Changes

Author: ghosharitro

Chapter02/Activities/Activity_01.py

@@ -1,43 +1,17 @@
-# Activity 2: Bar plot
+# Activity 1: Line Plot
 
-# Create a list for x
-x = ['Boston Celtics','Los Angeles Lakers', 'Chicago Bulls', 'Golden State Warriors', 'San Antonio Spurs']
+# Create x
+x = ['January','February','March','April','May','June']
 print(x)
 
-# Create a list for y
-y = [17, 16, 6, 6, 5]
+# Create y
+y = [1000, 1200, 1400, 1600, 1800, 2000]
 print(y)
 
-# Put into a data frame so we can sort them
-import pandas as pd
-df = pd.DataFrame({'Team': x,
-                   'Titles': y})
-
-# Sort df by titles
-df_sorted = df.sort_values(by=('Titles'), ascending=False)
-
-# Make a programmatic title
-team_with_most_titles = df_sorted['Team'][0] # get team with most titles
-most_titles = df_sorted['Titles'][0] # get the number of max titles
-title = 'The {} have the most titles with {}'.format(team_with_most_titles, most_titles) # create title
-print(title)
-
-# Plot it
+# Create the plot
 import matplotlib.pyplot as plt # import matplotlib
-plt.bar(df_sorted['Team'], df_sorted['Titles'], color='red') # plot titles by team and make bars red
-plt.xlabel('Team') # create x label
-plt.ylabel('Number of Championships') # create y label
-plt.xticks(rotation=45) # rotate x tick labels 45 degrees
-plt.title(title) # title
-plt.savefig('Titles_by_Team') # save figure to present working directory
-plt.show() # print plot
-
-# Fix the cropping
-import matplotlib.pyplot as plt
-plt.bar(df_sorted['Team'], df_sorted['Titles'], color='red')
-plt.xlabel('Team')
-plt.ylabel('Number of Championships')
-plt.xticks(rotation=45)
-plt.title(title)
-plt.savefig('Titles_by_Team', bbox_inches='tight') # fix the cropping issue
-plt.show()
+plt.plot(x, y, '*:b') # plot items sold (y) by month (x)
+plt.xlabel('Month') # label x-axis
+plt.ylabel('Items Sold') # label y-axis
+plt.title('Items Sold has been Increasing Linearly') # add plot title
+plt.show() # print plot

Chapter02/Activities/Activity_02.py

@@ -1,171 +1,43 @@
-# Activity 3: Multiple Plot Types using Subplots 
+# Activity 2: Bar plot
 
-# import Items_Sold_by_Week.csv
-import pandas as pd
-Items_by_Week = pd.read_csv('Items_Sold_by_Week.csv')
-
-# For scatterplot
-# import Height_by_Weight.csv
-import pandas as pd
-Weight_by_Height = pd.read_csv('Weight_by_Height.csv')
-
-# For histogram and Box-and-Whisker
-# Create an array of 100 normally distributed numbers
-import numpy as np
-y = np.random.normal(loc=0, scale=0.1, size=100) # 100 numbers with mean of 0 and standard deviation of 0.1
-
-# generate figure with 6 subplots organized in 3 rows and 2 columns that do not overlap
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-plt.tight_layout() # prevent plot overlap
-
-# Name the titles
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-# line plot (top left)
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].set_title('Histogram')
-# Scatterplot (bottom left)
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
+# Create a list for x
+x = ['Boston Celtics','Los Angeles Lakers', 'Chicago Bulls', 'Golden State Warriors', 'San Antonio Spurs']
+print(x)
 
