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Learning Path: Python: Effective Data Analysis Using Python

Chapter 1 : Learning Python Data Analysis
The Course Overview 00:03:55
Getting started with Python 00:26:23
Getting Data using the Twitter API 00:20:47
Collecting and Storing Tweets 00:09:27
Database Design 00:10:31
Pandas and Databases 00:05:56
Panda Series, Dataframes, and Columnar Operations 00:21:21
Grouping Operations and Working with Date Columns 00:17:01
Merging Operations and Exporting data to JSON/CSV 00:14:54
Array Features, Bucketting Arrays and Histogram Functions 00:21:02
Simple Aggregations 00:21:23
Linear Algebra 00:04:29
Introducting PyQT and MatplotLib 00:31:47
Creating Charts 00:07:36
Simple XY Plots with Axis Scales 00:04:47
Introduction to the NTLK Package 00:19:00
Bag of Words 00:21:33
Classification of Words 00:09:27
Stemming 00:11:53
Simple Sentiment Analysis 00:05:43
Grouping By Dimensions and Classification of Data Types 00:25:08
Trend Analysis and Deriving New Metrics 00:20:29
Correlation Analysis 00:17:28
Course Summary 00:03:42


Chapter 2 : Getting Started with Python Web Scraping
The Course Overview 00:02:44
When to Web Scrape 00:02:57
What Makes up a Website 00:09:50
How to Interact with a Website 00:08:32
Using the Selenium Module 00:12:12
Ethical Web Scraping 00:04:39
Requesting HTML 00:09:14
Using the BeautifulSoup Module 00:13:18
Example: Parsing Wikipedia 00:11:22
Bypassing the Browser 00:04:25
Introduction to APIs 00:04:59
Working with APIs 00:11:52


Chapter 3 : Python Data Visualization Solutions
The Course Overview 00:03:38
Importing Data from CSV 00:04:33
Importing Data from Microsoft Excel Files 00:04:46
Importing Data from Fix-Width Files 00:03:06
Importing Data from Tab Delimited Files 00:02:23
Importing Data from a JSON Resource 00:05:17
Importing Data from a Database 00:05:09
Cleaning Up Data from Outliers 00:05:54
Importing Image Data into NumPy Arrays 00:06:01
Generating Controlled Random Datasets 00:06:36
Smoothing Noise in Real-World Data 00:04:45
Defining Plot Types and Drawing Sine and Cosine Plots 00:07:53
Defining Axis Lengths and Limits 00:05:16
Defining Plot Line Styles, Properties, and Format Strings 00:01:59
Setting Ticks, Labels, and Grids 00:02:43
Adding Legends and Annotations 00:02:33
Moving Spines to Center 00:01:22
Making Histograms 00:03:59
Making Bar Charts with Error Bars 00:03:23
Making Pie Charts Count 00:01:59
Plotting with Filled Areas 00:01:56
Drawing Scatter Plots with Colored Markers 00:02:13
Adding a Shadow to the Chart Line 00:03:56
Adding a Data Table to the Figure 00:02:26
Using Subplots 00:03:57
Customizing Grids 00:03:05
Creating Contour Plots 00:03:24
Filling an Under-Plot Area 00:02:01
Drawing Polar Plots 00:02:56
Visualizing the filesystem Tree Using a Polar Bar 00:03:03
Creating 3D Bars 00:05:33
Creating 3D Histograms 00:03:13
Animating with OpenGL 00:06:02
Plotting with Images 00:06:18
Displaying Images with Other Plots in the Figure 00:03:52
Plotting Data on a Map Using Basemap 00:05:23
Generating CAPTCHA 00:06:36
Understanding Logarithmic Plots 00:05:19
Creating a Stem Plot 00:04:18
Drawing Streamlines of Vector Flow 00:03:28
Using Colormaps 00:05:17
Using Scatter Plots and Histograms 00:04:29
Plotting the Cross Correlation Between Two Variables 00:03:27
The Importance of Autocorrelation 00:04:11
Drawing Barbs 00:06:24
Making a Box-and-Whisker Plot 00:03:37
Making Gantt Charts 00:03:50
Making Error Bars 00:04:40
Making Use of Text and Font Properties 00:04:00
Understanding the Difference between pyplot and OO API 00:05:13