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WebI have manually added a 'sex' column onto the DataFrame, and I am trying to replace 'Male' with 0 and 'Female' with 1 however it does not seem to work. I just get a 'NaN' value instead of the ones and zeroes. Relevant code: df ['sex'] = df ['sex'].map ( {'Male': 0, 'Female': 1}) It does not seem to be specific to the 'sex' column since this ... WebParameters: missing_values int, float, str, np.nan or None, default=np.nan. The placeholder for the missing values. All occurrences of missing_values will be imputed. For pandas’ dataframes with nullable integer dtypes with missing values, missing_values should be set to np.nan, since pd.NA will be converted to np.nan. n_neighbors int, default=5. Number of … chipotle se military
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