How to Perform a Mann-Kendall Trend Test in Python

How to Perform a Mann-Kendall Trend Test in Python

The Mann-Kendall Trend Test is a non-parametric test that is used to identify a trend in a series of values without making any assumptions about the distribution of values. It's commonly used in environmental sciences and meteorology to assess the trends in climatic and hydrologic time series.

To perform a Mann-Kendall Trend Test in Python, you can use the scipy.stats.kendalltau function, which computes the Kendall tau correlation coefficient, or the mk_test function from the pymannkendall package, which is specifically designed for this test.

Let's go through both methods:

Method 1: Using scipy.stats.kendalltau

import numpy as np from scipy.stats import kendalltau # Sample data data = np.array([12, 9, 10, 11, 13, 14, 13, 15, 12, 16, 17, 19]) # Perform Kendall tau correlation test tau, p_value = kendalltau(np.arange(len(data)), data) print(f'Kendall tau correlation: {tau:.3f}') print(f'P-value: {p_value:.3f}') # Interpretation alpha = 0.05 # or 0.01 for a 1% significance level if p_value < alpha: print('The trend is significant.') else: print('The trend is not significant.')

Method 2: Using pymannkendall package

First, install pymannkendall if you haven't:

pip install pymannkendall

Then perform the test:

import pymannkendall as mk import numpy as np # Sample data data = np.array([12, 9, 10, 11, 13, 14, 13, 15, 12, 16, 17, 19]) # Perform Mann-Kendall trend test result = mk.original_test(data) print(result)

The result will be an object containing the test statistics, p-value, and other information. You can interpret the trend based on the p-value as in the first method.

Note on Trend Interpretation

The Mann-Kendall test can detect a trend, but it doesn't tell you anything about the magnitude of the trend. To determine whether the trend is increasing or decreasing, you can look at the sign of the Kendall tau statistic. A positive tau indicates an increasing trend, while a negative tau indicates a decreasing trend.

Remember, a significant trend does not necessarily imply a large or important trend. It simply means that there is evidence of a consistent upward or downward movement in the dataset over time. Always consider the practical significance of the trend in addition to its statistical significance.

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