Optimized code for better readability.

Author: Juzer Shakir

How_to_Python/Modules/Numpy/Numpy_operation_2.py

@@ -17,84 +17,84 @@
 a = np.array([(1, 2, 3), (4, 5, 6)])
 
 #----9
-#Finding sum of the elemnts by columns
-#axis = 0 means column
-colsum = a.sum(axis = 0)
+# Finding sum of the elemnts by columns
+# axis = 0 means column
+colsum = a.sum(axis=0)
 print("\nThe sum of all the value in the array by columns are {}".format(colsum))
-#Finding sum of the elemnts by rows
-#axis = 1 means rows
-rowsum = a.sum(axis = 1)
+# Finding sum of the elemnts by rows
+# axis = 1 means rows
+rowsum = a.sum(axis=1)
 print("\nThe sum of all the value in the array by rows are {}".format(rowsum))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #----10
-#Finding sqaure root of each element in the array
+# Finding sqaure root of each element in the array
 sqrt = np.sqrt(a)
 print("\nThe sqaure root of each elements are \n{}".format(sqrt))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #----11
-#Finding standard deviation of the array
+# Finding standard deviation of the array
 stnd = np.std(a)
 print("\nThe standard deviation of array is \n{}".format(stnd))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
-#lets set another numpy array for performing arithmetic calculations
+# lets set another numpy array for performing arithmetic calculations
 b = np.array([(10, 11, 12), (13, 14, 15)])
 print("\nAnother numpy array given for calculations \n{}".format(b))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #-----12
-#Finding the sum of two arrays
+# Finding the sum of two arrays
 asumb = a + b
 print("\nThe sum of two arrays are \n{}".format(asumb))
-#Finding the substraction of two arrays
+# Finding the substraction of two arrays
 aminusb = a - b
 print("\nThe substraction of two arrays are \n{}".format(aminusb))
-#Finding the multiplication of two arrays
+# Finding the multiplication of two arrays
 amultib = a * b
 print("\nThe multiplication of two arrays are \n{}".format(amultib))
-#Finding the division of two arrays
+# Finding the division of two arrays
 adivb = a / b
 print("\nThe division of two arrays are \n{}".format(adivb))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #---13
-#Concatinating numpy's vertically
+# Concatinating numpy's vertically
 vstack = np.vstack((a, b))
 print("\nVertically stacked numpy's \n{}".format(vstack))
-#Concatinating numpy's horizontally
+# Concatinating numpy's horizontally
 hstack = np.hstack((a, b))
 print("\nHorizontally stacked numpy's \n{}".format(hstack))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #----14
-#Combining columns of a numpy into a single column
+# Combining columns of a numpy into a single column
 single_a = a.ravel()
 print("\nThe first numpy array now have a single column\n{}".format(single_a))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #----15
-#Exponential function
+# Exponential function
 ex_a = np.exp(a)
 print("\nThe elements of the first numpy array raised to the e power =\n{}".format(ex_a))
-#logarithmic function
-#natural logarithmic (ln)
+# logarithmic function
+# natural logarithmic (ln)
 log_a = np.log(a)
 print("\nThe natural log of the elements of the first numpy array =\n{}".format(log_a))
-#logarithmic (ln) with base 10 or log
+# logarithmic (ln) with base 10 or log
 log_a = np.log10(a)
 print("\nThe log with base 10 of the elements of the first numpy array =\n{}".format(log_a))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 #---16
-#the first value passed in the argument will be the value to start with
-#second will be the value to end at
-#third will be how many numbers do you want in between first and second arguments
+# the first value passed in the argument will be the value to start with
+# second will be the value to end at
+# third will be how many numbers do you want in between first and second arguments
 al = np.linspace(1, 5, 10)
 print("\nThese are 10 numbers in between 1 and 5 \n{}".format(al))
 """----------------------------------------------------------------------------------------------------------------------------------------------------------"""
 
 
-#That's it!
+# That's it!
 print("\nThe End!")