diff --git a/q01_plot_deliveries_by_team/build.py b/q01_plot_deliveries_by_team/build.py
index d1dab11..215e93c 100644
--- a/q01_plot_deliveries_by_team/build.py
+++ b/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
@@ -5,5 +6,19 @@
 
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
+def plot_deliveries_by_team():
+    x = ipl_df['batting_team']
+    #y = ipl_df.groupby('batting_team')['delivery'].count()
+    y = ipl_df['delivery']
+    print(x.shape,y.shape)
+    #plt.scatter(x,y)
+    plt.plot(x,y)
+    plt.show()
+
+#plot_deliveries_by_team()
+
 
 # Solution
+
+
+
diff --git a/q02_plot_matches_by_team/build.py b/q02_plot_matches_by_team/build.py
index ce53182..53362bf 100644
--- a/q02_plot_matches_by_team/build.py
+++ b/q02_plot_matches_by_team/build.py
@@ -1,8 +1,20 @@
+# %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)
 
-
+def plot_matches_by_team():
+    x_team = ipl_df['batting_team']
+    #y_count = ipl_df.groupby('batting_team')['match_code'].count()
+    y_count = ipl_df['match_code']
+    #print(y_count)
+    plt.scatter(x_team,y_count)
+    plt.plot(x_team,y_count)
+    plt.show()
 # Solution
+plot_matches_by_team()
+
+
+
diff --git a/q03_plot_innings_runs_histogram/build.py b/q03_plot_innings_runs_histogram/build.py
index ce53182..132ab30 100644
--- a/q03_plot_innings_runs_histogram/build.py
+++ b/q03_plot_innings_runs_histogram/build.py
@@ -1,8 +1,23 @@
+# %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_innings_runs_histogram():
+    #x = ipl_df.where(ipl_df['inning']==1)['runs']
+    x1 = ipl_df.where(ipl_df['inning']==1, other = 0)['runs']
+    x2 = ipl_df.where(ipl_df['inning']==2, other = 0)['runs']
+    #print(x)
+    plt.figure()
+    plt.subplot(121)
+    plt.hist(x1)
+    plt.subplot(122)
+    plt.hist(x2)
+
+plot_innings_runs_histogram()
+
+
diff --git a/q04_plot_runs_by_balls/build.py b/q04_plot_runs_by_balls/build.py
index ce53182..e83dd53 100644
--- a/q04_plot_runs_by_balls/build.py
+++ b/q04_plot_runs_by_balls/build.py
@@ -1,8 +1,25 @@
+# %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)
 
-
 # Solution
+def plot_runs_by_balls():
+    ball_count = ipl_df[['match_code','batsman','delivery']].groupby(['match_code','batsman'])['delivery'].count()
+    runs = ipl_df[['match_code','batsman','runs']].groupby(['match_code','batsman'])['runs'].sum()
+    ball_count = pd.DataFrame(ball_count, columns = ['match_code','batsman','delivery'])
+    runs = pd.DataFrame(runs, columns = ['match_code','batsman','runs'])
+    #print(runs)
+    merged = pd.merge(ball_count,runs, left_on= 'match_code', right_on= 'match_code')
+    x = merged['delivery']
+    y = merged['runs']
+    plt.figure()
+    plt.subplot(111)
+    plt.scatter(x,y)
+    
+    
+plot_runs_by_balls()
+
+