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q01_zeros_array/build.py

@@ -1,8 +1,15 @@
+# %load q01_zeros_array/build.py
 # Default Imports
 import sys, os
 sys.path.append(os.path.join(os.path.dirname(os.curdir),  '..'  ))
 import numpy as np
 
 # Your solution
+def array_zeros():
+    zeros_array = np.zeros((3,4,2))
+    return zeros_array
+
+
+
 
 

q02_zeros_reshaped/build.py

@@ -1,5 +1,21 @@
+# %load q02_zeros_reshaped/build.py
 # Default imports
 import numpy as np
 from greyatomlib.python_intermediate.q01_zeros_array.build import  array_zeros
 
 # Write your code
+def array_reshaped_zeros():
+    zeros_array_reshaped = array_zeros().reshape(2,3,4)
+    return zeros_array_reshaped
+
+
+
+
+
+
+
+
+
+
+
+

q03_create_3d_array/build.py

@@ -1,4 +1,16 @@
+# %load q03_create_3d_array/build.py
 # Default Imports
 import numpy as np
 
-# Enter solution here
+# Enter solution here
+def create_3d_array():
+    #specify desired dimensions
+    dim1 = 3; dim2 = 3; dim3 = 3
+    elements = dim1*dim2*dim3
+    variable = np.arange(elements).reshape(dim1,dim2,dim3)
+    return variable
+
+
+
+
+

q04_read_csv_data_to_ndarray/build.py

@@ -1,5 +1,19 @@
+# %load q04_read_csv_data_to_ndarray/build.py
 # Default Imports
 import numpy as np
-path = "./data/ipl_matches_small.csv"
+path = './data/ipl_matches_small.csv'
+dtype = None
+
+# Enter code here
+def read_csv_data_to_ndarray(path,dtype):
+    data = np.genfromtxt(path, delimiter = ',',dtype=dtype,skip_header=1)
+    return data
+
+read_csv_data_to_ndarray(path,dtype)
+#type(data)
+#print(data)
+
+
+
+
 
-# Enter code here

q05_read_csv_data/build.py

@@ -1,4 +1,16 @@
+# %load q05_read_csv_data/build.py
 # Default imports
 import numpy as np
+path = './data/ipl_matches_small.csv'
+dtype = '|S50'
+
+# Enter code here
+def read_ipl_data_csv(path,dtype):
+    ipl_matches_array = np.genfromtxt(path,delimiter=',',dtype=dtype,skip_header=1)
+    return ipl_matches_array
+
+read_ipl_data_csv(path,dtype)
+
+
+
 
-# Enter code here

q06_get_unique_matches_count/build.py

@@ -1,5 +1,23 @@
+# %load q06_get_unique_matches_count/build.py
 # Default imports
 from greyatomlib.python_intermediate.q05_read_csv_data.build import read_ipl_data_csv
-path = 'data/ipl_matches_small.csv'
+#path = 'data/ipl_matches_small.csv'  #path for reference as function should not take any parameter.
+import numpy as np
 
 # Enter Code Here
+def get_unique_matches_count():  
+
+    #loading the file in a variable
+    y=np.genfromtxt('data/ipl_matches_small.csv',dtype=None,delimiter=',')
+
+    #Getting unique match code ids by using numpy unique function
+    #Subtracting 1 from total count as one value among unique cinstitutes for the header
+    ipl_matches_array = len(np.unique(y[:,0]))-1  
+    return ipl_matches_array
+
+
+get_unique_matches_count()
+
+
+
+

q07_get_unique_teams_set/build.py

@@ -1,5 +1,31 @@
+# %load q07_get_unique_teams_set/build.py
 # Default imports
 from greyatomlib.python_intermediate.q05_read_csv_data.build import read_ipl_data_csv
-path = "data/ipl_matches_small.csv"
+
+#Path of the csv file to be passed onto function
+path = 'data/ipl_matches_small.csv'
 
 # Enter Code Here
+def get_unique_teams_set():
+
+    #Loading csv file
+    a = read_ipl_data_csv(path,dtype=None)
+
+    #creating empty set variables so that same team name doesn't get added repeatedly.
+    team1 = set() 
+    team2 = set()
+
+    #Looping thru list and getting inside tuple for team name fetching
+    for i,v in enumerate(a):
+        team1.add(a[i][3])
+        team2.add(a[i][4])
+
+    #returning union of two
+    return team1.union(team2)  # team1|team2 would do as well.
+
+#Call to a function - 
+get_unique_teams_set()
+
+
+
+

q08_get_total_extras/build.py

@@ -1,7 +1,23 @@
+# %load q08_get_total_extras/build.py
 # Default Imports
 from greyatomlib.python_intermediate.q05_read_csv_data.build import read_ipl_data_csv
 import numpy as np
 
 path = 'data/ipl_matches_small.csv'
 
-# Enter Code Here
+# Enter Code Here
+def get_total_extras():
+
+    #reading file using np.genfromtxt
+    a = np.genfromtxt(path,dtype=None,delimiter=',',skip_header=1)
+
+    #Creating an empty list to store extra runs.
+    extras = []
+
+    #Looping thru each deliveries' extra and storing the value in list
+    for i,v in enumerate(a):
+        extras.append(a[i][17])  #17th index is the extra column
+    return sum(extras)
+get_total_extras()
+
+