Updating docs, updating fill_value reference in README

Author: Brendan Herger

.pytest_cache/README.md

@@ -0,0 +1,8 @@
+# pytest cache directory #
+
+This directory contains data from the pytest's cache plugin,
+which provides the `--lf` and `--ff` options, as well as the `cache` fixture.
+
+**Do not** commit this to version control.
+
+See [the docs](https://docs.pytest.org/en/latest/cache.html) for more information.

.pytest_cache/v/cache/lastfailed

@@ -0,0 +1,6 @@
+{
+  "tests/test_categorical_imputer.py::test_unit[np-None]": true,
+  "tests/test_categorical_imputer.py::test_unit[np-nan]": true,
+  "tests/test_categorical_imputer.py::test_unit[pd-None]": true,
+  "tests/test_categorical_imputer.py::test_unit[pd-nan]": true
+}

.pytest_cache/v/cache/nodeids

@@ -0,0 +1,6 @@
+[
+  "tests/test_categorical_imputer.py::test_unit[np-None]",
+  "tests/test_categorical_imputer.py::test_unit[np-nan]",
+  "tests/test_categorical_imputer.py::test_unit[pd-None]",
+  "tests/test_categorical_imputer.py::test_unit[pd-nan]"
+]

README.rst

@@ -401,7 +401,7 @@ Example: imputing with a fixed value:
 
     >>> from sklearn_pandas import CategoricalImputer
     >>> data = np.array(['a', 'b', 'b', np.nan], dtype=object)
-    >>> imputer = CategoricalImputer(strategy='fixed_value', replacement='a')
+    >>> imputer = CategoricalImputer(strategy='constant', fill_value='a')
     >>> imputer.fit_transform(data)
     array(['a', 'b', 'b', 'a'], dtype=object)
 

sklearn_pandas/categorical_imputer.py

@@ -33,17 +33,20 @@ class CategoricalImputer(BaseEstimator, TransformerMixin):
     copy : boolean, optional (default=True)
         If True, a copy of X will be created.
 
-    strategy : string, optional (default = 'mode')
-        If set to 'mode', replace all instances of `missing_values`
-        with the modal value. Otherwise, replace with
-        the value specified via `replacement`.
+    strategy : string, optional (default = 'most_frequent')
+        The imputation strategy.
+
+        - If "most_frequent", then replace missing using the most frequent
+          value along each column. Can be used with strings or numeric data.
+        - If "constant", then replace missing values with fill_value. Can be
+          used with strings or numeric data.
 
     replacement : string, optional (default='?')
         The value that all instances of `missing_values` are replaced
-        with if `strategy` is not set to 'mode'. This is useful if
+        with if `strategy` is set to `constant`. This is useful if
         you don't want to impute with the mode, or if there are multiple
         modes in your data and you want to choose a particular one. If
-        `strategy` is set to `mode`, this parameter is ignored.
+        `strategy` is not set to `constant`, this parameter is ignored.
 
     Attributes
     ----------