mk趋势检验Python代码

Sure! Here's an example of how you can perform the Mann-Kendall trend test in Python using the `pymannkendall` library:

import numpy as np
from pymannkendall import mk_test

# Generate a sample dataset
data = np.random.random(100)

# Perform Mann-Kendall test
result = mk_test(data)

# Print the test statistic and p-value
print("Mann-Kendall test statistic:", result[0])
print("Mann-Kendall p-value:", result[1])

In this code, we first import the necessary libraries, `numpy` for generating sample data and `pymannkendall` for performing the Mann-Kendall test. Then, we generate a sample dataset, `data`, which could be your actual data.

Next, we call the `mk_test` function from `pymannkendall` and pass our data as an argument. The function returns a tuple containing the test statistic and p-value.

Finally, we print the test statistic and p-value to see the results of the Mann-Kendall trend test.

Make sure you have the `pymannkendall` library installed before running this code. You can install it using pip: `pip install pymannkendall`.