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Titanic Analysis - EDA
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
US Company Bankruptcy Prediction - Implement EDA/Clustering Analysis and Interpret
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.
Proyecto Final
Es el analisis economico de Nuevo laredo