# NumPy: Compute the median of flattened given array

## NumPy Statistics: Exercise-5 with Solution

From Wikipedia: The median is the value separating the higher half from the lower half of a data sample (a population or a probability distribution). For a data set, it may be thought of as the "middle" value. For example, in the data set {1, 3, 3, 6, 7, 8, 9}, the median is 6, the fourth largest, and also the fifth smallest, number in the sample. For a continuous probability distribution, the median is the value such that a number is equally likely to fall above or below it.

The median is a commonly used measure of the properties of a data set in statistics and probability theory. The basic advantage of the median in describing data compared to the mean (often simply described as the "average") is that it is not skewed so much by extremely large or small values, and so it may give a better idea of a "typical" value.

Write a NumPy program to compute the median of flattened given array.

**Sample Solution**:-

**Python Code:**

```
import numpy as np
x = np.arange(12).reshape((2, 6))
print("\nOriginal array:")
print(x)
r1 = np.median(x)
print("\nMedian of said array:")
print(r1)
```

Sample Output:

Original array: [[ 0 1 2 3 4 5] [ 6 7 8 9 10 11]] Median of said array: 5.5

**Python Code Editor:**

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**Previous:** Write a NumPy program to compute the 80th percentile for all elements in a given array along the second axis.

**Next:** Write a NumPy program to compute the weighted of a given array.

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## Python: Tips of the Day

**Chain Operators**

You can chain comparison operators in Python as following: n = 10 result = 1 < n < 20

distance = 200 checker = 100 < distance < 350 print(checker)

Output:

True

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