Nuevos modulos para analisis

analysis/index_batch.py

@@ -0,0 +1,37 @@
+from analysis.market_snapshot import Market, available_date_ranges
+
+class IndexMM:
+
+    def __init__(self):
+        self.name = 'indexmm'
+        self.date = None
+        self.data = None
+
+    def calculate(self, market):
+        self.market = market
+        self.date = self.market.end_date
+        self.data = market.get_market_data()
+
+        data_coche_pequeno = {'count': self.data[self.data['tamano_categorico'] == 'coche pequeño'].count(),
+                              'mean': self.data[self.data['tamano_categorico' == 'coche pequeño']]['precio'].transform('mean')}
+        data_coche_grande = {'count': self.data[self.data['tamano_categorico'] == 'coche grande'].count(),
+                              'mean': self.data[self.data['tamano_categorico' == 'coche grande']]['precio'].transform('mean')}
+        data_coche_moto = {'count': self.data[self.data['tamano_categorico'] == 'coche y moto'].count(),
+                              'mean': self.data[self.data['tamano_categorico' == 'coche y moto']]['precio'].transform('mean')}
+
+        self.value = (((data_coche_grande['count'] * data_coche_grande['mean']) + (data_coche_moto['count'] * data_coche_moto['mean'])
+                        + (data_coche_pequeno['count'] * data_coche_pequeno['mean']))
+                      / (data_coche_grande['count'] + data_coche_moto['count'] + data_coche_pequeno['count']))
+
+        #SEGUIR AQUI
+
+
+
+
+
+    def get_data(self):
+        return {'name': self.name,
+                'date': self.date,
+                'value': self.value}
+
+

analysis/market_snapshot.py

@@ -0,0 +1,74 @@
+from datetime import datetime,  timedelta
+import pandas as pd
+
+available_date_ranges = [{'start': datetime(2017, 10, 1), 'end': datetime(2018, 1, 1)},
+                         {'start': datetime(2017, 11, 1), 'end': datetime(2018, 2, 1)},
+                         {'start': datetime(2017, 12, 1), 'end': datetime(2018, 3, 1)},
+                         {'start': datetime(2018, 1, 1), 'end': datetime(2018, 4, 1)},
+                         {'start': datetime(2018, 2, 1), 'end': datetime(2018, 5, 1)},
+                         {'start': datetime(2018, 3, 1), 'end': datetime(2018, 6, 1)},
+                         {'start': datetime(2018, 4, 1), 'end': datetime(2018, 7, 1)},
+                         {'start': datetime(2018, 5, 1), 'end': datetime(2018, 8, 1)},
+                         {'start': datetime(2018, 6, 1), 'end': datetime(2018, 9, 1)},
+                         {'start': datetime(2018, 7, 1), 'end': datetime(2018, 10, 1)},
+                         {'start': datetime(2018, 8, 1), 'end': datetime(2018, 11, 1)},
+                         {'start': datetime(2018, 9, 1), 'end': datetime(2018, 12, 1)}]
+
+
+class Market:
+
+    def __init__(self):
+        self.start_date = datetime.today() - timedelta(days=90)
+        self.end_date = datetime.today()
+        self.market = None
+
+    def load_market(self, market_query_results):
+        self.market = pd.DataFrame(market_query_results)
+
+    def clean_market(self, method):
+
+        if method == 'index':
+            self.market.dropna(subset=['tamano_categorico'])
+            self.market = self.market[~self.market['tamano_categorico'].isin(['2 coches o más', 'moto'])]
+            self.market.drop_duplicates(subset=['precio', 'latitud', 'longitud'], keep='last')
+            self.market = self.market[self.market['tipo_anuncio'] == 1]
+            self.delete_outliers()
+
+        if method == 'valoracion':
+            self.market.dropna(subset=['tamano_categorico'])
+            self.market = self.market[~self.market['tamano_categorico'].isin(['2 coches o más', 'moto'])]
+            self.market = self.market[self.market['precision'].isin(['ROOFTOP'])]
+            self.market.drop_duplicates(subset=['precio', 'latitud', 'longitud'], keep='last')
+            self.market = self.market[self.market['tipo_anuncio'] == 1]
+            self.delete_outliers()
+
+    def delete_outliers(self):
+
+        outlier_combinations = [{'tipo_anuncio': 1, 'tamano_categorico': 'coche grande',
+                                 'min_precio': 1000, 'max_precio': 150000},
+                                {'tipo_anuncio': 1, 'tamano_categorico': 'coche pequeño',
+                                 'min_precio': 1000, 'max_precio': 150000},
+                                {'tipo_anuncio': 1, 'tamano_categorico': 'coche y moto',
+                                 'min_precio': 1000, 'max_precio': 200000},
+                                {'tipo_anuncio': 1, 'tamano_categorico': 'moto',
+                                 'min_precio': 1000, 'max_precio': 40000},
+                                {'tipo_anuncio': 2, 'tamano_categorico': 'coche grande',
+                                 'min_precio': 10, 'max_precio': 300},
+                                {'tipo_anuncio': 2, 'tamano_categorico': 'coche pequeño',
+                                 'min_precio': 10, 'max_precio': 300},
+                                {'tipo_anuncio': 2, 'tamano_categorico': 'coche y moto',
+                                 'min_precio': 10, 'max_precio': 3000},
+                                {'tipo_anuncio': 2, 'tamano_categorico': 'moto',
+                                 'min_precio': 10, 'max_precio': 150}]
+
+        for combination in outlier_combinations:
+            self.market = self.market.loc[~(
+                (self.market['tipo_anuncio'] == combination['tipo_anuncio']) &
+                (self.market['tamano_categorico'] == combination['tamano_categorico']) &
+                ((self.market['precio'] < combination['min_precio']) | (self.market['precio'] > combination['max_precio']))
+            )]
+
+    def get_market_data(self):
+        return self.market
+
+

db_layer/capturas_interface.py

@@ -96,6 +96,30 @@ class CapturasInterface:
 
         self.anunciosdb.query(query_statement, query_parameters)
 
+    def get_market_snapshot(self, start_date, end_date):
+        query_statement = """
+                           SELECT *
+                           FROM `anuncios`.`capturas` `t1`
+                           WHERE
+                           (
+                              (
+                                 `t1`.`fecha_captura` =
+                                 (
+                                    SELECT
+                                    max(`t2`.`fecha_captura`)
+                                    FROM `anuncios`.`capturas` `t2`
+                                    WHERE (`t1`.`referencia` = `t2`.`referencia`)
+                                 )
+                              )
+                              AND (`t1`.`fecha_captura` BETWEEN %(start_date)S AND %(end_date)S)
+                           )
+                                """
+        query_parameters = {'start_date': start_date.strftime('%Y-%m-%d 00:00:00'),
+                            'end_date': end_date.strftime('%Y-%m-%d 00:00:00')}
+
+        cursor_result = self.anunciosdb.query(query_statement, query_parameters, dictionary=True)
+        return cursor_result.fetchall()
+
 
 capturas_interface = CapturasInterface()
 

requirements.txt

@@ -2,3 +2,4 @@ bs4
 mysql-connector-python
 requests==2.18.4
 html5lib
+pandas==0.23.4