- Where are the colors set?(00:46:41 - 00:48:11) - How to Generate an Analytics Report (pdf) in Python!

- Where are the colors set?(00:46:41 - 00:48:11)
How to Generate an Analytics Report (pdf) in Python!

The first 1000 people to use the link will get a free trial of Skillshare Premium Membership: https://skl.sh/keithgalli10201

In this video we see how we can take visualizations that we plot in python libraries like Matplotlib & Plotly and package them into a nice looking analytics report usi...
The first 1000 people to use the link will get a free trial of Skillshare Premium Membership: https://skl.sh/keithgalli10201

In this video we see how we can take visualizations that we plot in python libraries like Matplotlib & Plotly and package them into a nice looking analytics report using the fpdf library.

Source code: https://github.com/keithgalli/generate-analytics-report
Data: https://github.com/CSSEGISandData/COVID-19
PyFPDF Docs: https://pyfpdf.readthedocs.io/en/latest/
Helpful blog post mentioned: https://towardsdatascience.com/covid-19-map-animation-with-python-in-5-minutes-2d6246c32e54

Thank you to Skillshare for sponsoring this video!

-------------------------
Follow me on social media!
Instagram | https://www.instagram.com/keithgalli/
Twitter |

-------------------------
Video Timeline!
0:00 - What we will be doing in this video
1:30 - Check out Skillshare! (sponsored)
3:00 - Source code & Setup
6:37 - Python FPDF library basics
9:42 - Choosing our paper format (A4, Letter, etc)
11:54 - Adding and resizing images in our PDF!
18:52 - Helper method (which states & countries can we plot?)
21:48 - Continuing to build out our report (exploring source code)
27:17 - Adding additional pages to the report
29:09 - Adding a title to our report
32:37 - Adding a professional letterhead to report
35:00 - Plotting geographic maps with covid-19 data (plotly)
40:02 - Using datetime library to automatically grab & format yesterday’s date
43:46 - Finalizing our report
46:41 - Where are the colors set?
48:11 - Final thoughts

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

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

Join the Python Army to get access to perks!
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Patreon - https://www.patreon.com/keithgalli

*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.

#Keith Galli #python #programming #python 3 #data science #data analysis #python programming #data visualization #analytics report #fpdf #data viz #pandas #numpy #matplotlib #plotly #line charts #bar charts #python project #edit pdf python #business analytics #marketing report #python reporting #python automation #data science projects #choropleth #map chart #geography plot #python plotting #pandas library #real world project #machine learning #plotly express #pdf report #pyfpdf
- 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

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:88件

- Livestream Overview - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Livestream Overview

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:00:00 - 00:04:00
- About the Olympics dataset (source website and how it was scraped) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- About the Olympics dataset (source website and how it was scraped)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:04:00 - 00:09:50
- Cleaning the dataset (getting started with code & data) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Cleaning the dataset (getting started with code & data)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:09:50 - 00:19:26
- What aspects of our data should be cleaned? - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- What aspects of our data should be cleaned?

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:19:26 - 00:29:08
- Get rid of bullet points in Used name column - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Get rid of bullet points in Used name column

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:29:08 - 00:34:08
- How to split Measurements into two separate height/weight numeric columns. - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- How to split Measurements into two separate height/weight numeric columns.

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
00:34:08 - 01:05:00
- Parse out dates from Born & Died columns - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Parse out dates from Born & Died columns

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
01:05:00 - 01:25:43
- Parse out city, region, and country from Born column (working with regular expressions) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Parse out city, region, and country from Born column (working with regular expressions)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
01:25:43 - 01:41:15
- Get rid of the extra columns - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Get rid of the extra columns

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
01:41:15 - 01:46:08
- Next steps (how would we clean the results.csv) - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Next steps (how would we clean the results.csv)

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
01:46:08 - 01:49:41
- Questions & Answers - Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)

- Questions & Answers

Real-World Dataset Cleaning with Python Pandas! (Olympic Athletes Dataset)
2024年04月20日 
01:49:41 - 02:02:26
- Intro & Setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Intro & Setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:00:00 - 00:02:14
great video! however, regarding the usage of the terminal to create directories etc at  , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :) - Solving 100 Python Pandas Problems! (from easy to very difficult)

great video! however, regarding the usage of the terminal to create directories etc at , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :)

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日  @realzeejay 様 
00:00:59 - 05:20:18
- Problems (1-3) Initial pandas setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (1-3) Initial pandas setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:02:14 - 00:04:42
- Problems (4-10) DataFrame operations - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (4-10) DataFrame operations

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:04:42 - 00:04:52
- 4) Create a dataframe from dictionary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 4) Create a dataframe from dictionary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:04:52 - 00:05:24
- 5) Display dataframe summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 5) Display dataframe summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:05:24 - 00:05:41
- 6) First 3 rows of the dataframe - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 6) First 3 rows of the dataframe

