mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
d051db1f14
* Add Simple Moving Average (SMA) Calculation This commit adds a Python script for calculating the Simple Moving Average (SMA) of a time series data. The script also includes a doctest that verifies the correctness of the SMA calculations for a sample dataset. Usage: - Run the script with your own time series data and specify the window size for SMA calculations. * Update financial/simple_moving_average.py Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com> * Update financial/simple_moving_average.py Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com> * Update financial/simple_moving_average.py Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update simple_moving_average.py * Update financial/simple_moving_average.py * Update simple_moving_average.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
"""
|
|
The Simple Moving Average (SMA) is a statistical calculation used to analyze data points
|
|
by creating a constantly updated average price over a specific time period.
|
|
In finance, SMA is often used in time series analysis to smooth out price data
|
|
and identify trends.
|
|
|
|
Reference: https://en.wikipedia.org/wiki/Moving_average
|
|
"""
|
|
from collections.abc import Sequence
|
|
|
|
|
|
def simple_moving_average(
|
|
data: Sequence[float], window_size: int
|
|
) -> list[float | None]:
|
|
"""
|
|
Calculate the simple moving average (SMA) for some given time series data.
|
|
|
|
:param data: A list of numerical data points.
|
|
:param window_size: An integer representing the size of the SMA window.
|
|
:return: A list of SMA values with the same length as the input data.
|
|
|
|
Examples:
|
|
>>> sma = simple_moving_average([10, 12, 15, 13, 14, 16, 18, 17, 19, 21], 3)
|
|
>>> [round(value, 2) if value is not None else None for value in sma]
|
|
[None, None, 12.33, 13.33, 14.0, 14.33, 16.0, 17.0, 18.0, 19.0]
|
|
>>> simple_moving_average([10, 12, 15], 5)
|
|
[None, None, None]
|
|
>>> simple_moving_average([10, 12, 15, 13, 14, 16, 18, 17, 19, 21], 0)
|
|
Traceback (most recent call last):
|
|
...
|
|
ValueError: Window size must be a positive integer
|
|
"""
|
|
if window_size < 1:
|
|
raise ValueError("Window size must be a positive integer")
|
|
|
|
sma: list[float | None] = []
|
|
|
|
for i in range(len(data)):
|
|
if i < window_size - 1:
|
|
sma.append(None) # SMA not available for early data points
|
|
else:
|
|
window = data[i - window_size + 1 : i + 1]
|
|
sma_value = sum(window) / window_size
|
|
sma.append(sma_value)
|
|
return sma
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import doctest
|
|
|
|
doctest.testmod()
|
|
|
|
# Example data (replace with your own time series data)
|
|
data = [10, 12, 15, 13, 14, 16, 18, 17, 19, 21]
|
|
|
|
# Specify the window size for the SMA
|
|
window_size = 3
|
|
|
|
# Calculate the Simple Moving Average
|
|
sma_values = simple_moving_average(data, window_size)
|
|
|
|
# Print the SMA values
|
|
print("Simple Moving Average (SMA) Values:")
|
|
for i, value in enumerate(sma_values):
|
|
if value is not None:
|
|
print(f"Day {i + 1}: {value:.2f}")
|
|
else:
|
|
print(f"Day {i + 1}: Not enough data for SMA")
|