more data in collection df

BAD_CONTAINERS.txt

+70b3d500700016dE
+70b3d500700016dF
+70b3d500700016E6
+70b3d500700016EB
+70b3d500700016F2
+70b3d500700016F4
+70b3d500700016F7
+70b3d500700016FC
+70b3d50070001700
+70b3d50070001701
+70b3d50070001708
+70b3d5007000170F
+70b3d50070001712
+70b3d50070001713
+70b3d50070001714
+70b3d50070001715
+70b3d5007000171A
+70b3d5007000171E
+70b3d5007000171F
+70b3d50070001722
+70b3d50070001727
+70b3d5007000172B
+70b3d5007000172C
+70b3d5007000172D
+70b3d50070001731
+70b3d50070001733
+70b3d50070001736
+70b3d5007000173A
+70b3d50070001740
+70b3d50070001743
+70b3d5007000174D
+70b3d50070001750
+70b3d50070001759
+70b3d5007000175A
+70b3d5007000175E
+70b3d50070001764
+70b3d50070001766
+70b3d50070001770
+70b3d50070001774
+70b3d50070001779
+70b3d5007000177C
+70b3d50070001780
+70b3d50070001782
+70b3d50070001786
+70b3d50070001789
\ No newline at end of file

notebooks/Visualization_Data.ipynb

-%% Cell type:code id:cd589004 tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 import json
 from pandas.io.json import json_normalize
 import plotly.graph_objects as go
 import os
 from ipywidgets import interact, interact_manual
 import ipywidgets as widgets
 import datetime
 ```
 
-%% Cell type:code id:4d82190b tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 file=os.getcwd()
 file_m=file[0:(len(file)-9)]
 file_dz='data\\raw'
 file_data=file_m+file_dz
 file_data
 data_name=os.listdir(file_data)
 ```
 
-%% Cell type:code id:6e8c589f tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 def load_data(container: str,start,end):
 
     file_number=file_m+file_dz+'\\'+container+'.txt'
     df = pd.read_json(file_number, lines=True)
     raw_data = pd.DataFrame(df[1][0])
     raw_data["time"]=pd.to_datetime(list(map(lambda st: str(st)[0:10],raw_data["created_at"])))
 
     raw_data_z1=raw_data[raw_data["time"]>=pd.to_datetime(start)]
     raw_data_z2=raw_data_z1[raw_data_z1["time"]<=pd.to_datetime(end)]
 
     return raw_data_z2
 ```
 
-%% Cell type:code id:733b95fb tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 def dec_data(data,sensor: str):
     df_decoded_data = pd.json_normalize(data.decoded_data)
 
     if sensor=='Height 1 (cm)':
         df_decoded_data["Height 1 (cm)"] =  df_decoded_data["sensor_data.Height 1"].str.replace("cm","").astype(int)
     elif sensor=='Height 2 (cm)':
         df_decoded_data["Height 2 (cm)"] =  df_decoded_data["sensor_data.Height 2"].str.replace("cm","").astype(int)
     elif sensor=='Height 3 (cm)':
         df_decoded_data["Height 3 (cm)"] =  df_decoded_data["sensor_data.Height 3"].str.replace("cm","").astype(int)
     elif sensor=='Height 4 (cm)':
         df_decoded_data["Height 4 (cm)"] =  df_decoded_data["sensor_data.Height 4"].str.replace("cm","").astype(int)
     elif sensor=='Voltage (mV)':
         df_decoded_data["Voltage (mV)"] =  df_decoded_data["sensor_data.Voltage"].str.replace("mV","").astype(int)
     elif sensor=='Temperature (C)':
         df_decoded_data["Temperature (C)"] =  df_decoded_data["sensor_data.Temperature"].str.replace("C","").astype(int)
     elif sensor=='Tilt (Degree)':
         df_decoded_data["Tilt (Degree)"] =  df_decoded_data["sensor_data.Tilt"].str.replace("Degree","").astype(int)
 
 
     return df_decoded_data
 ```
 
-%% Cell type:code id:d9cd2aab tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 sensor_list=['Height 1 (cm)', 'Height 2 (cm)','Height 3 (cm)','Height 4 (cm)','Voltage (mV)','Temperature (C)','Tilt (Degree)']
 
 fig = go.FigureWidget()
 fig.add_scatter()
 
