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q01_plot_deliveries_by_team/build.py

@@ -1,3 +1,4 @@
+# %load q01_plot_deliveries_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -7,3 +8,24 @@
 
 
 # Solution
+
+def plot_deliveries_by_team():
+    x=ipl_df.groupby('batting_team').delivery.count()
+    plt.bar(x.index,x.values)
+    plt.show()
+
+plt.bar([1,2,3],[1,4,9])
+plt.show()
+x=ipl_df.groupby('batting_team').delivery.count()
+type(x)
+plt.bar(x,height=2)
+plt.show()
+x
+x[0]
+x[1]
+x.index
+x.values
+u=x.index
+np.array(u)
+
+

q02_plot_matches_by_team/build.py

@@ -1,3 +1,4 @@
+# %load q02_plot_matches_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +7,14 @@
 
 
 # Solution
+def plot_matches_by_teams():
+    x=ipl_df.groupby('batting_team').match_code.nunique()
+    plt.bar(x.index, x.values)
+    plt.show()
+x=ipl_df.groupby('batting_team').match_code.nunique()
+x.index
+x.values
+plt.bar(x.index,x.values)
+plt.show()
+
+

q03_plot_innings_runs_histogram/build.py

@@ -1,8 +1,42 @@
+# %load q03_plot_innings_runs_histogram/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
+
 plt.switch_backend('agg')
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
 # Solution
+def plot_innigs_runs_histogram():
+    x=ipl_df[ipl_df['toss_decision']=='bat']['total']
+    y=ipl_df[ipl_df['toss_decision']=='field']['total']
+    fig, ax = plt.subplots(1,2)
+    ax[0].hist(x, bins=10, alpha = 0.5, color = 'r')
+    ax[1].hist(y, bins=10, alpha = 0.5, color = 'g')
+    plt.show()
+
+x=ipl_df[ipl_df['toss_decision']=='bat']['total']
+y=ipl_df[ipl_df['toss_decision']=='field']['total']
+plt.subplots(2,1)
+plt.hist(y,bins=10)
+
+
+# An 'interface' to matplotlib.axes.Axes.hist() method
+n, bins, patches = plt.hist(x=x, bins='auto', color='#0504aa',
+                            alpha=0.7, rwidth=0.85)
+plt.grid(axis='y', alpha=0.75)
+plt.xlabel('Value')
+plt.ylabel('Frequency')
+plt.title('My Very Own Histogram')
+plt.text(23, 45, r'$\mu=15, b=3$')
+maxfreq = n.max()
+# Set a clean upper y-axis limit.
+plt.ylim(ymax=np.ceil(maxfreq / 10) * 10 if maxfreq % 10 else maxfreq + 10)
+fig, ax = plt.subplots(1,2)
+ax[0].hist(x, bins=10, alpha = 0.5, color = 'r')
+ax[1].hist(y, bins=10, alpha = 0.5, color = 'g')
+plt.show()
+plot_innigs_runs_histogram()
+
+

q04_plot_runs_by_balls/build.py

@@ -1,3 +1,4 @@
+# %load q04_plot_runs_by_balls/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +7,17 @@
 
 
 # Solution
+def plot_runs_by_balls():
+    plt.scatter(ipl_df['runs'],ipl_df.index)
+    plt.show()
+
+
+plt.scatter(ipl_df['runs'],ipl_df.index)
+plt.show()
+fig, ax = plt.subplots(1,2)
+ax[0].hist(x, bins=10, alpha = 0.5, color = 'r')
+ax[1].hist(y, bins=10, alpha = 0.5, color = 'g')
+plt.show()
+plot_runs_by_balls()
+
+