- Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

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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

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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)

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- 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

Keith Galli

🎉 170,000 人達成! 🎉

【予測】20万人まであと260日(2023年6月24日)

チャンネル登録 RSS
Recent MIT Graduate. I make educational videos on Computer Science, Programming, Board Games, and more!

I found online videos to be extremely helpful as I progressed through the educational system growing up so I decided to make a channel of my own. Let me know what I should make next!

-Keith :)

Timetable

動画タイムテーブル

動画数:19件

- 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
- Introduction & video overview - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- Introduction & video overview

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:00:00 - 00:00:25
- Shoutout to this video’s sponsor, Brilliant.org! - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- Shoutout to this video’s sponsor, Brilliant.org!

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:00:25 - 00:02:11
- 1. Running terminal commands such as “pip” directly in a notebook - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- 1. Running terminal commands such as “pip” directly in a notebook

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:02:11 - 00:05:17
- Magic lines in Jupyter - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- Magic lines in Jupyter

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:05:17 - 00:06:11
- 2. Shortcuts that you need to know for Jupyter! - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- 2. Shortcuts that you need to know for Jupyter!

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:06:11 - 00:09:25
Pretty unnecessary to write all these out. Just go to the “Help” menu, and select “Keyboard Shortcuts”. They’re all there—and more. - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

Pretty unnecessary to write all these out. Just go to the “Help” menu, and select “Keyboard Shortcuts”. They’re all there—and more.

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:07:26 - 00:23:17
- 3. Changing default Pandas options to improve results display - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- 3. Changing default Pandas options to improve results display

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:09:25 - 00:14:00
- 4. Setting up notifications for when a cell finishes execution - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- 4. Setting up notifications for when a cell finishes execution

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:14:00 - 00:18:08
- 5. Creating slideshows from a IPython notebook! - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- 5. Creating slideshows from a IPython notebook!

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:18:08 - 00:23:00
- Conclusion (and link to bonus tip!) - 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!

- Conclusion (and link to bonus tip!)

5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!
2022年06月01日
00:23:00 - 00:23:17
- Intro - Solving real world data science problems with Python! (computer vision edition)

- Intro

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:00:00 - 00:00:40
- Video overview (what we’ll be working on) - Solving real world data science problems with Python! (computer vision edition)

- Video overview (what we’ll be working on)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:00:40 - 00:01:53
- Code setup (GitHub repo & HP challenge link) - Solving real world data science problems with Python! (computer vision edition)

- Code setup (GitHub repo & HP challenge link)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:01:53 - 00:05:11
- Exploring the dataset that we’ll be using - Solving real world data science problems with Python! (computer vision edition)

- Exploring the dataset that we’ll be using

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:05:11 - 00:06:20
- Reviewing template code (starter-code.ipynb) - Solving real world data science problems with Python! (computer vision edition)

- Reviewing template code (starter-code.ipynb)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:06:20 - 00:08:53
- Installing necessary Python libraries (opencv-python, tensorflow) - Solving real world data science problems with Python! (computer vision edition)

- Installing necessary Python libraries (opencv-python, tensorflow)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:08:53 - 00:10:31
- Reviewing template code (part 2) - Solving real world data science problems with Python! (computer vision edition)

- Reviewing template code (part 2)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:10:31 - 00:11:03
- How we load in the dataset (ImageDataGenerator, flow_from_directory) - Solving real world data science problems with Python! (computer vision edition)

- How we load in the dataset (ImageDataGenerator, flow_from_directory)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:11:03 - 00:14:33
- Building our first classifier (convolutional neural net - CNN) - Solving real world data science problems with Python! (computer vision edition)

- Building our first classifier (convolutional neural net - CNN)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:14:33 - 00:25:19
Buy more GPUs. - Solving real world data science problems with Python! (computer vision edition)

Buy more GPUs.