-# in the ‘Line’, ‘Bar’, and ‘Horizontal Bar’ axes, plot ‘Items_Sold’ by ‘Week’ from the ‘Items_by_Week’ 
-# Horizontal bar
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-# line plot (top left)
-axes[0,0].plot(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for line plot
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].bar(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for bar plot
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].barh(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for horizontal bar plot
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].set_title('Histogram')
-# Scatterplot (bottom left)
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
-
-# in the 'Histogram' and 'Box-and-Whisker axes, plot ‘Items_Sold’ by ‘Week’ from the ‘Items_by_Week’ 
-# Horizontal bar
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-# line plot (top left)
-axes[0,0].plot(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for line plot
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].bar(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for bar plot
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].barh(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for horizontal bar plot
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].hist(y, bins=20)
-axes[1,1].set_title('Histogram')
-# Scatterplot (bottom left)
-axes[2,1].boxplot(y)
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
-
-# add scatterplot
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-# line plot (top left)
-axes[0,0].plot(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for line plot
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].bar(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for bar plot
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].barh(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for horizontal bar plot
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].hist(y, bins=20) # for histogram
-axes[1,1].set_title('Histogram') 
-# Scatterplot (bottom left)
-axes[2,0].scatter(Weight_by_Height['Height'], Weight_by_Height['Weight']) # for scatterplot
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].boxplot(y) # for Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
-
-# Set x- and y-axis for each subplot
-import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2)
-# line plot (top left)
-axes[0,0].plot(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for line plot
-axes[0,0].set_xlabel('Week')
-axes[0,0].set_ylabel('Items Sold')
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].bar(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for bar plot
-axes[0,1].set_xlabel('Week')
-axes[0,1].set_ylabel('Items Sold')
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].barh(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for horizontal bar plot
-axes[1,0].set_xlabel('Items Sold')
-axes[1,0].set_ylabel('Week')
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].hist(y, bins=20) # for histogram
-axes[1,1].set_xlabel('y')
-axes[1,1].set_ylabel('Frequency')
-axes[1,1].set_title('Histogram') 
-# Scatterplot (bottom left)
-axes[2,0].scatter(Weight_by_Height['Height'], Weight_by_Height['Weight']) # for scatterplot
-axes[2,0].set_xlabel('Height')
-axes[2,0].set_ylabel('Weight')
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].boxplot(y) # for Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
+# Create a list for y
+y = [17, 16, 6, 6, 5]
+print(y)
 
-# Enlarge the figure size and Save the figure
+# Put into a data frame so we can sort them
+import pandas as pd
+df = pd.DataFrame({'Team': x,
+                   'Titles': y})
+
+# Sort df by titles
+df_sorted = df.sort_values(by=('Titles'), ascending=False)
+
+# Make a programmatic title
+team_with_most_titles = df_sorted['Team'][0] # get team with most titles
+most_titles = df_sorted['Titles'][0] # get the number of max titles
+title = 'The {} have the most titles with {}'.format(team_with_most_titles, most_titles) # create title
+print(title)
+
+# Plot it
+import matplotlib.pyplot as plt # import matplotlib
+plt.bar(df_sorted['Team'], df_sorted['Titles'], color='red') # plot titles by team and make bars red
+plt.xlabel('Team') # create x label
+plt.ylabel('Number of Championships') # create y label
+plt.xticks(rotation=45) # rotate x tick labels 45 degrees
+plt.title(title) # title
+plt.savefig('Titles_by_Team') # save figure to present working directory
+plt.show() # print plot
+
+# Fix the cropping
 import matplotlib.pyplot as plt
-fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(8,8)) # for figure size
-# line plot (top left)
-axes[0,0].plot(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for line plot
-axes[0,0].set_xlabel('Week')
-axes[0,0].set_ylabel('Items Sold')
-axes[0,0].set_title('Line')
-# Bar plot (top right)
-axes[0,1].bar(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for bar plot
-axes[0,1].set_xlabel('Week')
-axes[0,1].set_ylabel('Items Sold')
-axes[0,1].set_title('Bar')
-# Horizontal bar plot (middle left)
-axes[1,0].barh(Items_by_Week['Week'], Items_by_Week['Items_Sold']) # for horizontal bar plot
-axes[1,0].set_xlabel('Items Sold')
-axes[1,0].set_ylabel('Week')
-axes[1,0].set_title('Horizontal Bar')
-# Histogram (middle right)
-axes[1,1].hist(y, bins=20) # for histogram
-axes[1,1].set_xlabel('y')
-axes[1,1].set_ylabel('Frequency')
-axes[1,1].set_title('Histogram') 
-# Scatterplot (bottom left)
-axes[2,0].scatter(Weight_by_Height['Height'], Weight_by_Height['Weight']) # for scatterplot
-axes[2,0].set_xlabel('Height')
-axes[2,0].set_ylabel('Weight')
-axes[2,0].set_title('Scatter')
-# Box-and-Whisker
-axes[2,1].boxplot(y) # for Box-and-Whisker
-axes[2,1].set_title('Box-and-Whisker')
-plt.tight_layout() # prevent plot overlap
-fig.savefig('Six_Subplots') # save figure
+plt.bar(df_sorted['Team'], df_sorted['Titles'], color='red')
+plt.xlabel('Team')
+plt.ylabel('Number of Championships')
+plt.xticks(rotation=45)
+plt.title(title)
+plt.savefig('Titles_by_Team', bbox_inches='tight') # fix the cropping issue
+plt.show()