📄️ Rename
The Rename transform allows you to change the names of columns in your dataset. This is useful for standardizing column names, making them more descriptive, or preparing your data for specific analysis requirements.
📄️ Split Columns
The Split Columns transform allows you to divide the content of a single column into multiple new columns based on a specified separator. This is useful for parsing complex data fields, separating combined information, or restructuring your dataset for more detailed analysis.
📄️ Encode
The Encode transform allows you to convert categorical data into numerical formats that machine learning algorithms can process. This transformation is crucial for preparing categorical variables for analysis and model training.
📄️ Normalize Data
The Normalize Data transform allows you to scale numerical data in your dataset using various methods. This is crucial for many machine learning algorithms and statistical analyses that assume data is on a similar scale.
📄️ Impute
The Impute transform allows you to fill in missing values in your dataset using various methods. This is crucial for preparing data for analysis and machine learning models that can't handle missing values.