diff --git a/q01_plot_deliveries_by_team/build.py b/q01_plot_deliveries_by_team/build.py
index d1dab11..c54e6d5 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 +8,16 @@
 
 
 # Solution
+
+def plot_deliveries_by_team():
+    all_teams = ipl_df['batting_team']
+    x_series = pd.Series(all_teams.value_counts().index)
+    y_series = pd.Series(all_teams.value_counts().values)
+
+    plt.bar(x_series,y_series)
+    plt.xticks(rotation = 45)
+    plt.title('graph')
+    plt.xlabel('batting_team')
+    plt.ylabel('delivery')
+    plt.show()
+
diff --git a/q02_plot_matches_by_team/build.py b/q02_plot_matches_by_team/build.py
index ce53182..a85b604 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 +7,21 @@
 
 
 # Solution
+def plot_matches_by_team():
+    team_details = ipl_df.groupby(['batting_team','match_code']).count()
+    teams_per_match = team_details.index.values
+    teams_details = []
+    
+    for x in range(0,len(teams_per_match)):
+        teams_details.append(teams_per_match[x][0])
+    
+    values, counts = np.unique(teams_details, return_counts=True)
+    x1_series = list(values)
+    y1_series = list(counts)
+    plt.bar(x1_series,y1_series)
+    plt.xticks(x1_series , rotation = 90)
+    plt.xlabel('batting_team')
+    plt.ylabel('delivery')
+    plt.show()
+
+
diff --git a/q03_plot_innings_runs_histogram/build.py b/q03_plot_innings_runs_histogram/build.py
index ce53182..c421349 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 +7,18 @@
 
 
 # Solution
+
+def plot_innings_runs_histogram():
+    inningwise_data = ipl_df.groupby(['inning','match_code']).sum()
+    inningwise_data.sort_index(inplace=True)
+
+    match_codes = list(inningwise_data.loc[(1.0),'runs'].index.values)
+    first_innings_scores = list(inningwise_data.loc[(1.0),'runs'])
+    second_innings_scores = list(inningwise_data.loc[(2.0),'runs'])
+
+    fig,axes = plt.subplots(1,2)
+    
+    axes[0].hist(first_innings_scores , bins = 5)
+
+    axes[1].hist(second_innings_scores , bins = 5)
+
diff --git a/q04_plot_runs_by_balls/build.py b/q04_plot_runs_by_balls/build.py
index ce53182..a68238b 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():
+    return None
+def plot_runs_by_balls():
+    return None
+
+
+
+