: Extracting the "Month" or "Day of Week" from a timestamp column. Example: Creating a Log-Transformed Feature
import numpy as np # Creating a new feature to handle skewed data df['log_feature'] = np.log1p(df['existing_column']) Use code with caution. Copied to clipboard nikitanoelle16.zip
: Using the .apply() method for more complex logic. For example, if you are mapping functions to specific columns, developers on Stack Overflow suggest using a dictionary to map column names to functions for cleaner code. : Extracting the "Month" or "Day of Week"
import pandas as pd import zipfile # Extracting the file with zipfile.ZipFile('nikitanoelle16.zip', 'r') as zip_ref: zip_ref.extractall('data_folder') # Loading the dataset df = pd.read_csv('data_folder/dataset_name.csv') Use code with caution. Copied to clipboard Step 2: Create a Feature For example, if you are mapping functions to
: Combining two columns (e.g., df['total_cost'] = df['price'] * df['quantity'] ).