AttributeError: 'Timestamp' object has no attribute 'items' - when y_pred = model.predict_one(x) #1084

XaviMartiCamarasa · 2022-11-09T08:16:17Z

XaviMartiCamarasa
Nov 9, 2022

Hi.
I'm just replaying the example on AirlinePassengers for building a simple nowcasting model, but with my data.
I'm getting this error: AttributeError: 'Timestamp' object has no attribute 'items' - when y_pred = model.predict_one(x)

TE code is below

data_orig = pd.read_csv('C:/Users/jrmr/Master/TFM/PEC3/hungary_chickenpox/hungary_chickenpox.csv')
data_orig['Date'] = pd.to_datetime(data_orig['Date'],format="%d/%m/%Y") # convertimos a fecha
data_orig.set_index('Date', inplace=True)

#Chickepox 
from river import compose
from river import linear_model
from river import preprocessing


def get_ordinal_date(x):
    return {'ordinal_date': x['month'].toordinal()}


model_pox = compose.Pipeline(
   
    ('scale', preprocessing.StandardScaler()),
    ('lin_reg', linear_model.LinearRegression())
)

from river import metrics
from river import utils
import matplotlib.pyplot as plt


def evaluate_model(model): 

    metric = utils.Rolling(metrics.MAE(), 12)

    dates = []
    y_trues = []
    y_preds = []

    for x, y in df_BUDAPEST.T.iteritems():
     

       # print(x)

        # Obtain the prior prediction and update the model in one go
        y_pred = model.predict_one(x)
        model.learn_one(x, y)

        # Update the error metric
        metric.update(y, y_pred)

        # Store the true value and the prediction
[hungary_chickenpox.csv](https://github.com/online-ml/river/files/9968858/hungary_chickenpox.csv)

        dates.append(x['monthevaluate_model(model_pox)
        y_trues.append(y)
        y_preds.append(y_pred)

    # Plot the results
    fig, ax = plt.subplots(figsize=(10, 6))
    ax.grid(alpha=0.75)
    ax.plot(dates, y_trues, lw=3, color='#2ecc71', alpha=0.8, label='Ground truth')
    ax.plot(dates, y_preds, lw=3, color='#e74c3c', alpha=0.8, label='Prediction')
    ax.legend()
    ax.set_title(metric)

evaluate_model(model_pox)

hungary_chickenpox.csv

Answered by XaviMartiCamarasa

Nov 9, 2022

Understood Max

View full answer

MaxHalford · 2022-11-09T08:46:43Z

MaxHalford
Nov 9, 2022
Maintainer

Hey there. The x you pass to learn_one and predict_one is a dictionary of features. It seems to me you're passing a datetime object.

I would suggest rerunning the original example yourself, and printing the objects to get an understanding of them.

4 replies

XaviMartiCamarasa Nov 9, 2022
Author

Now I changed a little bit the code and still get another error


from river import dummy, stats, metrics
from river import linear_model
from datetime import datetime

model_regresion=linear_model.LinearRegression()

for date, value in df_BUDAPEST.T.iteritems():

  dict_date={}
  dict_date["month"]=date.to_pydatetime()

  print (type(dict_date))
  print (dict_date["month"])
  print("value",value)

  model_regresion.learn_one (dict_date,value)
  y_pred = model_regresion.predict_one(dict_date)
  print(y_pred)

MaxHalford Nov 9, 2022
Maintainer

That's normal. The features you pass to a linear regression must be numbers, like most machine learning algorithm.

It seems to me the issues you're having are more related to your understanding of the models you're using, more so than River itself. I would suggest taking a step back, and trying to understand the model you're using.

XaviMartiCamarasa Nov 9, 2022
Author

For Static Regressor should be the same? it worked with datetime!

For the issue I had, I changed the datetime for its ordinal number and worked as expected. Many thanks!

smastelini Nov 9, 2022
Maintainer

Hi @XaviMartiCamarasa, the StatisticRegressor is one of the simplest baselines. It works by completely ignoring the supplied x and uses a applies a statistic on y. That is why it worked in your example.

Still, x is expected to be a dictionary of features for most River models.

XaviMartiCamarasa · 2022-11-09T10:00:20Z

XaviMartiCamarasa
Nov 9, 2022
Author

Understood Max

…

On Wed, Nov 9, 2022 at 10:24 AM Max Halford ***@***.***> wrote: That's normal. The features you pass to a linear regression must be numbers, like most machine learning algorithm. It seems to me the issues you're having are more related to your understanding of the models you're using, more so than River itself. I would suggest taking a step back, and trying to understand the model you're using. — Reply to this email directly, view it on GitHub <#1084 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HELZO7XFKYBIPJCAXE6DWHNUTZANCNFSM6AAAAAAR3E5DTE> . You are receiving this because you authored the thread.Message ID: ***@***.***>

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

0 replies

XaviMartiCamarasa · 2022-11-09T10:44:13Z

XaviMartiCamarasa
Nov 9, 2022
Author

Cool, thanks!

