Problem with Preparing the data

[caiquanyou]

In the 02_Exploratory_analysis_of_single_cell_data_with_SAUCIE.ipynb example, i run it and get some error issues below:
'data = pca_op.fit_transform(data_raw)'
TypeError Traceback (most recent call last)
in
1 pca_op = sklearn.decomposition.PCA(100)
----> 2 data = pca_op.fit_transform(data_raw)
3 data

/usr/local/lib/python3.6/dist-packages/sklearn/decomposition/_pca.py in fit_transform(self, X, y)
374 C-ordered array, use 'np.ascontiguousarray'.
375 """
--> 376 U, S, V = self.fit(X)
377 U = U[:, :self.n_components]
378

/usr/local/lib/python3.6/dist-packages/sklearn/decomposition/_pca.py in _fit(self, X)
396
397 X = self._validate_data(X, dtype=[np.float64, np.float32],
--> 398 ensure_2d=True, copy=self.copy)
399
400 # Handle n_components==None

/usr/local/lib/python3.6/dist-packages/sklearn/base.py in _validate_data(self, X, y, reset, validate_separately, **check_params)
418 f"requires y to be passed, but the target y is None."
419 )
--> 420 X = check_array(X, **check_params)
421 out = X
422 else:

/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py in inner_f(*args, **kwargs)
70 FutureWarning)
71 kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72 return f(**kwargs)
73 return inner_f
74

/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)
576 dtype=dtype, copy=copy,
577 force_all_finite=force_all_finite,
--> 578 accept_large_sparse=accept_large_sparse)
579 else:
580 # If np.array(..) gives ComplexWarning, then we convert the warning

/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py in _ensure_sparse_format(spmatrix, accept_sparse, dtype, copy, force_all_finite, accept_large_sparse)
351
352 if accept_sparse is False:
--> 353 raise TypeError('A sparse matrix was passed, but dense '
354 'data is required. Use X.toarray() to '
355 'convert to a dense numpy array.')

TypeError: A sparse matrix was passed, but dense data is required. Use X.toarray() to convert to a dense numpy array.
I wonder how to fix this problem?