Creating project

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+FROM dokken/ubuntu-18.04
+

README.md

+## Script para el Análisis de Archivos de Datos
+
+## Finalidad del script
+El script se usa para tener una información útil sobre un dataset de un archivo. Describe los campos de éste y muestra características importantes
+
+## Requisitos del Sistema
+- Instalar Python en su version minima de 3.7
+- Tener mapeado el interprete en el path como: python3 (Alias)
+- Tener mapeado el administrador de paquetes de python como: pip3 (Alias)
+- Tener instalado la libreria para entornos virtuales: "virtualenv", si no se tiene, instalarla de la siguiente manera:
+      
+      pip3 install virtualenv
+
+## Creación de entorno virtual
+```sh
+python3 -m virtualenv analisis
+source analisis/bin/activate
+pip3 install -r dataset-descriptor/requirements.txt
+```
+
+## Configuración
+- Configurar el separador de las tramas en el archivo dataset_descriptor/config.py. Por defecto traerá el separador=';'
+- El formato de fecha que se muestra en consola también se puede cambiar en el archivo mencionado.
+- El archivo dataset_descriptor/monedas.json contiene los símbolos de monedas que se detectará en el proceso y se indicará el tipo de dato Moneda si en caso encuentre una de ellas.
+- Los formatos de fecha admitidos para el parseo de datos de tipo fecha esta en el archivo de configuración. Se pueden agregar tantos formatos se desee.
+
+## Parámetros del script:
+```sh
+cd dataset-descriptor
+python3 -m dataset_descriptor --help
+```
+- El parámetro header (--header) se pondrá como argumento si el archivo o los archivos de la carpeta contiene header 
+
+## Ejemplos de ejecución:
+- Procesará el archivo train.csv y guardará el inforrme en prueba.json
+```sh
+python3 -m dataset_descriptor -f train.csv -o prueba.json 
+```
+
+- Procesará los archivos de la carpeta test y guardará el inforrme integral en prueba.json
+```sh
+python3 -m dataset_descriptor -f test -o prueba.json 
+```
+
+- Procesará los archivos de la carpeta test y guardará los informes en la carpeta salida
+```sh
+python3 -m dataset_descriptor -f test -o salida -s 
+```
+
+- Procesará el archivo train.csv y muestra el informe en consola
+```sh
+python3 -m dataset_descriptor -f train.csv
+```
+
+- Procesará el archivo train.csv e indicar que contiene header
+```sh
+python3 -m dataset_descriptor -f train.csv --header
+```
+
+- Procesará los archivos de la carpeta salida y le indicamos que todos sus archivos contienen header (si no se especifica -o solo muestr en consola)
+```sh
+python3 -m dataset_descriptor -f salida --header
+```
+
+- Procesará el archivo prueba.csv y lo guardara en el archivo /prueba1/prueba2/test1/test2/salida.json  (creará los directorios de forma recursiva si en caso no existen)
+```sh
+python3 -m dataset_descriptor -f prueba.csv -o /prueba1/prueba2/test1/test2/salida.json
+```
\ No newline at end of file

dataset_descriptor/__main__.py

+
+from dataset_descriptor import app
+
+if __name__=='__main__':
+    app.run()

