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q01_plot_deliveries_by_team/build.py

@@ -1,9 +1,23 @@
+#%load q01_plot_deliveries_by_team/build.py
+# %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')
+import matplotlib.pyplot as plt; plt.rcdefaults()
+#plt.switch_backend('agg')
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
 # Solution
+def plot_deliveries_by_team():
+    ser = ipl_df.groupby(['batting_team']).count()['match_code']
+    y_pos = np.arange(len(ser))
+    plt.bar(y_pos, ser, align='center', alpha=0.5)
+    x_pos = ser.index
+    plt.xticks(y_pos, x_pos, rotation=90)
+    plt.ylabel('Deliveries')
+    plt.title('Teams Vs Deliveries')
+    plt.show()
+
+
+

q02_plot_matches_by_team/build.py

@@ -1,3 +1,5 @@
+#%load q02_plot_matches_by_team/build.py
+# %load q02_plot_matches_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +8,13 @@
 
 
 # Solution
+def plot_matches_by_team():
+    ser = ipl_df.groupby(['batting_team']).count()['match_code']
+    y_pos = np.arange(len(ser))
+    plt.bar(y_pos, ser, align='center', alpha=0.5)
+    x_pos = ser.index
+    plt.xticks(y_pos, x_pos, rotation=90)
+    plt.ylabel('Deliveries')
+    plt.title('Teams Vs Deliveries')
+    plt.show()
+

q03_plot_innings_runs_histogram/build.py

@@ -1,3 +1,5 @@
+#%load q03_plot_innings_runs_histogram/build.py
+# %load q03_plot_innings_runs_histogram/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +8,27 @@
 
 
 # Solution
+def get_data():
+    first_inning = ipl_df[ipl_df['inning'] == 1]
+    second_inning = ipl_df[ipl_df['inning'] == 2]
+
+    fi_df = pd.DataFrame(
+        first_inning.groupby(['match_code']).sum()['runs'])
+    se_df = pd.DataFrame(
+        second_inning.groupby('match_code').sum()['runs'])
+
+    return fi_df, se_df
+
+def plot_innings_runs_histogram():
+    f,s = get_data()
+    fig, (ax1, ax2) = plt.subplots(1,2)
+    ax1.hist(f, bins=12)
+    ax1.set_title('First Inning Runs')
+    plt.xticks(rotation=90)
+    ax2.hist(s, bins=12)
+    ax2.set_title('Second Inning Runs')
+    plt.xticks(rotation=90)
+    plt.show()
+
+plot_innings_runs_histogram()
+

q04_plot_runs_by_balls/build.py

@@ -1,3 +1,5 @@
+#%load q04_plot_runs_by_balls/build.py
+# %load q04_plot_runs_by_balls/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +8,10 @@
 
 
 # Solution
+def plot_runs_by_balls():
+    run_details = ipl_df.groupby(['match_code', 'batsman']).agg({'runs': ['count', 'sum']})['runs']
+    plt.scatter(run_details['count'], run_details['sum'])
+    plt.show()
+plot_runs_by_balls()
+
+