ValueError: Wrong number of items passed 844, placement implies 30

Hi, I am trying to follow your tutorial: https://towardsdatascience.com/how-to-use-machine-learning-to-possibly-become-a-millionaire-predicting-the-stock-market-33861916e9c5

I am using Jupyter Notebooks, python 3.6, on Windows 10. After enter the following code:

import stocker
from stocker import Stocker
goog = Stocker('GOOGL')
goog.plot_stock()

Everything works, but then the next line:

model, model_data = goog.create_prophet_model(days=90)

I get a ValueError:

C:\Users\benki\.conda\envs\myenv\lib\site-packages\pystan\misc.py:399: 
FutureWarning: Conversion of the second argument of issubdtype from `float` 
to `np.floating` is deprecated. In future, it will be treated as `np.float64 == 
np.dtype(float).type`.
  elif np.issubdtype(np.asarray(v).dtype, float):
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-23-0dedf473e878> in <module>
----> 1 model, model_data = goog.create_prophet_model(days=90)

~\Desktop\yolov3-tf2\Data-Analysis\stocker\stocker.py in  
create_prophet_model(self, days, resample)
    516         # Make and predict for next year with future dataframe
    517         future = model.make_future_dataframe(periods=days, freq="D")
--> 518         future = model.predict(future)
    519 
    520         if days > 0:

~\.conda\envs\myenv\lib\site-packages\fbprophet\forecaster.py in 
predict(self, df)
   1040         df['trend'] = self.predict_trend(df)
   1041         seasonal_components = self.predict_seasonal_components(df)
-> 1042         intervals = self.predict_uncertainty(df)
   1043 
   1044         # Drop columns except ds, cap, floor, and trend

~\.conda\envs\myenv\lib\site-packages\fbprophet\forecaster.py in 
predict_uncertainty(self, df)
   1242         Dataframe with uncertainty intervals.
   1243         """
-> 1244         sim_values = self.sample_posterior_predictive(df)
   1245 
   1246         lower_p = 100 * (1.0 - self.interval_width) / 2

~\.conda\envs\myenv\lib\site-packages\fbprophet\forecaster.py in 
sample_posterior_predictive(self, df)
   1206                     iteration=i,
   1207                     s_a=component_cols['additive_terms'],
-> 1208                     s_m=component_cols['multiplicative_terms'],
   1209                 )
   1210                 for key in sim_values:

~\.conda\envs\myenv\lib\site-packages\fbprophet\forecaster.py in 
sample_model(self, df, seasonal_features, iteration, s_a, s_m)
   1274 
   1275         beta = self.params['beta'][iteration]
-> 1276         Xb_a = np.matmul(seasonal_features.values, beta * s_a) * 
self.y_scale
   1277         Xb_m = np.matmul(seasonal_features.values, beta * s_m)
   1278 

~\.conda\envs\myenv\lib\site-packages\pandas\core\series.py in 
__array_wrap__(self, result, context)
    502         """
    503         return self._constructor(result, index=self.index,
--> 504                                  copy=False).__finalize__(self)
    505 
    506     def __array_prepare__(self, result, context=None):

~\.conda\envs\myenv\lib\site-packages\pandas\core\series.py in __init__(self, 
data, index, dtype, name, copy, fastpath)
    264                                        raise_cast_failure=True)
    265 
--> 266                 data = SingleBlockManager(data, index, fastpath=True)
    267 
    268         generic.NDFrame.__init__(self, data, fastpath=True)

~\.conda\envs\myenv\lib\site-packages\pandas\core\internals.py in 
__init__(self, block, axis, do_integrity_check, fastpath)
   4400         if not isinstance(block, Block):
   4401             block = make_block(block, placement=slice(0, len(axis)), 
ndim=1,
-> 4402                                fastpath=True)
   4403 
   4404         self.blocks = [block]

~\.conda\envs\myenv\lib\site-packages\pandas\core\internals.py in 
make_block(values, placement, klass, ndim, dtype, fastpath)
   2955                      placement=placement, dtype=dtype)
   2956 
-> 2957     return klass(values, ndim=ndim, fastpath=fastpath, 
placement=placement)
   2958 
   2959 # TODO: flexible with index=None and/or items=None

~\.conda\envs\myenv\lib\site-packages\pandas\core\internals.py in 
__init__(self, values, placement, ndim, fastpath)
    118             raise ValueError('Wrong number of items passed %d, placement 
'
    119                              'implies %d' % (len(self.values),
--> 120                                              len(self.mgr_locs)))
    121 
    122     @property

ValueError: Wrong number of items passed 844, placement implies 30`

jerrytigerxu / Stock-Price-Prediction

ValueError: Wrong number of items passed 844, placement implies 30 #2