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:05:41 - 00:06:02
- 7) Select ‘animal’ and ‘age’ columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 7) Select ‘animal’ and ‘age’ columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:06:02 - 00:07:42
- 8) Data in specific rows and columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 8) Data in specific rows and columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:07:42 - 00:09:06
- 9) Rows with visits greater than 3 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 9) Rows with visits greater than 3

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:09:06 - 00:09:57
- 10) Rows with NaN in age - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 10) Rows with NaN in age

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:09:57 - 00:10:56
- 11) Cats younger than 3 years - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 11) Cats younger than 3 years

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:10:56 - 00:11:35
- 12) Age between 2 and 4 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 12) Age between 2 and 4

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:11:35 - 00:12:45
- 13) Change age in row ‘f’ - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 13) Change age in row ‘f’

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:12:45 - 00:15:56
- 14) Sum of all visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 14) Sum of all visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:15:56 - 00:16:41
- 15) Average age by animal - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 15) Average age by animal

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:16:41 - 00:20:21
I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”}) - Solving 100 Python Pandas Problems! (from easy to very difficult)

I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”})

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日  @AgustinGonzalez-tz3yr 様 
00:19:30 - 05:20:18
- 16) Modify and revert rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 16) Modify and revert rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:20:21 - 00:24:06
- 17) Count by animal type - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 17) Count by animal type

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:24:06 - 00:25:28
- Quick review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Quick review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:25:28 - 00:26:17
- 18) Sort by age and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 18) Sort by age and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:26:17 - 00:28:07
- 19) Convert 'priority' to boolean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 19) Convert 'priority' to boolean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:28:07 - 00:29:42
- 20) Replace 'snake' with 'python' - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 20) Replace 'snake' with 'python'

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:29:42 - 00:30:53
- 21) Mean age by animal and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 21) Mean age by animal and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:30:53 - 00:33:49
- Advanced DataFrame techniques - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Advanced DataFrame techniques

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:33:49 - 00:33:57
- 22) Filter duplicate integers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 22) Filter duplicate integers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:33:57 - 00:43:18
- 23) Subtract row mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 23) Subtract row mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:43:18 - 00:45:42
- 24) Column with smallest sum - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 24) Column with smallest sum

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:45:42 - 00:50:39
- 25) Count unique rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 25) Count unique rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:50:39 - 00:53:17
- 26) Column with third NaN - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 26) Column with third NaN

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:53:17 - 01:10:27
- Solution review for 26 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review for 26

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:10:27 - 01:17:13
- 27) Sum of top three values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 27) Sum of top three values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:17:13 - 01:24:01
- 28) Sum by column condition - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 28) Sum by column condition

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:24:01 - 01:40:11
- Recent problem review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Recent problem review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:40:11 - 01:42:53
- 29) Count differences since last zero - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 29) Count differences since last zero

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:42:53 - 01:56:19
- 30) Locate largest values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 30) Locate largest values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:56:19 - 02:08:38
- 31) Replace negatives with mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 31) Replace negatives with mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:08:38 - 02:17:43
- 32) Rolling mean over groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 32) Rolling mean over groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:17:43 - 02:23:10
- Series and DatetimeIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Series and DatetimeIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:23:10 - 02:23:12
- 33) DatetimeIndex for 2015 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 33) DatetimeIndex for 2015

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:23:12 - 02:27:56
- 34) Sum values on Wednesdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 34) Sum values on Wednesdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:27:56 - 02:45:04
- 35) Monthly mean values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 35) Monthly mean values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:45:04 - 02:46:16
- 36) Best value in four-month groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 36) Best value in four-month groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:46:16 - 02:50:26
- 37) DatetimeIndex of third Thursdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 37) DatetimeIndex of third Thursdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:50:26 - 02:59:03
- Cleaning Data - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Cleaning Data

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:59:03 - 02:59:40
- 38) Fill missing FlightNumber - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 38) Fill missing FlightNumber

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:59:40 - 03:02:45
- 39) Split column by delimiter - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 39) Split column by delimiter

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:02:45 - 03:06:47
- 40) Fix city name capitalization - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 40) Fix city name capitalization

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:06:47 - 03:08:30
- 41) Reattach columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 41) Reattach columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:08:30 - 03:13:11
- 42) Fix airline name punctuation - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 42) Fix airline name punctuation

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:13:11 - 03:17:45
- 43) Expand RecentDelays into columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 43) Expand RecentDelays into columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:17:45 - 03:27:31
- MultiIndexes in Pandas - Solving 100 Python Pandas Problems! (from easy to very difficult)

- MultiIndexes in Pandas

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:27:31 - 03:27:34
- 44) Construct a MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 44) Construct a MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:27:34 - 03:30:37
- Solution review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:30:37 - 03:32:44
- 45) Lexicographically sorted check - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 45) Lexicographically sorted check

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:32:44 - 03:32:58
- 46) Select specific MultiIndex labels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 46) Select specific MultiIndex labels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:32:58 - 03:34:23
- 47) Slice Series with MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 47) Slice Series with MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:34:23 - 03:35:24
- 48) Sum by first level - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 48) Sum by first level

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:35:24 - 03:37:47
- 49) Alternative sum method - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 49) Alternative sum method