dataset_descriptor/app.py

+import os
+import coloredlogs, logging
+import time
+import datetime
+import argparse as arg
+import dask.dataframe as dd
+from dataset_descriptor.src.utils import *
+import warnings
+
+warnings.filterwarnings("ignore")
+
+logger = logging.getLogger(__name__)
+coloredlogs.install(level='DEBUG', logger=logger)
+coloredlogs.install(level='success', logger=logger)
+
+# Get execution's parameters 
+parser = arg.ArgumentParser()
+
+parser.add_argument("-f","--file",default="__n",type=str,help="Argumento donde se especifica el archivo o carpeta a procesar.\n"+\
+                            "Si fuera una carpeta, se procesaran todos los archivos incluidos en ella.")
+
+parser.add_argument('-o','--output',default='',type=str,help="Archivo(Carpeta) de salida la cual tendra el(los) reporte(s) con las descripciones "+\
+                        "de los archivos procesados.")
+parser.add_argument('--header',action='store_true',help="Indicar si el o los archivos presentan header.")
+parser.add_argument('-s','--split',action='store_true',help="Si este flag esta presente, entonces el proceso construira un informe (archivo) para "+
+                                    "cada archivo procesado.")
+
+args = vars(parser.parse_args())
+if args["file"]=='__n':
+    logger.info("\nPor favor seleccione un archivo o carpeta para procesar con el comando -f o --file. Por ejemplo: '--file input1.csv'\n")
+    exit(0)
+if args["split"]:
+    if args["output"]=='':
+        logger.info("\nPor favor seleccione un nombre de carpeta donde se alojaran los informes. Esto es requerido al usar el flag -s o --split.\n")
+        exit(0)
+
+# Run function
+
+def run():
+    start_time = datetime.datetime.now()
+    tic = time.time()
+    logger.info("Iniciando proceso de Análisis de Archivos. Hora actual: "+start_time.strftime(cfg.datetime_format_string))
+    logger.info("El token asignado es :'"+cfg.sep+"'")
+    try:
+        if os.path.isdir(args["file"]):
+            logger.info("Se procesaran los archivos de la carpeta: "+args["file"])
+            dfs,files = proccess_dir(args["file"],args["header"])
+            logger.info("Se encontraron "+str(len(dfs))+" archivos. Creando Informe ...")
+            write_from_dir(dfs,files,args["output"],args["file"],args["split"])
+        elif os.path.isfile(args["file"]):
+            logger.info("Se procesara el archivo: "+args["file"])
+            df = proccess_file(args["file"],args["header"])
+            write_from_file(df,args["output"],args["file"])
+        else:
+            logger.info("No se encuentra el archivo especificado")
+            exit(0)
+        logger.info("Fin de proceso, tomó "+str(round(time.time() - tic,3))+" segundos")    
+
+    except Exception as error:
+        print(type(error))
+        logger.error("Existe un problema en el proceso : %s", error)
+    

dataset_descriptor/config.py

+# Separador o token de las tramas
+sep = ";"
+# formato de fecha a usar en la consola o terminal 
+datetime_format_string = '%d/%m/%Y %H:%M:%S'
+
+# formato de fechas a parsear
+parse_dates = ['%d/%m/%Y %H:%M:%S','%Y-%m-%d %H:%M:%S','%Y/%m/%d %H:%M:%S','%d-%m-%Y %H:%M:%S','%Y-%m-%d','%d-%m-%Y','%Y/%m/%d','%d/%m/%Y']
+
+# archivo de formato de las monedas
+coins_file = "dataset_descriptor/monedas.json"
+
+# sufijo a agregarle al archivo de salida, cuando se indica el parámetro --split
+sufijo = "_output.json"
+

