How to Use Statistical Functions from Python Numpy Module?
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Condition for Statistical Functions from Python Numpy Module
Description:
NumPy is a powerful numerical computing library in Python that provides a wide range of statistical
functions to perform operations such as mean, median, standard deviation, variance, etc.,
on arrays of data.
Step-by-Step Process
np.mean():
Returns the mean (average) of the elements.
np.median():
Returns the median (middle value) of the elements.
np.std():
Returns the standard deviation, a measure of the spread of the dataset.
np.var():
Returns the variance, showing how spread out the numbers are.
np.min():
Returns the smallest value.
np.max():
Returns the largest value.
np.sum():
Returns the sum of all elements.
np.percentile():
Returns the nth percentile of the data.
Sample Code
print("Output for Statistical function:")
import numpy as np
data = np.array([12, 15, 10, 20, 25, 30, 35, 40, 50])
# Mean
mean_value = np.mean(data)
print(f"Mean: {mean_value}")
print()
# Median
median_value = np.median(data)
print(f"Median: {median_value}")
print()
# Standard Deviation
std_deviation = np.std(data)
print(f"Standard Deviation: {std_deviation}")
print()
# Variance
variance = np.var(data)
print(f"Variance: {variance}")
print()
# Minimum and Maximum
min_value = np.min(data)
max_value = np.max(data)
print(f"Min: {min_value}")
print(f"Max: {max_value}")
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