27日 
00:13:45 - 00:19:01
- Overview & Getting Started - Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)

- Overview & Getting Started

Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)
2023年12月27日 
00:00:00 - 00:00:50
- 1. Predicting Heart Attack Risk (Easy Problem) - Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)

- 1. Predicting Heart Attack Risk (Easy Problem)

Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)
2023年12月27日 
00:00:50 - 00:06:44
- 2. Data Anonymization (Medium Problem) - Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)

- 2. Data Anonymization (Medium Problem)

Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)
2023年12月27日 
00:06:44 - 00:11:53
- 3.  Dessert Duel (Hard Problem) - Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)

- 3. Dessert Duel (Hard Problem)

Can You Solve These 3 Data Analysis Puzzles? (AnalystBuilder & Python Pandas)
2023年12月27日 
00:11:53 - 00:29:59
- Overview - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Overview

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:00:00 - 00:00:41
- Getting started on the Book Review API - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Getting started on the Book Review API

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:00:41 - 00:02:20
- Set up Airtable as our database & connect to it with Python - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Set up Airtable as our database & connect to it with Python

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:02:20 - 00:10:44
- Implement code to add reviews and view all reviews - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Implement code to add reviews and view all reviews

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:10:44 - 00:31:40
- Adding a POST request to our API - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Adding a POST request to our API

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:31:40 - 00:36:40
- Trying out our new endpoints (using documentation & requests library of Python) - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Trying out our new endpoints (using documentation & requests library of Python)

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:36:40 - 00:41:32
- Commit code to Github & deploy live to Render.com - Python Project: Implement a REST API with Flask & Flasgger Libraries!

- Commit code to Github & deploy live to Render.com

Python Project: Implement a REST API with Flask & Flasgger Libraries!
2023年12月04日 
00:41:32 - 00:50:46
- Video overview - How to create & deploy an API in Python! (with interactive documentation)

- Video overview

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:00:00 - 00:01:18
- What we're building - How to create & deploy an API in Python! (with interactive documentation)

- What we're building

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:01:18 - 00:03:20
- How to get setup with Github template code - How to create & deploy an API in Python! (with interactive documentation)

- How to get setup with Github template code

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:03:20 - 00:07:00
- Taking a look at the Flask, Flasgger Python3 code - How to create & deploy an API in Python! (with interactive documentation)

- Taking a look at the Flask, Flasgger Python3 code

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:07:00 - 00:08:38
- Testing some API requests (GET) locally - How to create & deploy an API in Python! (with interactive documentation)

- Testing some API requests (GET) locally

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:08:38 - 00:13:09
- Building another GET request endpoint (with multiple parameters) - How to create & deploy an API in Python! (with interactive documentation)

- Building another GET request endpoint (with multiple parameters)

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:13:09 - 00:14:34
- Using ChatGPT to help us build another endpoint - How to create & deploy an API in Python! (with interactive documentation)

- Using ChatGPT to help us build another endpoint

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:14:34 - 00:22:43
- Deploying our API to a live public URL endpoint (using render.com) - How to create & deploy an API in Python! (with interactive documentation)

- Deploying our API to a live public URL endpoint (using render.com)

How to create & deploy an API in Python! (with interactive documentation)
2023年11月26日 
00:22:43 - 00:29:27
- Video overview & topics covered - Complete Regular Expressions Tutorial! (with exercises for practice)

- Video overview & topics covered

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:00:00 - 00:01:43
- Basic regex syntax (building up an intuition) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Basic regex syntax (building up an intuition)

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:01:43 - 00:04:23
- Character Sets Overview ([A-Za-z0-9]) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Character Sets Overview ([A-Za-z0-9])

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:04:23 - 00:05:57
- Quantifiers Guide (*, +, ?, {3,5}) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Quantifiers Guide (*, +, ?, {3,5})

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:05:57 - 00:09:30
- Guided Exercise: Find all words that don't use vowels - Complete Regular Expressions Tutorial! (with exercises for practice)

- Guided Exercise: Find all words that don't use vowels

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:09:30 - 00:11:08
Linguistically speaking, [y] can be a vowel, especially in words like "crypt". Pedantry of course, since it could just be added into the regex if needed. 🤓 - Complete Regular Expressions Tutorial! (with exercises for practice)

Linguistically speaking, [y] can be a vowel, especially in words like "crypt". Pedantry of course, since it could just be added into the regex if needed. 🤓

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日  Anon Viewer 様 
00:10:50 - 00:36:40
- Helpful cheat sheet to remember regex syntax in the real-world - Complete Regular Expressions Tutorial! (with exercises for practice)

- Helpful cheat sheet to remember regex syntax in the real-world

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:11:08 - 00:12:47
- Matching words/patterns of a specific length ({3,5}) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Matching words/patterns of a specific length ({3,5})

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:12:47 - 00:14:58
- OR operator overview - Complete Regular Expressions Tutorial! (with exercises for practice)

- OR operator overview

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:14:58 - 00:17:14
- Guided Exercise: Match valid sentences (starts with capital letter, ends with period) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Guided Exercise: Match valid sentences (starts with capital letter, ends with period)