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:21:31 - 01:21:38
- Methods to improve neural network performance (MaxPooling, dropout, network architecture) - Solving real world data science problems with Python! (computer vision edition)

- Methods to improve neural network performance (MaxPooling, dropout, network architecture)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:25:19 - 00:29:30
- Quick discussion about importance of precision & recall versus accuracy - Solving real world data science problems with Python! (computer vision edition)

- Quick discussion about importance of precision & recall versus accuracy

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:29:30 - 00:32:35
- Data augmentation & preprocessing (another way to improve performance) - Solving real world data science problems with Python! (computer vision edition)

- Data augmentation & preprocessing (another way to improve performance)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:32:35 - 00:47:15
- Programmatically finding the best neural network architectures (Keras Tuner) - Solving real world data science problems with Python! (computer vision edition)

- Programmatically finding the best neural network architectures (Keras Tuner)

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
00:47:15 - 01:20:00
- Video recap & conclusion - Solving real world data science problems with Python! (computer vision edition)

- Video recap & conclusion

Solving real world data science problems with Python! (computer vision edition)
2022年05月11日
01:20:00 - 01:21:38
- Announcements! - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Announcements!

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:00:00 - 00:01:12
- Video overview & timeline - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Video overview & timeline

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:01:12 - 00:03:06
- Bag of words (BOW) overview - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Bag of words (BOW) overview

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:03:06 - 00:04:42
- Bag of words example code! (sklearn | CountVectorizer, fit_transform) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Bag of words example code! (sklearn | CountVectorizer, fit_transform)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:04:42 - 00:11:20
- Building a text classification model using bag-of-words (SVM) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Building a text classification model using bag-of-words (SVM)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:11:20 - 00:14:07
keith enum 😂👌 - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

keith enum 😂👌

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:11:57 - 01:37:46
- Predicting new utterances classes using our model (transform) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Predicting new utterances classes using our model (transform)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:14:07 - 00:16:02
If anyone else is getting "CLOTHING" here, try creating your vectorizer like this:vectorizer = CountVectorizer(stop_words=["the"]) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

If anyone else is getting "CLOTHING" here, try creating your vectorizer like this:vectorizer = CountVectorizer(stop_words=["the"])

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:15:01 - 01:37:46
- Unigram, bigram, ngrams (using consecutive words in your model) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Unigram, bigram, ngrams (using consecutive words in your model)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:16:02 - 00:19:28
- Word vectors overview - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Word vectors overview

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:19:28 - 00:23:27
- Word vectors example code! (Using spaCy library) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Word vectors example code! (Using spaCy library)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:23:27 - 00:28:10
- Building a text classification model using word vectors - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Building a text classification model using word vectors

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:28:10 - 00:34:04
- Predicting new utterances using our model - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Predicting new utterances using our model

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:34:04 - 00:40:42
"I went to the bank and wrote a check" is an incorrect English sentence.It should have been "I went to the bank and wrote a cheque" - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

"I went to the bank and wrote a check" is an incorrect English sentence.It should have been "I went to the bank and wrote a cheque"

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:39:52 - 01:37:46
- Regexes (pattern matching) in Python. - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Regexes (pattern matching) in Python.

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:40:42 - 00:52:30
- Stemming/Lemmatization in Python (text normalization w/ NLTK library) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Stemming/Lemmatization in Python (text normalization w/ NLTK library)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
00:52:30 - 01:01:17
- Stopwords Removal (removing most common words from sentences) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Stopwords Removal (removing most common words from sentences)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:01:17 - 01:05:56
- Various other techniques (spell correction, sentiment analysis, part-of-speech tagging). - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Various other techniques (spell correction, sentiment analysis, part-of-speech tagging).

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:05:56 - 01:12:45
- Recurrent Neural Networks (RNNs) for text classification - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Recurrent Neural Networks (RNNs) for text classification

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:12:45 - 01:17:00
- Transformer architectures (attention is all you need) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Transformer architectures (attention is all you need)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:17:00 - 01:21:00
- Writing Python code to leverage transformers (BERT | spacy-transformers) - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Writing Python code to leverage transformers (BERT | spacy-transformers)

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:21:00 - 01:25:00
- Writing a classification model using transformers/BERT - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Writing a classification model using transformers/BERT

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:25:00 - 01:29:37
- Fine-tuning transformer models - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Fine-tuning transformer models

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:29:37 - 01:31:16
- Bring it all together and build a high performance model to classify the categories of Amazon reviews! - Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

- Bring it all together and build a high performance model to classify the categories of Amazon reviews!

Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)
2022年03月17日
01:31:16 - 01:37:46
- Introduction - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Introduction

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:00:00 - 00:01:05
- Getting started w/ Lego analysis project - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Getting started w/ Lego analysis project

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:01:05 - 00:02:33
- How to follow along if you are not a premium DataCamp subscriber (GitHub) - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- How to follow along if you are not a premium DataCamp subscriber (GitHub)

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:02:33 - 00:04:01
- Project tasks overview - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Project tasks overview

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:04:01 - 00:05:40
- Basic exploration of the dataset - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Basic exploration of the dataset

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:05:40 - 00:09:45
- Task #1: What percentage of all licensed sets ever released were Star Wars Themed? - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Task #1: What percentage of all licensed sets ever released were Star Wars Themed?

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:09:45 - 00:24:23
how did you change 'Star wars' text immediately? - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

how did you change 'Star wars' text immediately?

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:16:52 - 00:43:37
- Task #2: In which year was Star Wars not the most popular licensed theme? - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Task #2: In which year was Star Wars not the most popular licensed theme?

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:24:23 - 00:34:00
- Bonus Task: How many unique sets were released each year (1955-2017)? - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Bonus Task: How many unique sets were released each year (1955-2017)?

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:34:00 - 00:42:26
- Conclusion! - Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)

- Conclusion!

Solving real-world data analysis problems with Python Pandas! (Lego dataset analysis)
2022年03月01日
00:42:26 - 00:43:37
- What we’ll be doing in this video - How to Schedule & Automatically Run Python Code!

- What we’ll be doing in this video

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:00:00 - 00:00:56
- Check out Skillshare! (sponsored) - How to Schedule & Automatically Run Python Code!

- Check out Skillshare! (sponsored)

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:00:56 - 00:01:56
).hours.at("").do(func). but this is not working. - How to Schedule & Automatically Run Python Code!

).hours.at("").do(func). but this is not working.

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:01:00 - 01:20:23
- How can we automate scripts? Overview of local, cloud, and serverless methods - How to Schedule & Automatically Run Python Code!

- How can we automate scripts? Overview of local, cloud, and serverless methods

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:01:56 - 00:05:18
- Simple example of local script automation w/ cronjobs & windows task scheduler - How to Schedule & Automatically Run Python Code!

- Simple example of local script automation w/ cronjobs & windows task scheduler

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:05:18 - 00:18:32
- How to schedule code on a cloud machine (use cronjobs) - How to Schedule & Automatically Run Python Code!

- How to schedule code on a cloud machine (use cronjobs)

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:18:32 - 00:18:51
- Simple example of cloud script automation w/ AWS Lambda & Cloudwatch - How to Schedule & Automatically Run Python Code!

- Simple example of cloud script automation w/ AWS Lambda & Cloudwatch

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:18:51 - 00:27:09
- Schedule & automate sending an email locally - How to Schedule & Automatically Run Python Code!

- Schedule & automate sending an email locally

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:27:09 - 00:45:12
- Schedule & automate sending an email on the cloud w/ Lambda & Cloudwatch - How to Schedule & Automatically Run Python Code!

- Schedule & automate sending an email on the cloud w/ Lambda & Cloudwatch

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:45:12 - 00:50:18
- Installing python packages in a serverless environment (zip uploads) - How to Schedule & Automatically Run Python Code!

- Installing python packages in a serverless environment (zip uploads)

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:50:18 - 00:55:50
- Generate & schedule sending analytics reports (locally) - How to Schedule & Automatically Run Python Code!

- Generate & schedule sending analytics reports (locally)

How to Schedule & Automatically Run Python Code!
2020年11月27日
00:55:50 - 01:02:45
- Limitations of lambda (max file upload size) - How to Schedule & Automatically Run Python Code!

- Limitations of lambda (max file upload size)

How to Schedule & Automatically Run Python Code!
2020年11月27日
01:07:03 - 01:09:00
- Generate & schedule sending analytics reports in AWS Lambda - How to Schedule & Automatically Run Python Code!

