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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 Lambda Function Quickly in Python: 5 Examples

Here are the top python lambda function examples for your project and interviews. "Python's lambda functions are a powerful way to create small, anonymous functions on the fly. In this post, we'll explore some examples of how to use lambda functions in Python.

5 Best Python Lambda Function Examples

Lambda in python

#1 Sorting a List of Tuples by the Second Element

This lambda function sorts a list of tuples based on the second element of each tuple.

python code

my_list = [(1, 2), (4, 1), (9, 10), (13, 6), (5, 7)]

sorted_list = sorted(my_list, key=lambda x: x[1])



[(4, 1), (1, 2), (13, 6), (5, 7), (9, 10)]

** Process exited - Return Code: 0 **

Press Enter to exit terminal

#2 Finding the Maximum Value in a List of Dictionaries

This lambda function finds the maximum value in a list of dictionaries based on a specific key.

python code

my_list = [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 30}, {'name': 'Charlie', 'age': 20}]

max_age = max(my_list, key=lambda x: x['age'])



{'name': 'Bob', 'age': 30}

** Process exited - Return Code: 0 **

Press Enter to exit terminal

#3 Multiplying Two Lists Element-Wise

This lambda function multiplies two lists element-wise and returns the result as a new list.

python code

list1 = [1, 2, 3, 4]

list2 = [5, 6, 7, 8]

result = list(map(lambda x, y: x * y, list1, list2))



[5, 12, 21, 32]

** Process exited - Return Code: 0 **

Press Enter to exit terminal

#4 Filtering a List of Integers

This lambda function filters a list of integers and returns only the even numbers.

python code

my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

even_numbers = list(filter(lambda x: x % 2 == 0, my_list))



[2, 4, 6, 8, 10]

** Process exited - Return Code: 0 **

Press Enter to exit terminal

#5 Creating a Function That Returns a Function

This lambda function creates a function that returns another function that adds a constant value to its input.

python code

def add_constant(const):

    return lambda x: x + const

add5 = add_constant(5)

add10 = add_constant(10)






** Process exited - Return Code: 0 **

Press Enter to exit terminal

In the above example, add_constant is a function that returns a lambda function that adds the constant value to its input. add5 and add10 are two different functions that add 5 and 10 to their input, respectively.



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