Exploratory Data Analysis In Python: Machine Learning Project Transactional Data

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Published 2024-07-26

This is the first tutorial video in a series of three, starting-off with understanding the data through exploratory data analysis using the essential Python libraries: pandas, sklearn and seaborn. The data is wrangled by merging dataFrames, pivoting tables, melting column names into categories, reindexing, aggragating, grouping and more available in pandas library. I am walking you through a unique machine learning #project using the transactional data of online casino players.

The content of the video is as follows:
00:00 - Intro
00:51 - Data loading
01:45 - Cast datetime data type to a column
02:22 - Describe of non-numeric variables of Data Frame
04:25 - Remove rows on datetime condition
06:08 - Variable understanding
08:03 - Change values in pandas DataFrame column with .map
09:00 - Group data and generate Histograms and Density plots
13:20 - Subset pandas DataFrame rows based on two conditions
14:14 - Generate TOP N barchart
19:39 - Datetime date type operations
21:40 - Heatmap with time data
26:00 - Apply multiple functions on pandas DataFrame columns at once
29:45 - Fill in the missing datetime slots in pandas Data Frame
35:39 - Create a Sankey Diagram for customer lifetime
45:38 - Format a pandas DataFrame for a grouped bar plot .melt
53:27 - Two project ideas and Bye!

Datasets: data.mendeley.com/datasets/9j5gcygnwg/1
Article: www.sciencedirect.com/science/article/pii/S2352340…

All Comments (6)

@akalokiii yesterday

nice work, giraffa! Following your tutorials
@shaneshshukla 2 days ago

another great video .. learning a lot from you . thank you for creating all this content . your amazing.
@mytechnotalent 3 days ago

Bravo Loana I am a Data Scientist as well working on Deepfake Detection. I love your channel.
@williansuarez3988 3 days ago

Excelent! but still to small, maybe a little zoom +, just a little, thanks
@thirdojohnson4325 2 days ago

Thanks a lot for this. Please do you have a twitter or LinkedIn account? If you don't mind me asking