Obtención/Exploración de la Estructura del Conjunto de Datos

.gitignore

@@ -3,3 +3,4 @@ downloads/**
 data
 venv 
 .env 
+.json

app/services/Prueva_J.json

@@ -0,0 +1 @@
+{"P\u00e1gina":{"0":"\/herramientas-de-consulta\/volante-de-nomina\/","1":"\/","2":"\/servicios\/pasantia-medica-de-ley\/","3":"\/autoservicios\/","4":"\/transparencia\/recursos-humanos\/nominas-de-empleados\/","5":"\/herramientas-de-consulta\/consulta-de-exequatur\/","6":"\/coronavirus\/establecimientos-toma-muestras-pcr\/","7":"\/foro\/main-forum\/","8":"\/servicios\/solicitud-de-empleo\/","9":"\/servicios\/","10":"\/transparencia\/","11":"\/sobre-nosotros\/quienes-somos\/","12":"\/regionales-de-salud\/","13":"\/regionales-de-salud\/metropolitano\/","14":"\/foro\/main-forum","15":"\/herramientas-de-consulta\/","16":"\/contacto\/","17":"\/servicios\/gestion-de-citas-medicas\/","18":"\/transparencia\/recursos-humanos\/","19":"\/sobre-nosotros\/organigrama\/","20":"Total"},"Vistas de una p\u00e1gina":{"0":96673,"1":36169,"2":28091,"3":22451,"4":18279,"5":16063,"6":11245,"7":9641,"8":6932,"9":6390,"10":5587,"11":4128,"12":3359,"13":2950,"14":2237,"15":2143,"16":2066,"17":1959,"18":1755,"19":1619,"20":390995},"N\u00famero de vistas de p\u00e1gina \u00fanicas":{"0":57460,"1":28188,"2":22575,"3":16639,"4":14497,"5":11747,"6":8565,"7":119,"8":5166,"9":5160,"10":4472,"11":3392,"12":2292,"13":2371,"14":27,"15":1757,"16":1788,"17":1692,"18":1470,"19":1379,"20":282611},"Promedio de tiempo en la p\u00e1gina":{"0":124.3784829892,"1":89.7614803163,"2":153.0671641791,"3":288.1576768394,"4":242.7883386581,"5":191.241555381,"6":171.3318070818,"7":43.3828362114,"8":120.1290801187,"9":46.7227901383,"10":59.5322685085,"11":221.4437317784,"12":70.3712598425,"13":184.6157237325,"14":32.5578568213,"15":31.8299465241,"16":192.8200514139,"17":197.6763392857,"18":51.1227272727,"19":189.6122699387,"20":122.6982238299},"Entradas":{"0":53379,"1":23297,"2":17993,"3":9509,"4":10305,"5":11212,"6":8442,"7":64,"8":4212,"9":813,"10":592,"11":1945,"12":1344,"13":1531,"14":27,"15":150,"16":890,"17":1486,"18":456,"19":439,"20":194167},"Porcentaje de rebote":{"0":0.4166432492,"1":0.408765077,"2":0.6441949647,"3":0.701966558,"4":0.703930131,"5":0.7304913939,"6":0.7353707652,"7":0.1875,"8":0.5880816714,"9":0.405904059,"10":0.3800675676,"11":0.7131105398,"12":0.3333333333,"13":0.6760287394,"14":0.2592592593,"15":0.3933333333,"16":0.7483146067,"17":0.8445491252,"18":0.4539473684,"19":0.7129840547,"20":0.5862243006},"Porcentaje de salidas":{"0":0.5296411614,"1":0.367220548,"2":0.5802214232,"3":0.6234466171,"4":0.6575304995,"5":0.6829981946,"6":0.7086705202,"7":0.0089202365,"8":0.5138488171,"9":0.2192488263,"10":0.170753535,"11":0.5845445736,"12":0.2438225662,"13":0.5386440678,"14":0.0071524363,"15":0.1273915072,"16":0.6234269119,"17":0.7713118938,"18":0.2478632479,"19":0.4966028413,"20":0.4965971432}}

app/services/data_structure.py

@@ -0,0 +1,31 @@
+# Import the pandas library to work with tabular data
+import pandas as pd
+# Import the deepcopy function from the copy library to create a deep copy of an object
+from copy import deepcopy
+
+# Definition of the DataStructure class
+class DataStructure:
+    def __init__(self, json_file):
+        # Initialize the DataStructure object with a JSON file
+        self.json_file = json_file
+        # Read the JSON file and convert it into a pandas DataFrame
+        self.df = pd.read_json(json_file)
+
+    def decribe_df(self):
+        # Create a deep copy of the DataFrame
+        data = deepcopy(self.df)
+        # Return a statistical summary of the DataFrame
+        return data.describe()
+
+    def info_df(self):
+        # Create a deep copy of the DataFrame
+        data = deepcopy(self.df)
+        # Return information about the DataFrame, such as column data types and the number of non-null values
+        return data.info()
+
+# Main execution block of the program
+if __name__ == "__main__":
+    # Create an instance of the DataStructure class with the "Prueva_J.json" JSON file
+    data_structure = DataStructure("Prueva_J.json")
+    # Call the decribe_df() method to get a statistical summary of the DataFrame and save it to a JSON file named "name.json"
+    data_structure.decribe_df().to_json("name")