diff --git a/q01_plot_deliveries_by_team/build.py b/q01_plot_deliveries_by_team/build.py
index d1dab11..d89f891 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
@@ -7,3 +8,14 @@
 
 
 # Solution
+def plot_deliveries_by_team():
+    batting_team = ipl_df['batting_team']
+    deliveries_by_team = batting_team.value_counts()
+    x_series = np.arange(len(deliveries_by_team.index))
+    plt.bar(x_series, deliveries_by_team)
+    plt.xticks(x_series, deliveries_by_team.index.values, rotation=90)
+    plt.show()
+    
+plot_deliveries_by_team()
+
+
diff --git a/q02_plot_matches_by_team/build.py b/q02_plot_matches_by_team/build.py
index ce53182..7f9103c 100644
--- a/q02_plot_matches_by_team/build.py
+++ b/q02_plot_matches_by_team/build.py
@@ -1,3 +1,4 @@
+# %load q02_plot_matches_by_team/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +7,17 @@
 
 
 # Solution
+def plot_matches_by_team():
+    matches_by_team = ipl_df[['batting_team', 'match_code']].groupby(['batting_team']).aggregate('nunique')
+    x_series = np.arange(len(matches_by_team.index))
+
+    plt.bar(x_series, matches_by_team['match_code'])
+    plt.xlabel('Team')
+    plt.ylabel('Matches Count')
+    
+    plt.xticks(x_series, matches_by_team.index.values, rotation=90)
+    plt.show()
+    print(matches_by_team)
+plot_matches_by_team()
+
+
diff --git a/q03_plot_innings_runs_histogram/build.py b/q03_plot_innings_runs_histogram/build.py
index ce53182..336ee2c 100644
--- a/q03_plot_innings_runs_histogram/build.py
+++ b/q03_plot_innings_runs_histogram/build.py
@@ -1,3 +1,4 @@
+# %load q03_plot_innings_runs_histogram/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +7,13 @@
 
 
 # Solution
+def plot_innings_runs_histogram():
+    per_match_runs = ipl_df[['match_code', 'inning']].groupby('inning').agg('sum')     
+    plt.hist(per_match_runs)
+    plt.show()
+    print(per_match_runs)
+    
+plot_innings_runs_histogram()
+
+
+
diff --git a/q04_plot_runs_by_balls/build.py b/q04_plot_runs_by_balls/build.py
index ce53182..df51a99 100644
--- a/q04_plot_runs_by_balls/build.py
+++ b/q04_plot_runs_by_balls/build.py
@@ -1,3 +1,4 @@
+# %load q04_plot_runs_by_balls/build.py
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -6,3 +7,15 @@
 
 
 # Solution
+def plot_runs_by_balls():
+    group_by = ipl_df.groupby(['match_code', 'batsman'])
+    balls = group_by['runs'].count().rename('balls').reset_index()
+    runs = group_by['runs'].sum().rename('runs').reset_index()
+    df = pd.merge(balls, runs, on=['match_code', 'batsman'])
+    plt.scatter(x=df['runs'], y=df['balls'])
+    plt.xlabel('Count of Balls Played')
+    plt.ylabel('Total Runs Scored')
+    plt.show()
+plot_runs_by_balls()    
+
+