From 382c3b50ed31eb9af9d1a9f96d6915a2ab94a135 Mon Sep 17 00:00:00 2001
From: Matt Dancho <mdancho@gmail.com>
Date: Wed, 4 Oct 2023 10:47:14 -0400
Subject: [PATCH] #46 start working on anomalize

---
 CHANGELOG.md                 |  5 +++++
 src/pytimetk/core/anomaly.py | 26 ++++++++++++++++++++++++++
 2 files changed, 31 insertions(+)
 create mode 100644 src/pytimetk/core/anomaly.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c991bf4a..ca57189e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,6 +2,11 @@
 
 ## pytimetk version 0.1.0.9000 (in development)
 
+New Functions:
+
+- `augment_expanding()`
+- `get_frequency()` 
+
 ## pytimetk version 0.1.0 (2023-10-02)
 
 Initial release. This release includes the following features:
diff --git a/src/pytimetk/core/anomaly.py b/src/pytimetk/core/anomaly.py
new file mode 100644
index 00000000..3c2e6a62
--- /dev/null
+++ b/src/pytimetk/core/anomaly.py
@@ -0,0 +1,26 @@
+import pandas as pd
+
+from pytimetk import ts_summary
+
+from statsmodels.tsa.seasonal import STL
+
+def stl_decompose(data, date_column, value_column, freq, trend, **kwargs):
+        
+    summary_df = ts_summary(data, date_column)
+    
+    # Decompose the time series
+    stl = STL(data[value_column], freq=freq, **kwargs)
+    res = stl.fit()
+    
+    # Build the dataframe containing the decomposed components
+    df = pd.DataFrame({
+        'date': data[date_column],
+        'value': data[value_column],
+        'trend': res.trend,
+        'seasonal': res.seasonal,
+        'residual': res.resid
+    })
+    
+    return df 
+    
+    
\ No newline at end of file