KeyError raised when using pandas DataFrame in SelectFromModel.fit()

### Describe the bug

When passing X to SelectFromModel.fit() where X is a pandas DatafFrame, a keyerror is raised at

https://github.com/scikit-learn/scikit-learn/blob/16625450b58f555dc3955d223f0c3b64a5686984/sklearn/feature_selection/_from_model.py#L317

This is because there is no `key==0` in the DF, this only works with numpy arrays not DataFrames.   
In version `1.0.2` this check was done with `X.shape[1]` which worked for both arrays and dataframes.

This is breaking our existing code.

### Steps/Code to Reproduce

```python
import logging

from mlxtend.classifier import LogisticRegression
from sklearn.feature_selection._from_model import SelectFromModel

import pandas as pd

df = pd.DataFrame(
    [
        ["c", 0, 3, 9, 5],
        ["d", 0, 4, 4, 6],
        ["d", 1, 15, 11, 7],
        ["c", 1, 1, 0, 9],
    ],
    columns=["a", "b", "c", "d", "e"],
)
target_col = "b"
df = df.drop(["a"], axis=1)
x = df[[x for x in df.columns if x != target_col]]
y = df[target_col]

try:
    SelectFromModel(LogisticRegression(), threshold="mean", max_features=2).fit(x, y)  # works in SKLearn v1.0.2, fails in 1.1.0
except KeyError:
    logging.exception("")

SelectFromModel(LogisticRegression(), threshold="mean", max_features=2).fit(x.values, y)
```

### Expected Results

No error raised.

### Actual Results

```console
Traceback (most recent call last):
  File "C:\Users\e68175\AppData\Local\JetBrains\PyCharm Community Edition 2021.3.3\plugins\python-ce\helpers\pydev\_pydevd_bundle\pydevd_exec2.py", line 3, in Exec
    exec(exp, global_vars, local_vars)
  File "<input>", line 1, in <module>
  File "C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\lib\site-packages\sklearn\feature_selection\_from_model.py", line 317, in fit
    max_val=len(X[0]),
  File "C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\lib\site-packages\pandas\core\frame.py", line 3505, in __getitem__
    indexer = self.columns.get_loc(key)
  File "C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\lib\site-packages\pandas\core\indexes\base.py", line 3623, in get_loc
    raise KeyError(key) from err
KeyError: 0
```

### Versions

```shell
Python dependencies:
      sklearn: 1.1.0
          pip: 21.2.4
   setuptools: 58.1.0
        numpy: 1.21.6
        scipy: 1.8.0
       Cython: 0.29.28
       pandas: 1.4.2
   matplotlib: 3.5.2
       joblib: 1.1.0
threadpoolctl: 3.1.0
Built with OpenMP: True
threadpoolctl info:
       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\Lib\site-packages\numpy\.libs\libopenblas.XWYDX2IKJW2NMTWSFYNGFUWKQU3LYTCZ.gfortran-win_amd64.dll
        version: 0.3.17
threading_layer: pthreads
   architecture: Haswell
    num_threads: 8
       user_api: openmp
   internal_api: openmp
         prefix: vcomp
       filepath: C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\Lib\site-packages\sklearn\.libs\vcomp140.dll
        version: None
    num_threads: 8
       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: C:\Users\e68175\projects\datalab-pypf-2\venv-skl110\Lib\site-packages\scipy\.libs\libopenblas.XWYDX2IKJW2NMTWSFYNGFUWKQU3LYTCZ.gfortran-win_amd64.dll
        version: 0.3.17
threading_layer: pthreads
   architecture: Haswell
    num_threads: 8
```

COMMENT:
I will have a look. I have to check if the `LogisticRegression` from `mlxtend` is fully compatible.

Labels: Bug, Regression, Needs Triage