diff --git a/q01_read_csv_data_to_df/build.py b/q01_read_csv_data_to_df/build.py
index 7af672f..6562a62 100644
--- a/q01_read_csv_data_to_df/build.py
+++ b/q01_read_csv_data_to_df/build.py
@@ -1,8 +1,20 @@
+# %load q01_read_csv_data_to_df/build.py
 # Default Imports
 import pandas as pd
 
 # Path has been given to you already to use in function.
-path = "data/ipl_dataset.csv"
+path = 'data/ipl_dataset.csv'
 
 # Solution
+def read_csv_data_to_df(path):
+    
+    #returning dataFrame when reding csv file
+    df = pd.read_csv(path) 
+    
+    return df
+
+read_csv_data_to_df(path)
+
+
+
 
diff --git a/q02_get_unique_values/build.py b/q02_get_unique_values/build.py
index a98550a..c8d87e9 100644
--- a/q02_get_unique_values/build.py
+++ b/q02_get_unique_values/build.py
@@ -1,6 +1,21 @@
+# %load q02_get_unique_values/build.py
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
-
+import pandas as pd
 # You have been given the dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('data/ipl_dataset.csv')
 
 #Solution
+def get_unique_venues():  
+    
+    # get unique values from venue column
+    unique_venue = ipl_df['venue'].unique()
+    
+    return unique_venue
+
+
+get_unique_venues()
+#pd.set_option('display.max_row', 1000)
+#pd.set_option('display.max_columns',10)
+
+
+
diff --git a/q03_get_run_counts/build.py b/q03_get_run_counts/build.py
index 07a05ac..1cee855 100644
--- a/q03_get_run_counts/build.py
+++ b/q03_get_run_counts/build.py
@@ -1,8 +1,19 @@
+# %load q03_get_run_counts/build.py
 # Default Imports
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
 
 # You have been given the dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('./data/ipl_dataset.csv')
 
 # Solution
+def get_run_counts():
+    
+    # calculate the frequency of values in column runs
+    frequency_of_runs = ipl_df['runs'].value_counts()
+    
+    return frequency_of_runs
+
+
+get_run_counts()
+
 
diff --git a/q04_get_match_specific_df/build.py b/q04_get_match_specific_df/build.py
index 37ec96a..e1cbea7 100644
--- a/q04_get_match_specific_df/build.py
+++ b/q04_get_match_specific_df/build.py
@@ -1,7 +1,24 @@
+# %load q04_get_match_specific_df/build.py
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
 
 # You have been given dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('./data/ipl_dataset.csv')
 
 # Solution
 
+def get_match_specific_df(match_code):
+    
+    #checking type of data in match_code
+    #print(type(ipl_df['match_code'][0]))
+    
+    #match_code == ipl_df['match_code'][0] #output is true 
+    
+    # result of particular match_code
+    result = ipl_df[ipl_df['match_code']== match_code]
+    
+    return result
+
+match_code = 392203
+get_match_specific_df(match_code)
+
+
diff --git a/q05_create_bowler_filter/build.py b/q05_create_bowler_filter/build.py
index 5c15aaa..434c0a3 100644
--- a/q05_create_bowler_filter/build.py
+++ b/q05_create_bowler_filter/build.py
@@ -1,7 +1,21 @@
+# %load q05_create_bowler_filter/build.py
 # Default imports
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
 
 # You have been given dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('./data/ipl_dataset.csv')
 
 # Solution
+def create_bowler_filter(bowler_name):
+    
+    #checking whether type of data in bowler column same or not
+    #print(ipl_df['bowler'][0]== bowler_name )
+    
+    # returning filter result
+    result = ipl_df['bowler'] == bowler_name
+    
+    return result
+bowler_name = 'I Sharma'
+create_bowler_filter(bowler_name)
+
+
diff --git a/q06_get_match_innings_runs/build.py b/q06_get_match_innings_runs/build.py
index d938fc2..5f9f819 100644
--- a/q06_get_match_innings_runs/build.py
+++ b/q06_get_match_innings_runs/build.py
@@ -1,10 +1,21 @@
+# %load q06_get_match_innings_runs/build.py
 # Default Imports
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
-
+import pandas as pd
 # You have been given dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('data/ipl_dataset.csv')
+
+#pd.set_option('display.max_columns', 30)
+def get_match_innings_runs():
+    
+    df = (ipl_df.groupby(['match_code', 'inning']).sum())
+
+    return df
+
+
+get_match_innings_runs().sort_values(ascending = False)
+
 
-# Solution
 
 
 
diff --git a/q07_get_run_counts_by_match/build.py b/q07_get_run_counts_by_match/build.py
index a18e534..281c71a 100644
--- a/q07_get_run_counts_by_match/build.py
+++ b/q07_get_run_counts_by_match/build.py
@@ -1,7 +1,21 @@
+# %load q07_get_run_counts_by_match/build.py
 # Default Imports
 from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
-
+import pandas as pd
 # You have been give the dataset already in 'ipl_df'.
-ipl_df = read_csv_data_to_df("./data/ipl_dataset.csv")
+ipl_df = read_csv_data_to_df('./data/ipl_dataset.csv')
 
 # Solution
+def get_runs_counts_by_match():
+    
+    # create new dataframe of following columns
+    ipl_df1 = ipl_df[['match_code','runs','batsman']]
+    
+    # create a pivot table 
+    pivot_df = pd.pivot_table(ipl_df1, values = ['runs'], index = ['match_code'], columns = ['runs'], aggfunc = 'count')
+    
+    return pivot_df
+get_runs_counts_by_match()
+
+
+