machine_failure_predict / functions.py
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def cria_feature(df):
import pandas as pd
df['Torque * Rotational speed'] = df['Torque [Nm]'] * df['Rotational speed [rpm]']
df['Torque * Tool wear'] = df['Torque [Nm]'] * df['Tool wear [min]']
return df
def get_rank_by_product_id(top,product_id):
# Verifique se o 'Product ID' está no DataFrame
if product_id in top['Product ID'].values:
# Se estiver no DataFrame, retorne o valor da coluna 'rank'
return top.loc[top['Product ID'] == product_id, 'Rank'].values[0]
else:
# Caso contrário, retorne 51
return 51
# Crie um transformador de função personalizada usando a função criada
def custom_encode(top,product_ids):
import numpy as np
result = []
result.append([get_rank_by_product_id(top,product_id) for product_id in product_ids])
return np.array(result).reshape(-1, 1)