Compute Statistical properties of NumPy array with SciPy
NumPy: Integration with SciPy Exercise-1 with Solution
Write a NumPy program that creates a NumPy array of random numbers and uses SciPy to compute the statistical properties (mean, median, variance) of the array.
Sample Solution:
Python Code:
# Import necessary libraries
import numpy as np
from scipy import stats
# Create a NumPy array of random numbers
data = np.random.rand(100)
# Compute the mean of the array using SciPy
mean = stats.tmean(data)
# Compute the median of the array using SciPy
median = np.median(data)
# Compute the variance of the array using SciPy
variance = stats.tvar(data)
# Print the statistical properties
print("Mean:", mean)
print("Median:", median)
print("Variance:", variance)
Output:
Mean: 0.4879592058849749 Median: 0.49297261150369925 Variance: 0.09259159781167492
Explanation:
- Import the necessary libraries:
- Import NumPy and SciPy's "stats" module.
- Create a NumPy array of random numbers:
- Generate an array of 100 random numbers between 0 and 1.
- Compute the mean:
- Use SciPy's tmean function to calculate the mean of the array.
- Compute the median:
- Use NumPy's median function to calculate the median of the array.
- Compute the variance:
- Use SciPy's tvar function to calculate the variance of the array.
- Finally display the mean, median, and variance.
Python-Numpy Code Editor:
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