…

On Wed, Nov 9, 2022 at 11:25 AM Saulo Martiello Mastelini < ***@***.***> wrote: Hi @XaviMartiCamarasa <https://github.com/XaviMartiCamarasa>, the StatisticRegressor is one of the simplest baselines. It works by completely ignoring the supplied x and uses a applies a statistic on y. That is why it worked in your example. Still, x is expected to be a dictionary of features for most River models. — Reply to this email directly, view it on GitHub <#1084 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A37HELYINLBIP2NUKGHMIFDWHN33FANCNFSM6AAAAAAR3E5DTE> . You are receiving this because you were mentioned.Message ID: ***@***.***>

-- INFORMACIÓ SOBRE PROTECCIÓ DE DADES DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Us informem que les vostres dades identificatives i les contingudes en els missatges electrònics i fitxers adjunts es poden incorporar a les nostres bases de dades amb la finalitat de gestionar les relacions i comunicacions vinculades a la UOC, i que es poden conservar mentre es mantingui la relació. Si ho voleu, podeu exercir el dret a accedir a les vostres dades, rectificar-les i suprimir-les i altres drets reconeguts normativament adreçant-vos a l'adreça de correu emissora o a ***@***.*** ***@***.***>. Aquest missatge i qualsevol fitxer que porti adjunt, si escau, tenen el caràcter de confidencials i s'adrecen únicament a la persona o entitat a qui s'han enviat. Així mateix, posem a la vostra disposició un delegat de protecció de dades que no només s'encarregarà de supervisar tots els tractaments de dades de la nostra entitat, sinó que us podrà atendre per a qualsevol qüestió relacionada amb el tractament de dades. La seva adreça de contacte és ***@***.*** ***@***.***>. INFORMACIÓN SOBRE PROTECCIÓN DE DATOS DE LA UNIVERSITAT OBERTA DE CATALUNYA (UOC) Os informamos de que vuestros datos identificativos y los contenidos en los mensajes electrónicos y ficheros adjuntos pueden incorporarse a nuestras bases de datos con el fin de gestionar las relaciones y comunicaciones vinculadas a la UOC, y de que pueden conservarse mientras se mantenga la relación. Si lo deseáis, podéis ejercer el derecho a acceder a vuestros datos, rectificarlos y suprimirlos y otros derechos reconocidos normativamente dirigiéndoos a la dirección de correo emisora o a ***@***.*** ***@***.***>. Este mensaje y cualquier fichero que lleve adjunto, si procede, tienen el carácter de confidenciales y se dirigen únicamente a la persona o entidad a quien se han enviado. Así mismo, ponemos a vuestra disposición a un delegado de protección de datos que no solo se encargará de supervisar todos los tratamientos de datos de nuestra entidad, sino que podrá atenderos para cualquier cuestión relacionada con el tratamiento de datos. Su dirección de contacto es ***@***.*** ***@***.***>. UNIVERSITAT OBERTA DE CATALUNYA (UOC) DATA PROTECTION INFORMATION Your personal data and the data contained in your email messages and attached files may be stored in our databases for the purpose of maintaining relations and communications linked to the UOC, and the data may be stored for as long as these relations and communications are maintained. If you so wish, you can exercise your rights to access, rectification and erasure of your data, and any other legally held rights, by writing to the sender’s email address or ***@***.*** ***@***.***>. This message and, where applicable, any attachments are confidential and addressed solely to the individual or organization they were sent to. The UOC has a data protection officer who not only supervises the data processing carried out at the University, but who will also respond to any questions you may have about this data processing. You can contact our data protection officer by writing to ***@***.*** ***@***.***>.

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AttributeError: 'Timestamp' object has no attribute 'items' - when y_pred = model.predict_one(x) #1084

XaviMartiCamarasa Nov 9, 2022

Replies: 3 comments · 4 replies

MaxHalford Nov 9, 2022 Maintainer

XaviMartiCamarasa Nov 9, 2022 Author

MaxHalford Nov 9, 2022 Maintainer

XaviMartiCamarasa Nov 9, 2022 Author

smastelini Nov 9, 2022 Maintainer

XaviMartiCamarasa Nov 9, 2022 Author

XaviMartiCamarasa Nov 9, 2022 Author

XaviMartiCamarasa
Nov 9, 2022

Replies: 3 comments 4 replies

MaxHalford
Nov 9, 2022
Maintainer

XaviMartiCamarasa Nov 9, 2022
Author

MaxHalford Nov 9, 2022
Maintainer

XaviMartiCamarasa Nov 9, 2022
Author

smastelini Nov 9, 2022
Maintainer

XaviMartiCamarasa
Nov 9, 2022
Author

XaviMartiCamarasa
Nov 9, 2022
Author