почему консоль spyder python перестала показывать INFO: Numberxpr.utils: NumExpr по умолчанию для 4 потоков.?

Question

Я работаю с данными временных рядов, и когда я написал 'pjme_test_fcst = model.predict (df = pjme_test.reset_index () \ .rename (columns = {' Datetime ':' ds '}))', то консольный jus остановился и не работал, и я попытался перезапустить, но то же самое случилось, не могли бы вы сказать мне, почему это произошло и что мне нужно сделать? примечание: я учу это у Kaggle.

 import pandas as pd
   import numpy as np
   import matplotlib.pyplot as plt
   from fbprophet import Prophet
   from sklearn.metrics import mean_squared_error, mean_absolute_error
   import seaborn as sns

 <pre> f=pd.read_csv('https://raw.githubusercontent.com/pedrocava/trab_series1/master/PJME_hourly.csv',index_col=[0],parse_dates=[0])


# Color pallete for plotting
color_pal = ["#F8766D", "#D39200", "#93AA00",
             "#00BA38", "#00C19F", "#00B9E3",
             "#619CFF", "#DB72FB"]

from fbprophet import Prophet
from sklearn.metrics import mean_squared_error, mean_absolute_error
plt.style.use('fivethirtyeight')
df.plot(style='.',figsize=(15,5),color=color_pal,title='hourly data ')




<pre> def create_features(df, label=None):

    df = df.copy()
    df['date'] = df.index
    df['hour'] = df['date'].dt.hour
    df['dayofweek'] = df['date'].dt.dayofweek
    df['quarter'] = df['date'].dt.quarter
    df['month'] = df['date'].dt.month
    df['year'] = df['date'].dt.year
    df['dayofyear'] = df['date'].dt.dayofyear
    df['dayofmonth'] = df['date'].dt.day
    df['weekofyear'] = df['date'].dt.weekofyear

    X = df[['hour','dayofweek','quarter','month','year',
           'dayofyear','dayofmonth','weekofyear']]
    if label:
        y = df[label]
             return X, y
        return X

    X, y = create_features(df, label='PJME_MW')
    features_and_target = pd.concat([X, y], axis=1)
    features_and_target.head()


    sns.pairplot(features_and_target.dropna(),
             hue='hour',
             x_vars=['hour','dayofweek','year','weekofyear'],
             y_vars='PJME_MW',
             height=5,
             plot_kws={'alpha':0.15,'linewidth':0})
    plt.suptitle('hourl;u ,day of week, year and week ofyear')






    split_date='01-Jan-2015'

    pjme_train=df.loc[df.index <=split_date].copy()

   pjme_test=df.loc[df.index > split_date].copy()


    pjme_test \
        .rename(columns={'PJME_MW':'Test set'})\
        .join(pjme_train.rename(columns={'PJME_MW':'train set'}),how='outer')\
        .plot(figsize=(15,5),title='PJME',style='.')
    plt.show()



    pjme_train.reset_index()\
        .rename(columns={'Datetime':'ds',
                         'PJME_MW':'Y'}).head()

    model=Prophet()
    model.fit(pjme_train.reset_index()\
              .rename(columns={'Datetime':'ds',
                               'PJME_MW':'y'}))


    #predict 
    pjme_test_fcst=model.predict(df=pjme_test.reset_index()\
                                 .rename(columns={'Datetime':'ds'}))


INFO:numexpr.utils:NumExpr defaulting to 4 threads.