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The Quick and Easy Way to Analyze Numpy Arrays

The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

How to Write Complex Python Program Using Functions

Complex Python program using functions

Here is an example of complex python program written using functions. Many times, in job interviews, you need to give a written test. There, you may need to answer tricky programs. Historically, people are afraid to take a test. Especially in python

Complex Python programs

Below are the Complex Python Program Using Functions and examples of how to write the code.
  1. Counting lower and upper case letters
  2. Creating a list

1. Counting lower and upper case letters

Below program counts the upper and lower case letters.

def count_lower_upper(s): dlu = {'Lower': 0, 'Upper': 0} for ch in s: if ch.islower(): dlu['Lower'] += 1 elif ch.isupper(): dlu['Upper'] += 1 return(dlu) d = count_lower_upper('James BOnd') print(d) d = count_lower_upper('Anant Amrut Mahalle') print(d)

python function program

Also read: How to Lose Your Weight

2. Creating a List

Here it uses two input lists for creating a new list. Additionally, it uses the list built-in function. 

def create_list(l1, l2): l3 = list(set(l1) & set(l2)) return(l3) lst1 = [10, 20, 30, 40, 50] lst2 = [1, 2, 3, 40, 10] lst3 = create_list(lst1, lst2) print(lst3)

tricky python program



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