dataset_descriptor/monedas.json

+{
+   "Monedas": [
+      {
+         "Albania": "L"
+      },
+      {
+         "Reino Unido": "£"
+      },
+      {
+         "Argelia": "د.ج"
+      },
+      {
+         "Andorra": "€"
+      },
+      {
+         "Angola": "Kz"
+      },
+      {
+         "Argentina": "$"
+      },
+      {
+         "Aruba": "ƒ"
+      },
+      {
+         "Australia": "$"
+      },
+      {
+         "Austria": "€"
+      },
+      {
+         "Bahamas": "$"
+      },
+      {
+         "Baréin, Bahrein": ".د.ب"
+      },
+      {
+         "Bangladés, Bangladesh": "৳"
+      },
+      {
+         "Barbados": "$"
+      },
+      {
+         "Bielorrusia, Belarús": "Br"
+      },
+      {
+         "Bélgica": "€"
+      },
+      {
+         "Belice": "$"
+      },
+      {
+         "Bután": "Nu."
+      },
+      {
+         "Bolivia": "Bs."
+      },
+      {
+         "Bosnia y Herzegovina": "KM"
+      },
+      {
+         "Botsuana, Botswana": "P"
+      },
+      {
+         "Brasil": "R$"
+      },
+      {
+         "Brunéi": "$"
+      },
+      {
+         "Bulgaria": "лв"
+      },
+      {
+         "Burkina Faso": "Fr"
+      },
+      {
+         "Birmania, Myanmar": "K"
+      },
+      {
+         "Burundi": "Fr"
+      },
+      {
+         "Camboya": "៛"
+      },
+      {
+         "Canadá": "$"
+      },
+      {
+         "Cabo Verde": "Esc, $"
+      },
+      {
+         "Islas Caimán": "$"
+      },
+      {
+         "República Centroafricana": "Fr"
+      },
+      {
+         "Chad": "Fr"
+      },
+      {
+         "Chile": "$"
+      },
+      {
+         "China": "¥, 元"
+      },
+      {
+         "Colombia": "$"
+      },
+      {
+         "Comores": "Fr"
+      },
+      {
+         "República Democrática del Congo": "Fr"
+      },
+      {
+         "República del Congo": "Fr"
+      },
+      {
+         "Costa Rica": "₡"
+      },
+      {
+         "Costa de Marfil, Côte d'Ivoire": "Fr"
+      },
+      {
+         "Croacia": "kn"
+      },
+      {
+         "Cuba": "$"
+      },
+      {
+         "Curação": "ƒ"
+      },
+      {
+         "Chipre": "€"
+      },
+      {
+         "República Checa": "Kč"
+      },
+      {
+         "Dinamarca": "kr"
+      },
+      {
+         "Yibuti, Djibouti": "Fr"
+      },
+      {
+         "República Dominicana": "$"
+      },
+      {
+         "Ecuador": "$"
+      },
+      {
+         "Egipto": "£, ج.م"
+      },
+      {
+         "El Salvador": "₡"
+      },
+      {
+         "Guinea Ecuatorial": "Fr"
+      },
+      {
+         "Eritrea": "Nfk"
+      },
+      {
+         "Estonia": "€"
+      },
+      {
+         "Etiopía": "Br"
+      },
+      {
+         "Finlandia": "€"
+      },
+      {
+         "Francia": "€"
+      },
+      {
+         "Polinesia Francesa": "Fr"
+      },
+      {
+         "Gabón": "Fr"
+      },
+      {
+         "Gambia": "D"
+      },
+      {
+         "Georgia": "ლ"
+      },
+      {
+         "Alemania": "€"
+      },
+      {
+         "Gana": "₵"
+      },
+      {
+         "Gibraltar": "£"
+      },
+      {
+         "Grecia": "€"
+      },
+      {
+         "Guatemala": "Q"
+      },
+      {
+         "Guinea": "Fr"
+      },
+      {
+         "Guinea-Bisáu, Guinea Bissau": "Fr"
+      },
+      {
+         "Haití": "G"
+      },
+      {
+         "Honduras": "L"
+      },
+      {
+         "Hungria": "Ft"
+      },
+      {
+         "Islandia": "kr"
+      },
+      {
+         "India": "₹"
+      },
+      {
+         "Indonesia": "Rp"
+      },
+      {
+         "Irán": "﷼"
+      },
+      {
+         "Irak": "ع.د"
+      },
+      {
+         "Irlanda": "€"
+      },
+      {
+         "Israel": "₪"
+      },
+      {
+         "Italia": "€"
+      },
+      {
+         "Jamaica": "$"
+      },
+      {
+         "Japón": "¥"
+      },
+      {
+         "Jordania": "د.ا"
+      },
+      {
+         "Kazajistán, Kazajstán": "₸"
+      },
+      {
+         "Kenia, Kenya": "Sh"
+      },
+      {
+         "Corea del Norte": "₩"
+      },
+      {
+         "Corea del Sur": "₩"
+      },
+      {
+         "Kuwait": "د.ك"
+      },
+      {
+         "Kirguzistán": "лв"
+      },
+      {
+         "Laos": "₭"
+      },
+      {
+         "Letonia": "Ls"
+      },
+      {
+         "Líbano": "ل.ل"
+      },
+      {
+         "Lesoto, Lesotho": "L"
+      },
+      {
+         "Liberia": "$"
+      },
+      {
+         "Libia": "ل.د"
+      },
+      {
+         "Lituania": "Lt"
+      },
+      {
+         "Luxemburgo": "€"
+      },
+      {
+         "Macao": "P"
+      },
+      {
