Add al files from local folder

Influxdataframe.py

@@ -0,0 +1,77 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Dec  2 07:46:09 2022
+
+@author: Daniel Häfliger
+"""
+import pandas as pd
+import Influxclient as I
+import influxdb_client
+
+
+# Returns values of an influxDB as they where specified in the config.xml 
+# as a Pandas Dataframe
+def Get_Df():
+
+
+    xfile = pd.read_xml('config.xml')
+    org = (xfile.loc[xfile['category'] == 'influx'].organisation[0])
+    token = (xfile.loc[xfile['category'] == 'influx'].influxtoken[0])
+    url = (xfile.loc[xfile['category'] == 'influx'].url[0])
+
+    client = influxdb_client.InfluxDBClient(
+        url=url,
+        token=token,
+        org=org
+    )
+
+    bucket = (xfile.loc[xfile['category'] == 'influx'].bucket[0])
+    measurement = (xfile.loc[xfile['category'] == 'influx'].measurement[0])
+
+    interval = (xfile.loc[xfile['category'] == 'influx'].interval[0])
+    valuessince = (xfile.loc[xfile['category'] == 'influx'].time[0])
+
+    Input = xfile.loc[xfile['category'] == 'feature'].f[1]
+    #numberofFeature=(xfile.loc[xfile['category']=='feature'].features[1])
+
+    feature = Input.split()
+    pred = xfile.loc[xfile['category'] == 'pred'].p1[2]
+   
+
+    data = {
+
+        "y_r": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[0],
+        "y_i": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[1],
+        "d_r": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[2],
+        "d_i": I.Get_Time(client, bucket, valuessince, measurement, feature[0])[3],
+
+    }
+
+    for i in range(len(feature)):
+        newd = {(feature[i]): I.Get_Value(client, bucket,
+                                          valuessince, measurement, feature[i])}
+        data.update(newd)
+
+    newd = {(pred): I.Get_Value(client, bucket,
+                                      valuessince, measurement, pred)}
+    data.update(newd)
+        
+    return pd.DataFrame(data)
+
+
+
+# Shifts the target variable and adds [shift_number] colums with the shiftet
+# values, then return the new Dataframe
+def ShiftTarget(df, shift_number, targetvariable):
+    dfziel = df[[targetvariable]].copy()
+    df = df.rename(columns={targetvariable:(targetvariable+str(0))})
+    dfziel = dfziel.rename(columns={targetvariable:(targetvariable+str(0))})
+
+    
+    
+    for i in range(shift_number):
+        dfziel = dfziel.rename(columns={(targetvariable+str(i)):targetvariable+str(i+1)})
+        dfziel = dfziel.shift(1)
+        df = pd.concat([df, dfziel], axis=1)
+ 
+    return df