mirror of
https://github.com/velocitatem/PHANTOM.git
synced 2026-05-31 16:43:36 +00:00
35 lines
1.0 KiB
Python
Executable File
35 lines
1.0 KiB
Python
Executable File
import pandas as pd
|
|
from procesing.steps.base import BaseContextStep
|
|
|
|
class ChunkByTimeWindowStep(BaseContextStep):
|
|
"""
|
|
Chunk dataframe into time windows.
|
|
Returns list of dicts with window metadata.
|
|
"""
|
|
|
|
def transform(self, df: pd.DataFrame):
|
|
if df.empty:
|
|
return []
|
|
|
|
df = df.copy()
|
|
ts_col = self.context.config.get('ts_col', 'ts')
|
|
window_size = self.context.window_size
|
|
|
|
# ensure datetime
|
|
if not pd.api.types.is_datetime64_any_dtype(df[ts_col]):
|
|
df[ts_col] = pd.to_datetime(df[ts_col])
|
|
|
|
df = df.sort_values(ts_col)
|
|
df['_window'] = df[ts_col].dt.floor(window_size)
|
|
|
|
chunks = []
|
|
for idx, (window_start, group) in enumerate(df.groupby('_window')):
|
|
chunks.append({
|
|
'window_start': window_start,
|
|
'window_end': window_start + pd.Timedelta(window_size),
|
|
'window_idx': idx,
|
|
'data': group.drop(columns=['_window'])
|
|
})
|
|
|
|
return chunks
|