[New post] How to use one hot encoding in Python?

Subash Chandran posted: "# Basic syntax: df_onehot = pd.get_dummies(df, columns=['col_name'], prefix=['one_hot']) # Where: # - get_dummies creates a one-hot encoding for each unique categorical # value in the column named col_name # - The prefix is added at the beginning of each" New post on Poopcode How to use one hot encoding in Python? by Subash Chandran # Basic syntax: df_onehot = pd.get_dummies(df, columns=['col_name'], prefix=['one_hot']) # Where: # - get_dummies creates a one-hot encoding for each unique categorical # value in the column named col_name # - The prefix is added at the beginning of each categorical value # to create new column names for the one-hot columns # Example usage: # Build example dataframe: df = pd.DataFrame(['sunny', 'rainy', 'cloudy'], columns=['weather']) print(df) weather 0 sunny 1 rainy 2 cloudy # Convert categorical weather variable to one-hot encoding: df_onehot = pd.get_dummies(df, columns=['weather'], prefix=['one_hot']) print(df_onehot) one_hot_cloudy one_hot_rainy one_hot_sunny 0 0 0 1 1 0 1 0 2 1 0 0 Read more of this post Subash Chandran | October 17, 2021 at 10:30 am | Tags: apply one hot encoding automatic find categorical data, Apply one hot encoding for categorical data., apply one hot encoding to all categorical variables python, apply one hot encoding to integer values, array to onehot encoded, best way to one hot encode data in python for machine learning, best way to one hot encode in python, categorical encoding into rows, categorical text to numerical one hot encoding method pandas, categorical to one hot python, convert a categorical column into one-hot encoding pandas, convert categorical data to one hot, convert categorical variables using one-hot encoding, convert labels to categorical one-hot encoding, convert labels to categorical one-hot encoding tf, convert multiple labels to categorical one-hot encoding, convert one hot encoding to binary labels, convert to one hot encoding python, coverting 8 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