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The Quick and Easy Way to Analyze Numpy Arrays

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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

Print Dictionary Values Simplified Logic


Here's for loop logic that says how to use Dictionary to get its data. I will present here how to use it as input In for loop. You can also call Dictionary as Map, Hash, or Associative array.


Print dictionary values

Here is way to print dictionary values using for loop

Below is my example. I have created a simple Dictionary called 'store.' Then, I will get its data using for-loop. Here's my previous post Python -  How to Lookup Dictionary By Key.


Dictionary example

Store = { "rao" : 1, "srini' : 2}


For-loop logic

for key in store:
     print(key, store[key])


Laptop batteries can last longer if you charge them up to only 80% instead of the full 100%. - By Lifehack.org

Real-time result

The execution of for loop showed here. It's much simple. Just use the code as I did. You'll get the desired result quickly.


How to use for loop on Dictionary Useful Example


References

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