In this analysis, we will be evaluating the Titanic dataset. The data dictionary is as follows: - Passengerid: Passenger ID - Age: Age in years - Fare: Passenger fare - Sex: Sex (female, male) - Sibsp: \# of siblings/spouses aboard the Titanic (Sibling = brother, sister, stepbrother, stepsister ; Spouse = husband, wife ) - Parch: \# of parents/children aboard the Titanic (Parent = mother, father; Child = daughter, son, stepdaughter, stepson) - Pclass: Ticket class (1 = 1st class, 2 = 2nd class, 3 = 3rd class) - Embarked: Port of Embarkation (C = Cherbourg, Q = Queenstown, S = Southampton) - Survived: Survival (0 = No, 1 = Yes) - Cabin: Cabin number - Ticket: Ticket number

This analysis uses the American Companies Bankruptcy Prediction dataset to build a two-cluster k-means model and evaluate its ability to separate surviving firms from failed firms. The workflow follows the standard exploratory data analysis pipeline: data ingestion, type verification, missing value assessment, outlier handling, transformation, splitting, feature engineering, modeling, and evaluation. The dataset contains 18 financial variables along with a company identifier, year, and survival status label. The table below documents the original column codes, the renamed variables used throughout this analysis, and a short description of each measure.

Es el analisis economico de Nuevo laredo