AttributeError：类型对象'object'没有属性'dtype'

Question

I'm trying to replicate the results described in How to Determine the Best Fitting Data Distribution Using Python . I used then the following code:

import numpy as np
from distfit import distfit

# Generate 10000 normal distribution samples with mean 0, std dev of 3 
X = np.random.normal(0, 3, 10000)

# Initialize distfit
dist = distfit()

# Determine best-fitting probability distribution for data
dist.fit_transform(X)

Anyway, I obtained the following error:

[distfit] >fit..
[distfit] >transform..
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-8-02f73e7f157d> in <module>
      9 
     10 # Determine best-fitting probability distribution for data
---> 11 dist.fit_transform(X)

~\Anaconda3\lib\site-packages\distfit\distfit.py in fit_transform(self, X, verbose)
    275         self.fit(verbose=verbose)
    276         # Transform X based on functions
--> 277         self.transform(X, verbose=verbose)
    278         # Store
    279         results = _store(self.alpha,

~\Anaconda3\lib\site-packages\distfit\distfit.py in transform(self, X, verbose)
    214         if self.method=='parametric':
    215             # Compute best distribution fit on the empirical X
--> 216             out_summary, model = _compute_score_distribution(X, X_bins, y_obs, self.distributions, self.stats, verbose=verbose)
    217             # Determine confidence intervals on the best fitting distribution
    218             model = _compute_cii(self, model, verbose=verbose)

~\Anaconda3\lib\site-packages\distfit\distfit.py in _compute_score_distribution(data, X, y_obs, DISTRIBUTIONS, stats, verbose)
    906     model['params'] = (0.0, 1.0)
    907     best_score = np.inf
--> 908     df = pd.DataFrame(index=range(0, len(DISTRIBUTIONS)), columns=['distr', 'score', 'LLE', 'loc', 'scale', 'arg'])
    909     max_name_len = np.max(list(map(lambda x: len(x.name), DISTRIBUTIONS)))
    910 

~\Anaconda3\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
    346                                  dtype=dtype, copy=copy)
    347         elif isinstance(data, dict):
--> 348             mgr = self._init_dict(data, index, columns, dtype=dtype)
    349         elif isinstance(data, ma.MaskedArray):
    350             import numpy.ma.mrecords as mrecords

~\Anaconda3\lib\site-packages\pandas\core\frame.py in _init_dict(self, data, index, columns, dtype)
    449                     nan_dtype = dtype
    450                 v = construct_1d_arraylike_from_scalar(np.nan, len(index),
--> 451                                                        nan_dtype)
    452                 arrays.loc[missing] = [v] * missing.sum()
    453 

~\Anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in construct_1d_arraylike_from_scalar(value, length, dtype)
   1194     else:
   1195         if not isinstance(dtype, (np.dtype, type(np.dtype))):
-> 1196             dtype = dtype.dtype
   1197 
   1198         # coerce if we have nan for an integer dtype

AttributeError: type object 'object' has no attribute 'dtype'

(I'm using Jupyter.)

How can I fix this problem?

Answer 1

The solution to the above error, as can be seen in the comments of the question, was to upgrade pandas . This issue appears in versions 1.0.4 and lower.