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q01_plot_deliveries_by_team/build.py

@@ -1,8 +1,12 @@
+# %load q01_plot_deliveries_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
-
-
-# Solution
+data = ipl_df.pivot_table(values='delivery',index=['batting_team'],aggfunc='count')
+data.plot(kind='bar')
+plt.title('Number of Deliveries Faced by IPL Teams')
+plt.xlabel('IPL Teams')
+plt.ylabel('Number of Deliveries')
+plt.show()

q02_plot_matches_by_team/build.py

@@ -1,8 +1,13 @@
+# %load q02_plot_matches_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
-
-
-# Solution
+def plot_matches_by_team():
+    a=ipl_df.groupby(by='batting_team').nunique()
+    plot=a['match_code'].plot(kind='bar')
+    plot.set_ylabel("Match_Count")
+    plot.set_xlabel("Teams")
+    plt.show()
+plot_deliveries_by_team()

q03_plot_innings_runs_histogram/build.py

@@ -1,8 +1,16 @@
+# %load q03_plot_innings_runs_histogram/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
-
-# Solution
+def plot_innings_runs_histogram():
+    pivot = ipl_df.pivot_table(values=['runs'], index=['match_code'], columns='inning', aggfunc='count')
+    inning_1 = pivot['runs'][1]
+    inning_2 = pivot['runs'][2]
+    plt.subplot(1,2,1)
+    inning_1.hist()
+    plt.subplot(1,2,2)
+    inning_2.hist()
+    plt.show()

q04_plot_runs_by_balls/build.py

@@ -4,5 +4,9 @@
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_runs_by_balls():
+    table = ipl_df.pivot_table(index ='delivery', values=['runs'], aggfunc = np.sum)
+    plt.scatter(table.index,table['runs'])
+    plt.show()
 
 # Solution