Feature names are only supported if all input features have string names

[Rahimlou]

Hello,

I receive the following error running concoct. I can't understand which file is problematic and how should I solve it.

TypeError: Feature names are only supported if all input features have string names, but your input has ['int', 'str'] as feature name / column name types. If you want feature names to be stored and validated, you must convert them all to strings, by using X.columns = X.columns.astype(str) for example. Otherwise you can remove feature / column names from your input data, or convert them all to a non-string data type.

[jpalmer37]

Receiving the same error. Can't seem to debug it. Would appreciate someone looking at this.

[maddne]

Hi, I was able to workaround the issue by opening the validation.py file. In my case (concoct installed with conda) the file was in miniconda3/envs/concoct/lib/python3.10/site-packages/sklearn/utils/validation.py.
on line 1885 I changed the following:
feature_names = np.asarray(X.columns, dtype=object) to
feature_names = np.asarray(X.columns.astype(str), dtype=object)
The value error that you pasted said to do that in such case. It worked, got another error, but it is not connected to this one. Hope it helps!

[timeresistance1996]

I got the same error too. Have you fixed this problem？

[jpalmer37]

Thanks @maddne! Seems like a promising step towards fixing it. If you or @timeresistance1996 are still encountering errors and need a quick solution, vinisalazar's custom conda environment worked for me with no errors. Here's a link to it #321 (comment)

[timeresistance1996]

Thank you so much! @jpalmer37 I have create a new conda env with #321mentioned, but run with a new error,which is,

/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/sklearn/utils/validation.py:1858: FutureWarning: Feature names only support names that are all strings. Got feature names with dtypes: ['int', 'str']. An error will be raised in 1.2.
warnings.warn(
Traceback (most recent call last):
File "/root/anaconda3/envs/concoct_env/bin/concoct", line 90, in
results = main(args)
File "/root/anaconda3/envs/concoct_env/bin/concoct", line 37, in main
transform_filter, pca = perform_pca(
File "/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/concoct/transform.py", line 5, in perform_pca
pca_object = PCA(n_components=nc, random_state=seed).fit(d)
File "/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/sklearn/decomposition/_pca.py", line 408, in fit
self._fit(X)
File "/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/sklearn/decomposition/_pca.py", line 456, in _fit
X = self._validate_data(
File "/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/sklearn/base.py", line 577, in _validate_data
X = check_array(X, input_name="X", **check_params)
File "/root/anaconda3/envs/concoct_env/lib/python3.10/site-packages/sklearn/utils/validation.py", line 909, in check_array
raise ValueError(
ValueError: Found array with 0 sample(s) (shape=(0, 138)) while a minimum of 1 is required by PCA.

Have you ever got this error before?

[jpinus]

thanks, worked for me :)

[marsfro]

I solved it by installing scikit-learn inside concoct_env
conda install -c intel scikit-learn

[YeGuoZJU]

Hi, I was able to workaround the issue by opening the validation.py file. In my case (concoct installed with conda) the file was in miniconda3/envs/concoct/lib/python3.10/site-packages/sklearn/utils/validation.py.
on line 1885 I changed the following:
feature_names = np.asarray(X.columns, dtype=object) to
feature_names = np.asarray(X.columns.astype(str), dtype=object)
The value error that you pasted said to do that in such case. It worked, got another error, but it is not connected to this one. Hope it helps!

thanks, I have fixed this error by using this way

[saras224]

Hi, I was able to workaround the issue by opening the validation.py file. In my case (concoct installed with conda) the file was in miniconda3/envs/concoct/lib/python3.10/site-packages/sklearn/utils/validation.py.
on line 1885 I changed the following:
feature_names = np.asarray(X.columns, dtype=object) to
feature_names = np.asarray(X.columns.astype(str), dtype=object)
The value error that you pasted said to do that in such case. It worked, got another error, but it is not connected to this one. Hope it helps!

thanks, I have fixed this error by using this way

Worked for me too!!! thanks for posting this up!!!! :))