Descripción del Problema¶
Your task is to clean and explore a dataset for HR executives that describes trends in their employee data related to attrition. A data dictionary can be found at the bottom of this page...
Descripción del Conjunto de Datos¶
| Column Name | Data Type | Description |
|---|---|---|
| Age | int | Age of employee |
| Attrition | Object | Employee leaving the company (no or yes) |
| BusinessTravel | Object | How much the employee travels for work (no travel, travels frequently, or travels rarely) |
| ... | ... | ... |
Nota: utilizar Tables Generator para generar tablas en markdown.
Solución¶
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# librerias
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
# Ver gráficos de matplotlib en jupyter notebook/lab
%matplotlib inline
# librerias
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
# Ver gráficos de matplotlib en jupyter notebook/lab
%matplotlib inline
I.- Análisis Exploratorio¶
Manipulación de datos¶
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Visualizaciones¶
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II.- Modelos¶
Feature engineering¶
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Entrenamiento de modelos¶
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Evaluación de modelos¶
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Conclusiones Generales¶
- Conclusión 01
- Conclusión 02
- ...