- Generate & schedule sending analytics reports in AWS Lambda

How to Schedule & Automatically Run Python Code!
2020年11月27日
01:09:00 - 01:18:32
- Final thoughts & video recap! - How to Schedule & Automatically Run Python Code!

- Final thoughts & video recap!

How to Schedule & Automatically Run Python Code!
2020年11月27日
01:18:32 - 01:20:23
- What we will be doing in this video - How to Generate an Analytics Report (pdf) in Python!

- What we will be doing in this video

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:00:00 - 00:01:30
- Check out Skillshare! (sponsored) - How to Generate an Analytics Report (pdf) in Python!

- Check out Skillshare! (sponsored)

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:01:30 - 00:03:00
- Source code & Setup - How to Generate an Analytics Report (pdf) in Python!

- Source code & Setup

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:03:00 - 00:06:37
- Python FPDF library basics - How to Generate an Analytics Report (pdf) in Python!

- Python FPDF library basics

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:06:37 - 00:09:42
- Choosing our paper format (A4, Letter, etc) - How to Generate an Analytics Report (pdf) in Python!

- Choosing our paper format (A4, Letter, etc)

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:09:42 - 00:11:54
- Adding and resizing images in our PDF! - How to Generate an Analytics Report (pdf) in Python!

- Adding and resizing images in our PDF!

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:11:54 - 00:18:52
- Helper method (which states & countries can we plot?) - How to Generate an Analytics Report (pdf) in Python!

- Helper method (which states & countries can we plot?)

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:18:52 - 00:21:48
- Continuing to build out our report (exploring source code) - How to Generate an Analytics Report (pdf) in Python!

- Continuing to build out our report (exploring source code)

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:21:48 - 00:27:17
- Adding additional pages to the report - How to Generate an Analytics Report (pdf) in Python!

- Adding additional pages to the report

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:27:17 - 00:29:09
- Adding a title to our report - How to Generate an Analytics Report (pdf) in Python!

- Adding a title to our report

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:29:09 - 00:32:37
- Adding a professional letterhead to report - How to Generate an Analytics Report (pdf) in Python!

- Adding a professional letterhead to report

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:32:37 - 00:35:00
- Plotting geographic maps with covid-19 data (plotly) - How to Generate an Analytics Report (pdf) in Python!

- Plotting geographic maps with covid-19 data (plotly)

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:35:00 - 00:40:02
- Using datetime library to automatically grab & format yesterday’s date - How to Generate an Analytics Report (pdf) in Python!

- Using datetime library to automatically grab & format yesterday’s date

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:40:02 - 00:43:46
Hey, Keith awesome tutorial! At  to remove leading "0" you can do "%#m/%#d/%y" instead. The "#" will remove leading "0" - How to Generate an Analytics Report (pdf) in Python!

Hey, Keith awesome tutorial! At to remove leading "0" you can do "%#m/%#d/%y" instead. The "#" will remove leading "0"

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:42:23 - 00:49:15
- Finalizing our report - How to Generate an Analytics Report (pdf) in Python!

- Finalizing our report

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:43:46 - 00:46:41
- Where are the colors set? - How to Generate an Analytics Report (pdf) in Python!

- Where are the colors set?

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:46:41 - 00:48:11
- Final thoughts - How to Generate an Analytics Report (pdf) in Python!

- Final thoughts

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:48:11 - 00:49:15
...OK, maybe the second best , right after the time spent yesterday building play dough dinosaurs with my 2 y.o. son after a 1 week business trip. But you were really close from 1st place, I promised :)More seriously, absolutly stunning tutorial! Highly valuable and extremly clearly explained.Thanks for that ! - How to Generate an Analytics Report (pdf) in Python!

...OK, maybe the second best , right after the time spent yesterday building play dough dinosaurs with my 2 y.o. son after a 1 week business trip. But you were really close from 1st place, I promised :)More seriously, absolutly stunning tutorial! Highly valuable and extremly clearly explained.Thanks for that !

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:49:14 - 00:49:15
This were the best  minutes I spent this week... - How to Generate an Analytics Report (pdf) in Python!

This were the best minutes I spent this week...

How to Generate an Analytics Report (pdf) in Python!
2020年11月11日
00:49:14 - 00:49:14