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:37:47 - 03:40:08
- Additional solution insights - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Additional solution insights

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:40:08 - 03:41:22
- 50) Swap MultiIndex levels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 50) Swap MultiIndex levels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:41:22 - 03:45:27
- Minesweeper problems - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Minesweeper problems

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:45:27 - 03:45:44
- 51) Generate coordinate grid - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 51) Generate coordinate grid

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:45:44 - 04:00:28
- 52) Add 'safe' or 'mine' column - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 52) Add 'safe' or 'mine' column

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:00:28 - 04:03:04
- 53) Count adjacent mines - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 53) Count adjacent mines

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:03:04 - 04:27:33
- Review solution to 53 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Review solution to 53

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:27:33 - 04:33:02
- Skipped problems 54 & 55 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Skipped problems 54 & 55

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:02 - 04:33:11
- Plotting - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Plotting

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:11 - 04:33:12
- 56) Scatter plot with black x markers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 56) Scatter plot with black x markers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:12 - 04:41:26
- 57) Plot four data types - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 57) Plot four data types

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:41:26 - 04:52:50
- 58) Overlay multiple graphs - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 58) Overlay multiple graphs

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:52:50 - 05:03:11
- 59) Hourly stock data summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 59) Hourly stock data summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
05:03:11 - 05:14:12
- 60) Candlestick plot - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 60) Candlestick plot

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
05:14:12 - 05:20:18
- Intro & Live Stream Overview - Ask me anything! (data science, LLMs, landing a job, and more)

- Intro & Live Stream Overview

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:00:00 - 00:04:58
- How over saturated is the data science job market and will things improve in your opinion? - Ask me anything! (data science, LLMs, landing a job, and more)

- How over saturated is the data science job market and will things improve in your opinion?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:04:58 - 00:07:26
- How much maths is needed to get a data science job? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much maths is needed to get a data science job?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:07:26 - 00:09:55
- Can you share a basic roadmap to learn generative AI and LLMs? - Ask me anything! (data science, LLMs, landing a job, and more)

- Can you share a basic roadmap to learn generative AI and LLMs?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:09:55 - 00:13:08
- What future-proof tech career to should someone focus on who’s looking to change career? - Ask me anything! (data science, LLMs, landing a job, and more)

- What future-proof tech career to should someone focus on who’s looking to change career?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:13:08 - 00:16:52
- Is data structures & algorithms (dsa) necessary to get a job in data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is data structures & algorithms (dsa) necessary to get a job in data science?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:16:52 - 00:19:17
- How to get good at data structures and algorithms? - Ask me anything! (data science, LLMs, landing a job, and more)

- How to get good at data structures and algorithms?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:19:17 - 00:22:20
- Why don’t you make videos regularly now? - Ask me anything! (data science, LLMs, landing a job, and more)

- Why don’t you make videos regularly now?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:22:20 - 00:24:18
- How much do you need to know for entry-level roles / college internships? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much do you need to know for entry-level roles / college internships?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:24:18 - 00:27:02
- How important is domain knowledge for data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- How important is domain knowledge for data science?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:27:02 - 00:29:29
- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts - Ask me anything! (data science, LLMs, landing a job, and more)

- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:29:29 - 00:32:30
- Any good data projects to increase visibility to companies? - Ask me anything! (data science, LLMs, landing a job, and more)

- Any good data projects to increase visibility to companies?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:32:30 - 00:36:05
- Do you think we should all learn vector databases? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do you think we should all learn vector databases?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:36:05 - 00:39:10
- Is webscraping illegal? what can I do and not do? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is webscraping illegal? what can I do and not do?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:39:10 - 00:43:14
- What are you working on at the moment? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are you working on at the moment?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:43:14 - 00:45:25
- How can I turn a financial database I’m building into an interesting portfolio project to showcase work? - Ask me anything! (data science, LLMs, landing a job, and more)

- How can I turn a financial database I’m building into an interesting portfolio project to showcase work?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:45:25 - 00:49:23
- What advice do you have for data scientists who want to get into freelance/consulting? - Ask me anything! (data science, LLMs, landing a job, and more)

- What advice do you have for data scientists who want to get into freelance/consulting?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:49:23 - 00:55:15
- What are important skills for DS beyond ML & AI? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are important skills for DS beyond ML & AI?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:55:15 - 00:59:42
- Do I need to become a full-stack programmer to have success in this field? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do I need to become a full-stack programmer to have success in this field?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:59:42 - 01:02:31
- If you weren’t allowed to do programming or create content, what would you do? - Ask me anything! (data science, LLMs, landing a job, and more)

- If you weren’t allowed to do programming or create content, what would you do?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
01:02:31 - 01:03:39
- How did you achieve your advanced height? Asking for a friend. - Ask me anything! (data science, LLMs, landing a job, and more)

- How did you achieve your advanced height? Asking for a friend.

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
01:03:39 - 01:04:23
- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*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. - Ask me anything! (data science, LLMs, landing a job, and more)

- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*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.

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
01:04:23 - 01:05:26