 
 @interact(Container=list(map(lambda st: str.replace(st, '.txt', ''), data_name)),Sensor=list(sensor_list),
           Start_date=widgets.DatePicker(value=pd.to_datetime('2020-05-09')),
           End_date=widgets.DatePicker(value=pd.to_datetime('2021-05-08')),
           Mittelwert=False,Median=False,Erwartungswert_plus_minus_Standardabweichung=False,Quantil_75=False,Quantil_25=False,
           Varianz=False)
 
 def update(Container='70b3d50070001704',Sensor='Height 1',Start_date=pd.to_datetime('2020-05-09'),End_date=pd.to_datetime('2021-05-08'),
            Mittelwert=False,Median=False,Erwartungswert_plus_minus_Standardabweichung=False,
            Quantil_75=False,Quantil_25=False,Varianz=False):
     raw_data=load_data(Container,Start_date,End_date)
     decoded_data=dec_data(raw_data,Sensor)
     with fig.batch_update():
         fig.data[0].x=raw_data.created_at.tolist()
         fig.data[0].y=decoded_data[Sensor].tolist()
         fig.data[0].name=Sensor
         fig.update_layout(title=str('Data Vizualisation Container:'+str(Container)),xaxis_title="Time",yaxis_title=Sensor)
 
 
         if Mittelwert==True:
             fig.add_scatter()
             fig.data[1].x=raw_data.created_at.tolist()
             fig.data[1].y=np.ones(len(raw_data.created_at.tolist()))*np.mean(decoded_data[Sensor].tolist())
             fig.data[1].name="Arith. Mittel"
         if Mittelwert==False:
             fig.add_scatter()
             fig.data[1].x=[]
             fig.data[1].y=[]
 
         if Median==True:
             fig.add_scatter()
             fig.data[2].x=raw_data.created_at.tolist()
             fig.data[2].y=np.ones(len(raw_data.created_at.tolist()))*np.median(decoded_data[Sensor].tolist())
             fig.data[2].name="Median"
         if Median==False:
             fig.add_scatter()
             fig.data[2].x=[]
             fig.data[2].y=[]
 
 
         if Quantil_75==True:
             fig.add_scatter()
             fig.data[3].x=raw_data.created_at.tolist()
             fig.data[3].y=np.ones(len(raw_data.created_at.tolist()))*np.quantile(decoded_data[Sensor].tolist(),0.75)
             fig.data[3].name="75%-Quantil"
         if Quantil_75==False:
             fig.add_scatter()
             fig.data[3].x=[]
             fig.data[3].y=[]
 
 
         if Quantil_25==True:
             fig.add_scatter()
             fig.data[4].x=raw_data.created_at.tolist()
             fig.data[4].y=np.ones(len(raw_data.created_at.tolist()))*np.quantile(decoded_data[Sensor].tolist(),0.25)
             fig.data[4].name="25%-Quantil"
         if Quantil_25==False:
             fig.add_scatter()
             fig.data[4].x=[]
             fig.data[4].y=[]
 
         if Erwartungswert_plus_minus_Standardabweichung==True:
             fig.add_scatter()
             fig.data[5].x=raw_data.created_at.tolist()
             fig.data[5].y=np.ones(len(raw_data.created_at.tolist()))*np.mean(decoded_data[Sensor].tolist())+np.ones(len(raw_data.created_at.tolist()))*np.sqrt(np.var(decoded_data[Sensor].tolist()))
             fig.data[5].name="E+stdev"
             fig.add_scatter()
             fig.data[6].x=raw_data.created_at.tolist()
             fig.data[6].y=np.ones(len(raw_data.created_at.tolist()))*np.mean(decoded_data[Sensor].tolist())-np.ones(len(raw_data.created_at.tolist()))*np.sqrt(np.var(decoded_data[Sensor].tolist()))
             fig.data[6].name="E-stdev"
         if Erwartungswert_plus_minus_Standardabweichung==False:
             fig.add_scatter()
             fig.data[5].x=[]
             fig.data[5].y=[]
             fig.add_scatter()
             fig.data[6].x=[]
             fig.data[6].y=[]
 
         if Varianz==True:
             fig.add_scatter()
             fig.data[7].x=raw_data.created_at.tolist()
             fig.data[7].y=np.ones(len(raw_data.created_at.tolist()))*np.var(decoded_data[Sensor].tolist())
             fig.data[7].name="Variance"
         if Varianz==False:
             fig.add_scatter()
             fig.data[7].x=[]
             fig.data[7].y=[]\
 
 fig
 ```
 
 %%%% Output: display_data
 
 
 %%%% Output: display_data
 
 
-%% Cell type:code id:4f8b1bcf tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 raw_data
 ```
 
 %%%% Output: error
 
     ---------------------------------------------------------------------------
     NameError                                 Traceback (most recent call last)
-    <ipython-input-17-6b6e5e7f1078> in <module>
+    <ipython-input-6-6b6e5e7f1078> in <module>
     ----> 1 raw_data
 
     NameError: name 'raw_data' is not defined
 
-%% Cell type:code id:5e5d7e8c tags:
+%% Cell type:code id: tags:
 
-``` python
+``` 
 ```