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Introduction to Data Analytics.
Intro to Data Analysis and Visualisation with Python
Introduction (1:17)
What we are going to learn, and why learn Data Analytics? (15:59)
Why use Python? (5:05)
Setting up Python, Anaconda and Jupyter notebooks (15:15)
Intro to Jupyter notebooks (27:55)
Intro to Python notebooks + Variables (12:00)
Strings (14:24)
Numbers (10:51)
Boolean (8:09)
Lists (27:41)
Wrapping up and finding help (5:03)
Homework (10:06)
Problem definition, Getting data, and Pandas
Introduction (1:06)
Framing the problem (8:37)
Data sources (6:02)
Data quality and ethics (8:52)
Reading data in (4:19)
Intro to Pandas and dataframes (10:48)
Reading and writing dataframes (7:57)
Inspecting dataframes (3:30)
Indexing (4:07)
Golden thread project (6:03)
Homework (14:20)
Data Wrangling
Introduction (1:34)
Lightning quick theory (9:32)
Selecting columns (7:36)
Renaming columns (4:09)
Filtering rows (10:46)
Dropping rows and columns (5:43)
Mutating columns (9:26)
Summarising/aggregating (29:03)
Homework (4:33)
Visualisations
Introduction (1:24)
Intro to data visualisation (6:33)
How do our minds interpret visualisations? (11:33)
Do's and Don'ts (9:56)
Data visualisation in Python (12:03)
Intro to packages (8:54)
Intro to Seaborn (10:42)
Relationship plots (19:50)
Categorical plots (9:22)
Advanced plots (7:31)
Homework (2:44)
Why use Python?
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