The seasonal_decompose function in the hana_ml.algorithms.pal.tsa module tests for seasonality in a time series and decomposes it into seasonal, trend, and random components using various parameters such as the autocorrelation coefficient criterion, thread ratio, decompose type, and others.
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Here is a Python code template for the `seasonal_decompose` function from the `hana_ml.algorithms.pal.tsa.seasonal_decompose` module:

```python
# Import required modules
from hana_ml import DataFrame
from hana_ml.algorithms.pal.tsa import seasonal_decompose

# Create a connection to HANA
connection_context = ... # create a connection to HANA

# Create a DataFrame
data = DataFrame(connection_context, 'SELECT * FROM <your_table>')

# Define parameters
key = 'ID'
endog = 'SERIES'
alpha = 0.2
thread_ratio = 0.5
decompose_type = 'auto'
extrapolation = False
smooth_width = 0
auxiliary_normalitytest = False
periods = None
decompose_method = 'traditional'
stl_robust = True
stl_seasonal_average = False
smooth_method_non_seasonal = 'moving_average'

# Perform seasonal decomposition
stats, decompose = seasonal_decompose(data=data, 
                                      key=key, 
                                      endog=endog, 
                                      alpha=alpha, 
                                      thread_ratio=thread_ratio, 
                                      model=decompose_type, 
                                      decompose_type=decompose_type, 
                                      extrapolation=extrapolation, 
                                      smooth_width=smooth_width, 
                                      auxiliary_normalitytest=auxiliary_normalitytest, 
                                      periods=periods, 
                                      decompose_method=decompose_method, 
                                      stl_robust=stl_robust, 
                                      stl_seasonal_average=stl_seasonal_average, 
                                      smooth_method_non_seasonal=smooth_method_non_seasonal)

# Print results
print(stats.collect())
print(decompose.collect())
```

Please replace `<your_table>` with the name of your table in the HANA database. Also, you need to replace the `connection_context` with your actual HANA connection.