Category : facebook-prophet

I have a model that uses the python Prophet library for some predictive analytics. The code runs fine locally but when I run it via an Airflow DAG, I get the following error: [2022-01-11, 18:47:00 UTC] {subprocess.py:89} INFO – AttributeError: ‘StanModel’ object has no attribute ‘fit_class’ [2022-01-11, 18:47:00 UTC] {subprocess.py:93} INFO – Command exited with ..

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I’ve been trying forecasting package of facebook, named prophet. Even though I set up code, sample data and package, the result seems failing. Here’s the code and data. import pandas as pd from fbprophet import Prophet # Python df = pd.read_csv(‘./test.csv’) df.head() m = Prophet(yearly_seasonality=True, daily_seasonality=True) m.fit(df) future = m.make_future_dataframe(periods=365) future.tail() forecast = m.predict(future) forecast.head() ..

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I want to install the package fbprophet (it may now also be known as prophet). I tried importing both like so (not all at once): import fbprophet import prophet from fbprophet import Prophet from prophet import Prophet Error I receive is as follows: ————————————————————————— ModuleNotFoundError Traceback (most recent call last) ~AppDataLocalTemp/ipykernel_5908/2493871459.py in <module> —-> 1 ..

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Dataframe: I have a DataFrame (df) with ds and y columns for forecasting with FB Prophet. Here’s the code: from fbprophet import Prophet m=Prophet m.fit(df) future = m.make_future_dataframe(periods=180) forecast = m.predict(future) figure = m.plot(forecast) I get the error numpy.ndarray object has no attribute ‘is_all_dates’ This is quite a bizzare error as this code works with ..

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Code screenshot with dataframe Error I would like to understand why this model is not able to run successfully. Please find screenshots attached for more clarity. import numpy as np train,test = np.split(df,[int(.8 * len(df))]) train.rename(columns={‘datetime’:’ds’,’cnt’:’y’}, inplace=True) test.rename(columns={‘datetime’:’ds’,’cnt’:’y’}, inplace=True) #add additional regressor prophet = Prophet(yearly_seasonality=True,changepoint_range=0.75) prophet.add_regressor(‘temp’) prophet.add_regressor(‘weathersit’) prophet.add_regressor(‘holiday’) prophet.fit(train) forecast_data = prophet.predict(test) Source: Python..

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C:Userssaurabh>pip install prophet Collecting prophet Using cached prophet-1.0.1.tar.gz (65 kB) Preparing metadata (setup.py) … done Requirement already satisfied: Cython>=0.22 in c:userssaurabhappdatalocalprogramspythonpython38libsite-packages (from prophet) (0.29.24) Collecting cmdstanpy==0.9.68 Using cached cmdstanpy-0.9.68-py3-none-any.whl (49 kB) Requirement already satisfied: pystan~=2.19.1.1 in c:userssaurabhappdatalocalprogramspythonpython38libsite-packages (from prophet) (2.19.1.1) Requirement already satisfied: numpy>=1.15.4 in c:userssaurabhappdatalocalprogramspythonpython38libsite-packages (from prophet) (1.21.4) Requirement already satisfied: pandas>=1.0.4 in c:userssaurabhappdatalocalprogramspythonpython38libsite-packages ..

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