How to use Python’s statistical functions?

In Python, there are numerous functions and modules for statistical analysis. Commonly used statistical functions include sum, mean, median, mode, variance, standard deviation, etc. Here are some commonly used statistical functions and how to use them:

1. sum function: used to calculate the sum of all elements in a list or array.

numbers = [1, 2, 3, 4, 5]
total = sum(numbers)
print(total)  # 输出：15

1. mean function: used to calculate the average value of all elements in a list or array.

import statistics

numbers = [1, 2, 3, 4, 5]
average = statistics.mean(numbers)
print(average)  # 输出：3

1. Median function: used to calculate the median of all elements in a list or array.

import statistics

numbers = [1, 2, 3, 4, 5]
middle = statistics.median(numbers)
print(middle)  # 输出：3

1. Mode function: used to calculate the mode of all elements in a list or array.

import statistics

numbers = [1, 2, 3, 3, 4, 5]
most_common = statistics.mode(numbers)
print(most_common)  # 输出：3

1. The variance function is used to calculate the variance of all elements in a list or array.

import statistics

numbers = [1, 2, 3, 4, 5]
variance = statistics.variance(numbers)
print(variance)  # 输出：2.5

1. The stdev function is used to calculate the standard deviation of all elements in a list or array.

import statistics

numbers = [1, 2, 3, 4, 5]
std_deviation = statistics.stdev(numbers)
print(std_deviation)  # 输出：1.5811388300841898

It is important to note that statistics is a built-in module in Python and needs to be imported using the import statement in order to use its functions. Additionally, more complex statistical analysis can be done using third-party libraries such as numpy and pandas.