Add Lecture 9

Author: parthsarin

res/.DS_Store

@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+"""
+File: lecture-9.py
+------------------
+
+Code from CS 41: Lecture 9 (Matplotlib).
+
+Authors
+-------
+Parth Sarin (@psarin)
+
+History
+-------
+3-1-2020   @psarin    Created file
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+def simple_plot():
+    """
+    Makes a simple matplotlib plot, which is the segment of y=x from x=1, ..., 4
+    """
+    plt.plot([1, 2, 3, 4])
+    plt.ylabel('some numbers')
+    plt.show()
+
+
+def plot_customizations():
+    """
+    Some simple customizations to the line plot.
+    """
+    # Specify x and y coordinates to plot
+    xs = [1, 2, 3, 4]
+    ys = [1, 4, 9, 16]
+    plt.plot(xs, ys)
+    plt.show()
+    
+    # Change the style of the plot
+    plt.plot(xs, ys, 'ro')
+    plt.show()
+
+    # Use numpy!
+    t = np.arange(0., 5., 0.2)
+    # Red dashes, blue squares and green triangles
+    plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
+    plt.show()
+
+
+def multiple_subplots():
+    """
+    Plot multiple plots in the same figure.
+    """
+    def f(t):
+        return np.exp(-t) * np.cos(2*np.pi*t)
+
+    t1 = np.arange(0.0, 5.0, 0.1)
+    t2 = np.arange(0.0, 5.0, 0.02)
+
+    plt.figure()
+    plt.subplot(211)
+    plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')
+
+    plt.subplot(212)
+    plt.plot(t2, np.cos(2*np.pi*t2), 'r--')
+    plt.show()
+
+
+def histogram():
+    """
+    Plot a histogram.
+    """
+    # Fixing random state for reproducibility
+    np.random.seed(20081203)
+
+    mu, sigma = 100, 15
+    x = mu + sigma * np.random.randn(10000)
+
+    plt.hist(x, 50) # data, number of bins
+    plt.show()
+
+
+def scatter_plot():
+    """
+    Plot a scatter plot.
+    """
+    # Fixing random state for reproducibility
+    np.random.seed(20081203)
+
+    N = 50
+    x = np.random.rand(N)               # x-coordinates
+    y = np.random.rand(N)               # y-coordinates
+    colors = np.random.rand(N)          # color spectra values
+    area = (30 * np.random.rand(N))**2  # radii for points
+    alpha = 0.5                         # transparency
+
+    plt.scatter(x, y, s=area, c=colors, alpha=alpha)
+    plt.show()
+
+
+def main():
+    simple_plot()
+    plot_customizations()
+    multiple_subplots()
+    histogram()
+    scatter_plot()
+
+if __name__ == '__main__':
+    main()

res/lecture-code/Lecture9.zip res/lecture-code/Lecture8.zipres/lecture-code/Lecture9.zip renamed to res/lecture-code/Lecture8.zip

@@ -71,7 +71,7 @@
         "active": false,
         "code": "https://stanfordpython.com/res/lecture-code/Lecture5.zip"
     },
-        {
+    {
         "uid": "7ec7caac-ee4f-434c-9c13-d8f869d9590b",
         "title": "NumPy",
         "date": "2020-02-10",
@@ -83,7 +83,7 @@
         "active": false,
         "code": "#"
     },
-    	{
+    {
         "uid": "86d9817e-e471-4f32-a79e-aa88b307c54b",
         "title": "Standard Library",
         "date": "2020-02-19",
@@ -95,7 +95,7 @@
         "active": false,
         "code": "https://stanfordpython.com/res/lecture-code/Lecture7.zip"
     },
-        {
+    {
         "uid": "161d41b6-b91f-4711-8805-53e827fa2a79",
         "title": "Machine Learning",
         "date": "2020-02-24",
@@ -104,7 +104,19 @@
         "video": "https://drive.google.com/open?id=1V_9xmICwer1U5WlxMIzoY9EO3_it425y",
         "video_note": "#",
         "visible": true,
+        "active": false,
+        "code": "https://stanfordpython.com/res/lecture-code/Lecture8.zip"
+    },
+    {
+        "uid": "fbb1d737-46b3-4ca5-b2ee-339cf2edfcfb",
+        "title": "Matplotlib",
+        "date": "2020-03-02",
+        "condensed": "https://drive.google.com/file/d/1xcndwb2Bf6dS_BFE1bygfa7bOnbqMWQ4/view?usp=sharing",
+        "full": "https://drive.google.com/file/d/1cBMfE6I_-UEc9IdsTjiOJLnK562vHIjG/view?usp=sharing",
+        "video": "#",
+        "video_note": "#",
+        "visible": true,
         "active": true,
-        "code": "https://stanfordpython.com/res/lecture-code/Lecture9.zip"
+        "code": "https://stanfordpython.com/res/lecture-code/lecture-9.py"
     }
 ]