Open
Description
For a good UX, scikit-learn will attempt to convert string dtyped columns of an input dataframe to floats by default during e.g., RandomForestClassifier.fit (and possibly other estimators). If it can't it will throw an error. We throw an error in both scenarios.
We should potentially do the same, pending performance impact.
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
N = 1000
categories = ['0', '1', '2'] # automatically coerced, as it assumes there is an implied ordinality
# categories = ['a', 'b', 'c'] # errors, as it assumes cardinality
numeric_data = np.random.rand(N, 5)
string_data = np.random.choice(categories, size=(N,1))
y = np.random.choice([0, 1], size=N)
X = pd.DataFrame(numeric_data)
X["str_col"] = string_data
X.columns = [f"x{i}" for i in range(len(X.columns))]
clf = RandomForestClassifier()
clf.fit(X,y)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/tmp/ipykernel_3546391/1974482336.py in ?()
1 clf = RandomForestClassifier()
----> 2 clf.fit(X,y)
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/base.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/base.py) in ?(estimator, *args, **kwargs)
1385 skip_parameter_validation=(
1386 prefer_skip_nested_validation or global_skip_validation
1387 )
1388 ):
-> 1389 return fit_method(estimator, *args, **kwargs)
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/ensemble/_forest.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/ensemble/_forest.py) in ?(self, X, y, sample_weight)
356 # Validate or convert input data
357 if issparse(y):
358 raise ValueError("sparse multilabel-indicator for y is not supported.")
359
--> 360 X, y = validate_data(
361 self,
362 X,
363 y,
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py) in ?(_estimator, X, y, reset, validate_separately, skip_check_array, **check_params)
2957 if "estimator" not in check_y_params:
2958 check_y_params = {**default_check_params, **check_y_params}
2959 y = check_array(y, input_name="y", **check_y_params)
2960 else:
-> 2961 X, y = check_X_y(X, y, **check_params)
2962 out = X, y
2963
2964 if not no_val_X and check_params.get("ensure_2d", True):
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py) in ?(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)
1366 )
1367
1368 ensure_all_finite = _deprecate_force_all_finite(force_all_finite, ensure_all_finite)
1369
-> 1370 X = check_array(
1371 X,
1372 accept_sparse=accept_sparse,
1373 accept_large_sparse=accept_large_sparse,
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/validation.py) in ?(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_non_negative, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
1052 )
1053 array = xp.astype(array, dtype, copy=False)
1054 else:
1055 array = _asarray_with_order(array, order=order, dtype=dtype, xp=xp)
-> 1056 except ComplexWarning as complex_warning:
1057 raise ValueError(
1058 "Complex data not supported\n{}\n".format(array)
1059 ) from complex_warning
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/_array_api.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/sklearn/utils/_array_api.py) in ?(array, dtype, order, copy, xp, device)
835 # Use NumPy API to support order
836 if copy is True:
837 array = numpy.array(array, order=order, dtype=dtype)
838 else:
--> 839 array = numpy.asarray(array, order=order, dtype=dtype)
840
841 # At this point array is a NumPy ndarray. We convert it to an array
842 # container that is consistent with the input's namespace.
[/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/pandas/core/generic.py](http://10.176.1.125:8883/lab/tree/raid/nicholasb/raid/nicholasb/miniforge3/envs/cuml-25.02/lib/python3.11/site-packages/pandas/core/generic.py) in ?(self, dtype, copy)
2149 def __array__(
2150 self, dtype: npt.DTypeLike | None = None, copy: bool_t | None = None
2151 ) -> np.ndarray:
2152 values = self._values
-> 2153 arr = np.asarray(values, dtype=dtype)
2154 if (
2155 astype_is_view(values.dtype, arr.dtype)
2156 and using_copy_on_write()
ValueError: could not convert string to float: 'c'