quitar libreria joblib
Browse files
app.py
CHANGED
@@ -2,17 +2,15 @@
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import streamlit as st
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import random
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import pickle
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import joblib
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from sklearn.preprocessing import StandardScaler
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import pandas as pd
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import time
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from sklearn.cluster import KMeans
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standard_scaler = StandardScaler()
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#pre cargar
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dataIni = pd.read_csv('DataModelo.csv')
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#data = dataIni.drop(['Usuario_Id','Cluster','recency','Avg_dias','distancia','total_min','num_reincidencia','mes'], axis=1, )
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#data = dataIni.drop(columns= {'Cluster','Usuario_Id','recency', 'Avg_dias','distancia', 'total_min', 'num_reincidencia', 'mes'})
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@@ -125,7 +123,7 @@ with col1:
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with col2:
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#avg_dias = st.number_input('Promedio de dias que se usa mibici',value=0.00)
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avg_dias = option = st.selectbox(
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'
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('1 - 10 dias', '10 - 30 dias', '30 - 50 dias '))
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with col3:
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total_min = st.number_input('Distancia que recorre en km',value=0.000000)
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import streamlit as st
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import random
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import pickle
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from sklearn.preprocessing import StandardScaler
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import pandas as pd
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import time
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from sklearn.cluster import KMeans
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#pre cargar
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standard_scaler = StandardScaler()
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dataIni = pd.read_csv('DataModelo.csv')
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#data = dataIni.drop(['Usuario_Id','Cluster','recency','Avg_dias','distancia','total_min','num_reincidencia','mes'], axis=1, )
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#data = dataIni.drop(columns= {'Cluster','Usuario_Id','recency', 'Avg_dias','distancia', 'total_min', 'num_reincidencia', 'mes'})
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with col2:
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#avg_dias = st.number_input('Promedio de dias que se usa mibici',value=0.00)
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avg_dias = option = st.selectbox(
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'promedio en minutos de sus viajes',
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('1 - 10 dias', '10 - 30 dias', '30 - 50 dias '))
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with col3:
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total_min = st.number_input('Distancia que recorre en km',value=0.000000)
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