Starting to investigate the fact that qualitative features with NaN

[predictops.git] / main.py

diff --git a/main.py b/main.py
index 426d3b580fdbed6586b7111ce6ffb17c1172824a..9e35b2da9acf12c39b784454a8c420dae5ce2bb4 100644 (file)
--- a/main.py
+++ b/main.py
@@ -1,5 +1,6 @@
 from predictops.engine import Engine
 from predictops.learn.preprocessing import Preprocessing
 from predictops.engine import Engine
 from predictops.learn.preprocessing import Preprocessing

+from predictops.target.all import All

 from predictops.target.toarea import ToArea
 
 from logging import getLogger
 from predictops.target.toarea import ToArea
 
 from logging import getLogger


@@ -24,6 +25,11 @@ if __name__ == '__main__':
     #print(engine.X[datetime.strptime('06/30/2010 21:00:00', '%m/%d/%Y %H:%M:%S')])
     print(process.dataframe.head(n=20))
     print(process.dataframe.tail(n=20))
     #print(engine.X[datetime.strptime('06/30/2010 21:00:00', '%m/%d/%Y %H:%M:%S')])
     print(process.dataframe.head(n=20))
     print(process.dataframe.tail(n=20))

+
+
+    target = All(stream_file = Path.cwd() / 'data' / 'targets' / 'sdis25' / 'interventions.csv')
+
+

     exit()
 
     depts = gpd.read_file( Path.cwd() / 'data' / 'targets' / 'departments' / "departements-20180101.shp")
     exit()
 
     depts = gpd.read_file( Path.cwd() / 'data' / 'targets' / 'departments' / "departements-20180101.shp")