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:17:14 - 00:21:18
- Character classes overview (\w, \b, \d, \s) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Character classes overview (\w, \b, \d, \s)

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:21:18 - 00:23:13
- Escaping Characters - Complete Regular Expressions Tutorial! (with exercises for practice)

- Escaping Characters

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:23:13 - 00:25:02
- Practice Exercise #1: Write a regular expression to match meme text format - Complete Regular Expressions Tutorial! (with exercises for practice)

- Practice Exercise #1: Write a regular expression to match meme text format

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:25:02 - 00:30:39
- Practice Exercise #2: Write a regular expression to match a specific date format - Complete Regular Expressions Tutorial! (with exercises for practice)

- Practice Exercise #2: Write a regular expression to match a specific date format

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:30:39 - 00:39:03
Might not really be up to regex to do data validation. There are better tools for that. 🧰In fact, integrating these into data workflows would be a good follow-up video for the future. ▶ - Complete Regular Expressions Tutorial! (with exercises for practice)

Might not really be up to regex to do data validation. There are better tools for that. 🧰In fact, integrating these into data workflows would be a good follow-up video for the future. ▶

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日  Anon Viewer 様 
00:36:40 - 01:19:21
- Groups overview - Complete Regular Expressions Tutorial! (with exercises for practice)

- Groups overview

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:39:03 - 00:50:16
You could definitely get everything if you add an extra parenthesis around the thing you want to get in this case (([a-z][A-Z])+[a-z]?)@(\w+\.\w+) - Complete Regular Expressions Tutorial! (with exercises for practice)

You could definitely get everything if you add an extra parenthesis around the thing you want to get in this case (([a-z][A-Z])+[a-z]?)@(\w+\.\w+)

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日  Dendrocnide Moroides 様 
00:49:02 - 01:19:21
- Lookahead & Lookbehind Assertions - Complete Regular Expressions Tutorial! (with exercises for practice)

- Lookahead & Lookbehind Assertions

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
00:50:16 - 01:00:18
- Practice Exercise #3: Detect if same word pops up multiple times in a sentence - Complete Regular Expressions Tutorial! (with exercises for practice)

- Practice Exercise #3: Detect if same word pops up multiple times in a sentence

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
01:00:18 - 01:06:04
- Practice Exercise #4: Password matching with rules - Complete Regular Expressions Tutorial! (with exercises for practice)

- Practice Exercise #4: Password matching with rules

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
01:06:04 - 01:16:16
- Some final recommendations! (additional practice, chatgpt, etc.) - Complete Regular Expressions Tutorial! (with exercises for practice)

- Some final recommendations! (additional practice, chatgpt, etc.)

Complete Regular Expressions Tutorial! (with exercises for practice)
2023年04月13日 
01:16:16 - 01:19:21
- Video overview & format - Full Data Science Mock Interview! (featuring Kylie Ying)

- Video overview & format

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:00:00 - 00:03:38
- Introductory Behavioral questions | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- Introductory Behavioral questions | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:03:38 - 00:09:11
- Social media platform bot issue task overview | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- Social media platform bot issue task overview | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:09:11 - 00:16:51
- What are some features we should investigate regarding the bot issue? | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- What are some features we should investigate regarding the bot issue? | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:16:51 - 00:26:27
- Classification model implementation details (using feature vectors) | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- Classification model implementation details (using feature vectors) | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:26:27 - 00:43:03
- What would a dataset to train models to detect bots look like? How would you approach collecting this data? | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- What would a dataset to train models to detect bots look like? How would you approach collecting this data? | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:43:03 - 00:53:03
- Technical implementation details (python libraries, cloud services, etc) | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- Technical implementation details (python libraries, cloud services, etc) | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:53:03 - 00:57:26
- Any questions for me? | Data science interview - Full Data Science Mock Interview! (featuring Kylie Ying)

- Any questions for me? | Data science interview

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
00:57:26 - 01:05:07
- Post-interview breakdown & analysis - Full Data Science Mock Interview! (featuring Kylie Ying)

- Post-interview breakdown & analysis

Full Data Science Mock Interview! (featuring Kylie Ying)
2023年01月09日 
01:05:07 - 01:27:34
- Video Introduction - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Video Introduction

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:00:00 - 00:01:19
- How podcasts work (RSS feeds overview) - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- How podcasts work (RSS feeds overview)

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:01:19 - 00:05:11
- How can we utilize the XML webpages? (breakdown of RSS feed information & how we’ll use it to create a smart program) - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- How can we utilize the XML webpages? (breakdown of RSS feed information & how we’ll use it to create a smart program)

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:05:11 - 00:07:47
- Accessing this project on GitHub - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Accessing this project on GitHub

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:07:47 - 00:09:22
-Writing Python code to download podcasts locally (requests & beautifulsoup libraries) - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

-Writing Python code to download podcasts locally (requests & beautifulsoup libraries)

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:09:22 - 00:18:10
- Modify our script to be able to download many podcasts - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Modify our script to be able to download many podcasts

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:18:10 - 00:22:51
- Building in smart search capabilities to grab podcasts we’ll find most interesting! - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Building in smart search capabilities to grab podcasts we’ll find most interesting!

