diff --git a/q01_plot_deliveries_by_team/build.py b/q01_plot_deliveries_by_team/build.py
index d1dab11..0eab31a 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 +8,12 @@
 
 
 # Solution
+def plot_deliveries_by_team():
+    count=ipl_df.groupby(ipl_df['batting_team']).agg('count')
+    plt.bar(count.index,count['delivery'])
+    plt.title('Deliveries/teams')
+    plt.xlabel('batting_teams')
+    plt.ylabel('Deliveries')
+    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..70803fb 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 +7,14 @@
 
 
 # Solution
+def plot_matches_by_team():
+    count=ipl_df.groupby(ipl_df['batting_team']).agg('nunique')
+    plt.bar(count.index,count['match_code'])
+    plt.title('count of matches/teams')
+    plt.xlabel('batting_teams')
+    plt.ylabel('count of matches')
+    plt.xticks(count.index,rotation=90)
+    plt.show()
+plot_matches_by_team()
+    
+
diff --git a/q03_plot_innings_runs_histogram/build.py b/q03_plot_innings_runs_histogram/build.py
index ce53182..7dbcf72 100644
--- a/q03_plot_innings_runs_histogram/build.py
+++ b/q03_plot_innings_runs_histogram/build.py
@@ -1,8 +1,21 @@
+# %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')
+#plt.switch_backend('agg')
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
 # Solution
+def plot_innings_runs_histogram():
+    i1=ipl_df[ipl_df['inning']==1]
+    x=i1.groupby(ipl_df['match_code']).agg('sum')
+
+    i2=ipl_df[ipl_df['inning']==2]
+    y=i2.groupby(ipl_df['match_code']).agg('sum')
+    fig, axs = plt.subplots(1, 2, sharey=True)
+    axs[0].hist(x['runs'])
+    axs[1].hist(y['runs'])
+    fig.show()
+plot_innings_runs_histogram()
+
diff --git a/q04_plot_runs_by_balls/build.py b/q04_plot_runs_by_balls/build.py
index ce53182..be679e2 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 +7,11 @@
 
 
 # Solution
+def plot_runs_by_balls():
+    bat=ipl_df.groupby(['batsman','match_code']).agg({'runs':sum,'delivery':'count'})
+    plt.scatter(bat.delivery,bat.runs)
+    plt.xlabel('balls faced')
+    plt.ylabel('runs scored')
+    plt.show()
+plot_runs_by_balls()
+