diff --git a/q01_plot_deliveries_by_team/build.py b/q01_plot_deliveries_by_team/build.py
index d1dab11..22ed586 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
@@ -6,4 +7,9 @@
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
-# Solution
+def plot_deliveries_by_team():
+    ipl1=ipl_df.groupby('team1').match_code.agg(['count'])
+    ipl1.plot(kind='bar')
+plot_deliveries_by_team()
+
+
diff --git a/q02_plot_matches_by_team/build.py b/q02_plot_matches_by_team/build.py
index ce53182..aaeb571 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
@@ -5,4 +6,9 @@
 ipl_df = pd.read_csv('data/ipl_dataset.csv', index_col=None)
 
 
-# Solution
+def plot_matches_by_team():
+    ipl1=ipl_df.groupby('batting_team').match_code.agg(['nunique'])
+    ipl1.plot.bar()
+
+
+
diff --git a/q03_plot_innings_runs_histogram/build.py b/q03_plot_innings_runs_histogram/build.py
index ce53182..dc0ef26 100644
--- a/q03_plot_innings_runs_histogram/build.py
+++ b/q03_plot_innings_runs_histogram/build.py
@@ -1,8 +1,30 @@
+# %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)
 
+def plot_innings_runs_histogram():
+    ipl_df1=ipl_df.groupby(['inning','match_code'], as_index=False)['runs'].sum()
+    fig,axs=plt.subplots(1,2)
+    axs[0].hist(ipl_df1[ipl_df1.inning==1].runs)
+    axs[0].set_title('First Inning runs distribution')
+    axs[1].hist(ipl_df1[ipl_df1.inning==2].runs)
+    axs[1].set_title('Second Inning runs distribution')
+    plt.show()
+    fig
+fig
+ipl_df1=ipl_df.groupby(['inning','match_code'], as_index=False)['runs'].sum()
+ipl_df1
+ipl_df1[ipl_df1.inning==1].runs
+ipl_df1[ipl_df1.inning==2].runs
+fig,axs=plt.subplots(1,2)
+axs[0].hist(ipl_df1[ipl_df1.inning==1].runs)
+axs[0].set_title('First Inning runs distribution')
+axs[1].hist(ipl_df1[ipl_df1.inning==2].runs)
+axs[1].set_title('Second Inning runs distribution')
+plt.show()
+fig
+
 
-# Solution
diff --git a/q04_plot_runs_by_balls/build.py b/q04_plot_runs_by_balls/build.py
index ce53182..bb1fea8 100644
--- a/q04_plot_runs_by_balls/build.py
+++ b/q04_plot_runs_by_balls/build.py
@@ -1,8 +1,24 @@
+# %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)
+def plot_runs_by_balls():
+    ipl_runs=ipl_df.groupby(['batsman','match_code'],as_index=False).runs.sum()
+    ipl_balls=ipl_df.groupby(['batsman','match_code'],as_index=False).runs.count()
+    ipl_balls.rename(columns={'runs':'balls'},inplace=True)
+    ipl3=pd.concat([ipl_runs, ipl_balls], axis=1, join='inner')
+    fig,axs=plt.subplots(1,1)
+    axs.scatter(ipl3['balls'],ipl3['runs'])
+    plt.show()
+    fig
+plot_runs_by_balls()
+ipl_balls=ipl_df.groupby(['batsman','match_code'],as_index=False).runs.count()
+ipl_balls.rename(columns={'runs':'balls'},inplace=True)
+ipl3=pd.concat([ipl_runs, ipl_balls], axis=1, join='inner')
+fig,axs=plt.subplots(1,1)
+axs.scatter(ipl3['balls'],ipl3['runs'])
+fig
 
 
-# Solution