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:22:51 - 00:31:00
- Using the AssemblyAI API to transcribe the podcasts we’ve downloaded - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Using the AssemblyAI API to transcribe the podcasts we’ve downloaded

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
00:31:00 - 01:06:08
- Cleaning our code with functions & classes and putting everything into Python scripts. - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Cleaning our code with functions & classes and putting everything into Python scripts.

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
01:06:08 - 01:18:09
- Portfolio project extension ideas! (Spotify API, NLP semantic search) - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Portfolio project extension ideas! (Spotify API, NLP semantic search)

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
01:18:09 - 01:19:56
- Smash like & subscribe pretty please :) - Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.

- Smash like & subscribe pretty please :)

Full Python Portfolio Project! Create a smart program to download & transcribe top podcasts.
2022年11月23日 
01:19:56 - 01:20:39
- Intro & Video Overview - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Intro & Video Overview

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:00:00 - 00:00:46
- Check out this Video’s Sponsor, Brilliant! - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Check out this Video’s Sponsor, Brilliant!

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:00:46 - 00:03:10
- Coding #1 (Microsoft, Easy) - Finding Updated Records - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #1 (Microsoft, Easy) - Finding Updated Records

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:03:10 - 00:10:36
- Coding #2 (Airbnb, Easy) - Number of Bathrooms and Bedrooms - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #2 (Airbnb, Easy) - Number of Bathrooms and Bedrooms

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:10:36 - 00:16:38
- Coding #3 (Google, Medium) - Counting Instances in Text - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #3 (Google, Medium) - Counting Instances in Text

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:16:38 - 00:28:23
I know it's more a reference to the stock market terms, but I can't stop thinking of Fallout: New Vegas. - Solving Real-World Data Science Interview Questions! (with Python Pandas)

I know it's more a reference to the stock market terms, but I can't stop thinking of Fallout: New Vegas.

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:17:20 - 01:11:00
- Coding #4 (Meta/Facebook, Medium) - Customer Revenue in March - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #4 (Meta/Facebook, Medium) - Customer Revenue in March

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:28:23 - 00:36:51
That first one and others are SQL problems converted to pandas. I suppose that's a decent way to get basic pd questions. () - Solving Real-World Data Science Interview Questions! (with Python Pandas)

That first one and others are SQL problems converted to pandas. I suppose that's a decent way to get basic pd questions. ()

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:28:48 - 00:17:20
- Coding #5 (Amazon, Hard) - Monthly Percentage Difference - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #5 (Amazon, Hard) - Monthly Percentage Difference

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:36:51 - 00:56:38
AtI work for Amazon's RPA team, trying to make a career in data science. Last month I was appearing for an IJP and got the same question in SQL coding round.Thanks for making this Keith. Keep them coming. - Solving Real-World Data Science Interview Questions! (with Python Pandas)

AtI work for Amazon's RPA team, trying to make a career in data science. Last month I was appearing for an IJP and got the same question in SQL coding round.Thanks for making this Keith. Keep them coming.

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:37:48 - 01:47:50
- Coding #6 (Microsoft, Hard) - Premium vs Freemium - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Coding #6 (Microsoft, Hard) - Premium vs Freemium

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
00:56:38 - 01:10:28
- Non-Coding #1 (Visa, Easy) - Credit Card Activity - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Non-Coding #1 (Visa, Easy) - Credit Card Activity

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:10:28 - 01:13:33
If you have the locations that's just a simple matter of putting it on a map and seeing where it clusters the most. - Solving Real-World Data Science Interview Questions! (with Python Pandas)

If you have the locations that's just a simple matter of putting it on a map and seeing where it clusters the most.

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:11:00 - 01:28:00
- Non-Coding #2 (IBM, Easy) - Outliers Detection - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Non-Coding #2 (IBM, Easy) - Outliers Detection

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:13:33 - 01:16:46
- Non-Coding #3 (Google, Medium) - Probability of Having a Sister - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Non-Coding #3 (Google, Medium) - Probability of Having a Sister

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:16:46 - 01:27:19
- Non-Coding #4 (Uber, Medium) - Uber Black Rides - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Non-Coding #4 (Uber, Medium) - Uber Black Rides

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:27:19 - 01:36:57
Context, context, context. Was that the only reduction? - Solving Real-World Data Science Interview Questions! (with Python Pandas)

Context, context, context. Was that the only reduction?

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:28:00 - 01:47:50
- Non-Coding #5 (Capital One, Hard) - Terabyte of Data - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Non-Coding #5 (Capital One, Hard) - Terabyte of Data

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:36:57 - 01:46:41
- Video Conclusion & Recap - Solving Real-World Data Science Interview Questions! (with Python Pandas)

- Video Conclusion & Recap

Solving Real-World Data Science Interview Questions! (with Python Pandas)
2022年07月26日 
01:46:41 - 01:47:50