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Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
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Python data analysis / data science tutorial. Let’s go!
Outline - check the comment section for a clickable version:
0:37: Why data visualization?
1:05: Why Python?
1:39: Why Matplotlib?
2:23: Installing Jupyter through Anaconda
3:20: Launching Jupyter
3:41: DEMO begins: create a folder and download data
4:27: Create a new Jupyter Notebook file
5:09: Importing libraries
6:04: Simple examples of how to use Matplotlib / Pyplot
7:21: Plotting multiple lines
8:46: Importing data from a CSV file
10:46: Plotting data you’ve imported
13:19: Using a third argument in the plot() function
13:42: A real analysis with a real data set - loading data
14:49: Isolating the data for the U.S. and China
16:29: Plotting US and China’s population growth
18:22: Comparing relative growths instead of the absolute amount
Outline - check the comment section for a clickable version:
0:37: Why data visualization?
1:05: Why Python?
1:39: Why Matplotlib?
2:23: Installing Jupyter through Anaconda
3:20: Launching Jupyter
3:41: DEMO begins: create a folder and download data
4:27: Create a new Jupyter Notebook file
5:09: Importing libraries
6:04: Simple examples of how to use Matplotlib / Pyplot
7:21: Plotting multiple lines
8:46: Importing data from a CSV file
10:46: Plotting data you’ve imported
13:19: Using a third argument in the plot() function
13:42: A real analysis with a real data set - loading data
14:49: Isolating the data for the U.S. and China
16:29: Plotting US and China’s population growth
18:22: Comparing relative growths instead of the absolute amount
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