Added Matplotlib and Comprehensions files

Matplotlib/pyplot.py

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+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# 1. simple plot with 4 numbers
+plt.plot([1, 3, 2, 4])
+plt.show()
+
+# 2. points have x and y values; add title and axis labels
+plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
+plt.title('Test Plot', fontsize=8, color='g')
+plt.xlabel('number n')
+plt.ylabel('n^2')
+plt.show()
+
+# 3. change figure size. plot red dots; set axis scales x: 0-6 and y: 0-20
+plt.figure(figsize=(1,5))	# 1 inch wide x 5 inches tall
+plt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')	# red-o
+plt.axis([0, 6, 0, 20])						# [xmin, xmax, ymin, ymax]
+plt.annotate('square it', (3,6))
+plt.show()
+
+# 4. bar chart with four bars
+plt.clf()			# clear figure
+x = np.arange(4)
+y = [8.8, 5.2, 3.6, 5.9]
+plt.xticks(x, ('Ankit', 'Hans', 'Joe', 'Flaco'))
+plt.bar(x, y)
+# plt.bar(x, y, color='y')
+# plt.bar(x, y, color=['lime', 'r', 'k', 'tan'])
+plt.show()
+
+# 5. two sets of 10 random dots plotted
+d = {'Red O' : np.random.rand(10),
+     'Grn X' : np.random.rand(10)}
+df = pd.DataFrame(d)
+df.plot(style=['ro','gx'])
+plt.show()
+
+# 6. time series - six months of random floats
+ts = pd.Series(np.random.randn(180), index=pd.date_range('1/1/2018', periods=180))
+df = pd.DataFrame(np.random.randn(180, 3), index=ts.index, columns=list('ABC'))
+df.cumsum().plot()
+plt.show()
+
+# 7. random dots in a scatter
+N = 50
+x = np.random.rand(N)
+y = np.random.rand(N)
+colors = np.random.rand(N)
+sizes = (30 * np.random.rand(N))**2  # 0 to 15 point radii
+plt.scatter(x, y, s=sizes, c=colors, alpha=0.5)
+plt.show()
+
+# 8. load csv file and show multiple chart types
+df = pd.read_csv('Fremont_weather.txt')
+print(df)
+plt.bar(df['month'], df['record_high'], color='r')
+plt.bar(df['month'], df['record_low'], color='c')
+plt.plot(df['month'], df['avg_high'], color='k')
+plt.plot(df['month'], df['avg_low'], color='b')
+plt.legend()   # or plt.figlegend for legend outside the plot area
+plt.show() 
+
+# 9. subplots
+fig = plt.figure()
+fig.suptitle('My SubPlots')
+fig.add_subplot(221)   #top left
+plt.plot([np.log(n) for n in range(1,10)])
+fig.add_subplot(222, facecolor='y')   #top right
+fig.add_subplot(223)   #bottom left
+fig.add_subplot(224)   #bottom right 
+plt.show()
+
+fig, plots = plt.subplots(2, sharex=True)
+fig.suptitle('Sharing X axis')
+x = range(0,200,5)
+y = [n**0.8 for n in x]
+plots[0].plot(x, y, color='r')
+plots[1].scatter(x, y)
+
+# 10. save figure to image file
+plt.figure(figsize=(4,3), dpi=100)
+plt.plot([245, 170, 148, 239, 161, 196, 112, 258])
+plt.axis([0, 7, 0, 300])
+plt.title('Flight Data')
+plt.xlabel('Speed')
+# plt.savefig('Flights.png')
+plt.show()
+

list_comprehensions.py

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+# list comprehensions
+# basic format: new_list = [transform sequence [filter] ]
+import random
+
+under_10 = [x for x in range(10)]
+print('under_10: ' + str(under_10))
+
+squares = [x**2 for x in under_10]
+print('squares: ' + str(squares))
+
+odds =  [x for x in range(10) if x%2 == 1]
+print('odds: ' + str(odds))
+
+ten_x = [x * 10 for x in range(10)]
+print('ten_x: ' + str(ten_x))
+
+# get all numbers from a string
+s = 'I love 2 go t0 the store 7 times a w3ek.'
+nums = [x for x in s if x.isnumeric()]
+print('nums: ' + ''.join(nums))
+
+# get index of a list item
+names = ['Cosmo', 'Pedro', 'Anu', 'Ray']
+idx = [k for k, v in enumerate(names) if v == 'Anu']
+print('index = ' + str(idx[0]))
+
+# delete an item from a list
+letters = [x for x in 'ABCDEF']
+random.shuffle(letters)
+letrs = [a for a in letters if a != 'C']
+print(letters, letrs)
+
+# if-else condition in a comprehension (must come before iteration)
+nums = [5, 3, 10, 18, 6, 7]
+new_list = [x if x%2 == 0 else 10*x for x in nums]
+print('new list: ' + str(new_list))
+
+# nested loop iteration for 2D list
+a = [[1,2],[3,4]]
+new_list = [x for b in a for x in b]
+print(new_list)
+