From dict to dataframe: done

[predictops.git] / main.py

diff --git a/main.py b/main.py
index b43c188627d52c218cb527d5dce3ee16dde1575d..fe8ed203fe9fd78a2f61b98fed7a0474a4b3d3bd 100644 (file)
--- a/main.py
+++ b/main.py
@@ -1,8 +1,9 @@
 from predictops.source.ephemeris import Ephemeris
 from predictops.source.meteofrance import MeteoFrance
+from predictops.learn.preprocessing import Preprocessing
 from predictops.target.toarea import ToArea
 
-from datetime import datetime
+from datetime import datetime, timedelta
 from logging import getLogger
 from logging.config import fileConfig
 from pathlib import Path
@@ -16,7 +17,6 @@ logger = getLogger()
 
 class Engine:
     def __init__(self, start = None, end = None, time_step = None):
-        logger.info("Predictops engine launched")
         self._X = {}
         self._Y = {}
 
@@ -69,11 +69,19 @@ engine.add_feature(name = 'ephemeris',
                    features = ['hour', 'dayInWeek', 'dayInMonth', 'dayInYear',
                                'weekInYear', 'month', 'year'])
 
-print(engine.X[datetime.strptime('06/30/2010 21:00:00', '%m/%d/%Y %H:%M:%S')])
+process = Preprocessing(dict_features = engine.X,
+                   start = start, end = end, timestep = timedelta(hours=1))
+
+process.fill_na()
+print(process.dataframe.head(n=20))
+#print(engine.X[datetime.strptime('06/30/2010 21:00:00', '%m/%d/%Y %H:%M:%S')])
+
+exit()
 
 depts = gpd.read_file( Path.cwd() / 'data' / 'targets' / 'departments' / "departements-20180101.shp")
 Doubs = depts.loc[depts['nom'] == 'Doubs'].iloc[0]
 
 ToArea(area=Doubs.geometry,
-       start = start, end = end)
+       start = start, end = end,
+       csv_file = Path.cwd() / 'data' / 'targets' / 'sdis25' / 'interventions.csv')