AttributeError: 'ColumnTransformer' object has no attribute '_check_n_features'

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It collects links to all the places you might be looking at while hunting down a tough bug.<br/></p><p class="_description_9cepa_87 _strongText_9cepa_146">And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.</p><button class="_btnHero_9cepa_111">Talk to a Lightrun Answers expert</button></div></div></div></div></astro-island><section class="sectionWrapper _issueSummary_1slku_1"><div class="_container_riqi3_1"><div class="_wrapper_1slku_6"><h1 class="_title_1slku_11">AttributeError: 'ColumnTransformer' object has no attribute '_check_n_features'</h1><a href="https://github.com/scikit-learn/scikit-learn/issues/17741" class="_linkUnderline_1slku_16">See original GitHub issue</a></div><div class="_wrapperGrid_1slku_66"><div class="_descriptionWrapper_1slku_31"><div class="_wrapper_1otsw_1 _textContainer_1slku_36 "><div class="_content_1otsw_23"><div><p>I am a beginner and started learning data science some days ago. My feature data set has some categorical features and I was trying to preprocess in order to convert them into numbers. I was trying to use the <strong>ColumnTransformer</strong> from the sklearn compose module but had an error when I used the <strong>fit_transform( )</strong> parameter&gt;</p> <pre><code class="language-python"># Turn our categories into numbers from sklearn.preprocessing import OneHotEncoder from sklearn.compose import ColumnTransformer categorical_features = ["Make", "Colour", "Doors"] one_hot = OneHotEncoder() transformer = ColumnTransformer([("one_hot", one_hot, categorical_features)], remainder = "passthrough") transformed_X= transformer.fit_transform(X) <h2>These are the details of the error:</h2> <pre><code class="language-pytb">AttributeError Traceback (most recent call last) &lt;ipython-input-179-9955bb392ac9&gt; in &lt;module&gt; 12 categorical_features)], 13 remainder = "passthrough") ---&gt; 14 transformed_X= transformer.fit_transform(X) ~\Desktop\sample_project1\env\lib\site-packages\sklearn\compose\_column_transformer.py in fit_transform(self, X, y) 524 X = _check_X(X) 525 # set n_features_in_ attribute --&gt; 526 self._check_n_features(X, reset=True) 527 self._validate_transformers() 528 self._validate_column_callables(X)