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q01_plot_deliveries_by_team/build.py

@@ -1,9 +1,23 @@
+#%load q01_plot_deliveries_by_team/build.py
+
 import pandas as pd
 import numpy as np
-import matplotlib.pyplot as plt
-plt.switch_backend('agg')
+from matplotlib import  pyplot as plt
+
+ipl_df=pd.read_csv('./data/ipl_dataset.csv')
+
+# gr=ipl_df.groupby('batting_team').delivery.agg('count')
+
+# plt.bar(gr.index,gr,title='Bar graph of \n Batting team vs count of deliveries ')
+# plt.show()
+def plot_deliveries_by_team():
+    ipl_df.groupby('batting_team').delivery.agg('count').plot(kind='bar',title='Batting team vs count of deliveries ')
+    plt.xlabel=('batsman')
+    plt.ylabel=('runs')
+    plt.show() 
+
+plot_deliveries_by_team()
+
 
-ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
-# Solution

q02_plot_matches_by_team/build.py

@@ -1,8 +1,23 @@
+#%load q02_plot_matches_by_team/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)
+
+from matplotlib import pyplot as plt
+
+ifl_df=pd.read_csv('./data/ipl_dataset.csv')
+
+def plot_matches_by_team():
+    gr=ifl_df.groupby('batting_team')['match_code'].nunique()
+    gr.plot(kind='bar',title=' total number of matches played by each team')
+
+    plt.xlabel('batsman')
+    plt.ylabel('matches played')
+
+    plt.show()
+
+plot_matches_by_team()
+
+
 
 
-# Solution

q03_plot_innings_runs_histogram/build.py

@@ -1,8 +1,22 @@
-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)
+import pandas as  pd
+from matplotlib import pyplot as plt
+
+ifl_df=pd.read_csv('./data/ipl_dataset.csv')
+
+def plot_innings_runs_histogram():
+
+    gr=ifl_df.groupby(['match_code','inning'])['runs'].sum()
+#gr[1::2]
+
+    fig = plt.figure()
+    ax = fig.add_subplot(121)
+    gr[1::2].plot(kind='hist',title=' total number of runs inning 1')
+    ax = fig.add_subplot(122)
+    gr[2::2].plot(kind='hist',title=' total number of runs inning 2')
+
+    plt.show()
+
+plot_innings_runs_histogram()
 
 
-# Solution

q04_plot_runs_by_balls/build.py

@@ -1,8 +1,29 @@
+#%load q04_plot_runs_by_balls/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)
+from matplotlib import pyplot as plt
+
+ifl_df=pd.read_csv('./data/ipl_dataset.csv')
+# ifl_df.columns
+# runs,delivery,batsman
+
+def plot_runs_by_balls():
+
+    gr=ifl_df.groupby('batsman')
+    balls=pd.DataFrame(gr['delivery'].count())
+    runs=pd.DataFrame(gr['runs'].sum())
+
+    A=balls.merge(runs, left_index=True,right_index=True, how='inner')
+
+    plt.scatter(A.runs,A.delivery)
+    plt.xlabel=('runs')
+    plt.ylabel=('deliveries')
+
+    plt.show()
+
+# runs
+
+# plt.scatter(ifl_df[)
 
 
-# Solution