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q01_plot_deliveries_by_team/build.py

@@ -5,5 +5,15 @@
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_deliveries_by_team():
+    count_deliveries = ipl_df.groupby(['batting_team']).agg('count')['delivery']
+    count_deliveries.plot(kind = 'bar')
+
+    plt.show();
+
+
+
+plot_deliveries_by_team()
+
+
 
-# Solution

q02_plot_matches_by_team/build.py

@@ -4,5 +4,13 @@
 plt.switch_backend('agg')
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_matches_by_team():
+    count_matches = ipl_df.groupby(['batting_team']).agg('nunique')['match_code']
+    count_matches.plot(kind = 'bar')
+    plt.show();
+
+plot_matches_by_team()
+
+
+
 
-# Solution

q03_plot_innings_runs_histogram/build.py

@@ -4,5 +4,11 @@
 plt.switch_backend('agg')
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_innings_runs_histogram():
+    f1_match = ipl_df.groupby(['match_code','inning']).agg('sum')['total']
+    f1_match.plot(kind= 'hist', subplots= True)
+    plt.show();
+
+plot_innings_runs_histogram()
+
 
-# Solution

q04_plot_runs_by_balls/build.py

@@ -4,5 +4,16 @@
 plt.switch_backend('agg')
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_runs_by_balls():
+    runs_scored = pd.DataFrame(ipl_df.groupby(['match_code', 'batsman']).agg('sum')['runs'])
+    balls_played = pd.DataFrame(ipl_df.groupby(['match_code', 'batsman']).agg('count')['delivery'])
+    playedscored = runs_scored.join(balls_played)
+    plt.scatter(playedscored['runs'], playedscored['delivery'])
+    plt.show();
+
+
+
+plot_runs_by_balls()
+
+
 
-# Solution