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Learn Python for Data Analysis and Visualization
Course Introduction
Course overview (3:36)
How to access the source code of this course
Setting up Python, Anaconda, Atom and GitHub
Setting up Anaconda (7:02)
Setting up the Atom text editor (4:28)
How to create a virtual environment (3:28)
How to clone a GitHub Repository (5:44)
New Lecture
How to use the Atom Text Editor to push code to GitHub
Introduction to Python Pandas
Introduction to Pandas (1:05)
Introduction to Dataframes (2:13)
Inspecting data (17:46)
Conditional filtering (3:51)
Using NumPy and Pandas together (2:21)
Creating Dataframes from NumPy (3:03)
Creating Dataframes from dictionaries (6:16)
Using Broadcasting in Pandas (1:40)
Labelling data in a Dataframe (1:29)
Building Dataframes with broadcasting (1:55)
Cleansing, Importing and Exporting Data (12:19)
Creating plots with pandas (10:29)
Visual Data Analysis
Creating graphs with pandas line plot (4:15)
Creating graphs with pandas scatter plot (4:22)
Creating graphs with pandas bar plot (2:01)
Statistical Exploratory Data Analysis (6:07)
Filtering data (5:38)
Managing Dates and Times with Python Pandas
Introduction to pandas DateTime (0:47)
Indexing panda time series (5:38)
Creating and using a DateTimeIndex (2:08)
Resampling Pandas Time Data (5:36)
Method Chaining (2:36)
Separating and Resampling (2:29)
Additional Filtering Methods (3:05)
Visualizing Pandas Time Data (5:02)
How to use the Atom Text Editor to push code to GitHub
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