+         "Macedonia": "ден"
+      },
+      {
+         "Madagascar": "Ar"
+      },
+      {
+         "Malaui, Malawi": "MK"
+      },
+      {
+         "Malasia": "RM"
+      },
+      {
+         "Maldivas": ".ރ"
+      },
+      {
+         "Mali": "Fr"
+      },
+      {
+         "Malta": "€"
+      },
+      {
+         "Mauritania": "UM"
+      },
+      {
+         "Mauricio": "₨"
+      },
+      {
+         "México": "$"
+      },
+      {
+         "Estados Federados de Micronesia": "$"
+      },
+      {
+         "Moldavia": "L"
+      },
+      {
+         "Mónaco": "€"
+      },
+      {
+         "Mongolia": "₮"
+      },
+      {
+         "Montenegro": "€"
+      },
+      {
+         "Marruecos": "د.م."
+      },
+      {
+         "Mozambique": "MT"
+      },
+      {
+         "Namibia": "$"
+      },
+      {
+         "Nauru": "$"
+      },
+      {
+         "Nepal": "₨"
+      },
+      {
+         "Países Bajos": "€"
+      },
+      {
+         "Nueva Caledonia": "Fr"
+      },
+      {
+         "Nueva Zelanda": "$"
+      },
+      {
+         "Nicaragua": "C$"
+      },
+      {
+         "Níger": "Fr"
+      },
+      {
+         "Nigeria": "₦"
+      },
+      {
+         "Noruega": "kr"
+      },
+      {
+         "Omán": "ر.ع."
+      },
+      {
+         "Paquistán": "₨"
+      },
+      {
+         "Panamá": "B/."
+      },
+      {
+         "Papua-Nueva Guiné": "K"
+      },
+      {
+         "Paraguay": "₲"
+      },
+      {
+         "Perú": "S/"
+      },
+      {
+         "Filipinas": "₱"
+      },
+      {
+         "Polonia": "zł"
+      },
+      {
+         "Portugal": "€"
+      },
+      {
+         "Catar, Qatar": "ر.ق"
+      },
+      {
+         "Rumanía": "L"
+      },
+      {
+         "Rusia": "₽"
+      },
+      {
+         "Ruanda, Rwanda": "Fr"
+      },
+      {
+         "San Cristóbal y Nieves, Saint Kitts y Nevis": "$"
+      },
+      {
+         "Santa Lucía": "$"
+      },
+      {
+         "San Viccente y las Granadinas": "$"
+      },
+      {
+         "Samoa": "T"
+      },
+      {
+         "San Marino": "€"
+      },
+      {
+         "Santo Tomé y Príncipe": "Db"
+      },
+      {
+         "Arabia Saudí": "ر.س"
+      },
+      {
+         "Senegal": "Fr"
+      },
+      {
+         "Serbia": "дин. o din."
+      },
+      {
+         "Seichelles": "₨"
+      },
+      {
+         "Sierra Leona": "Le"
+      },
+      {
+         "Singapur": "$"
+      },
+      {
+         "Eslovaquia": "€"
+      },
+      {
+         "Eslovenia": "€"
+      },
+      {
+         "Islas Salomón": "$"
+      },
+      {
+         "Somalia": "Sh"
+      },
+      {
+         "Sudáfrica": "R"
+      },
+      {
+         "España": "€"
+      },
+      {
+         "Sudán del Sur": "£"
+      },
+      {
+         "Sri Lanka": "Rs"
+      },
+      {
+         "Sudán": "£"
+      },
+      {
+         "Surinám": "$"
+      },
+      {
+         "Suazilandia, Swazilandia": "L"
+      },
+      {
+         "Suecia": "kr"
+      },
+      {
+         "Suiza": "Fr"
+      },
+      {
+         "Siria": "£ o ل.س"
+      },
+      {
+         "Taiwán": "$"
+      },
+      {
+         "Tayikistán": "ЅМ"
+      },
+      {
+         "Tanzania": "Sh"
+      },
+      {
+         "Tailandia": "฿"
+      },
+      {
+         "Togo": "Fr"
+      },
+      {
+         "Tonga": "T$"
+      },
+      {
+         "Trindade e Tobago": "$"
+      },
+      {
+         "Túnez": "د.ت"
+      },
+      {
+         "Turkmenistán": "m"
+      },
+      {
+         "Uganda": "Sh"
+      },
+      {
+         "Ucrania": "₴"
+      },
+      {
+         "Emiratos Árabes Unidos": "د.إ"
+      },
+      {
+         "Estados Unidos": "$"
+      },
+      {
+         "Uruguay": "$"
+      },
+      {
+         "Uzbequistán": "лв"
+      },
+      {
+         "Vanuatu": "Vt"
+      },
+      {
+         "Ciudad del Vaticano": "€"
+      },
+      {
+         "Venezuela": "Bs F"
+      },
+      {
+         "Vietnam": "₫"
+      },
+      {
+         "Yemen": "﷼"
+      },
+      {
+         "Zambia": "ZK"
+      },
+      {
+         "Zimbabue, Zimbabwe": "$"
+      }
+   ]
+}
\ No newline at end of file

dataset_descriptor/src/utils.py

+import datetime
+import os
+import json
+import time
+import numpy as np
+import pandas as pd
+import dask.dataframe as dd
+from pandas.io.parsers import count_empty_vals
+from dataset_descriptor import config as cfg
+from os import path
+import enum
+import coloredlogs, logging
+logger = logging.getLogger(__name__)
+coloredlogs.install(level='DEBUG', logger=logger)
+
+# Clase Enum no deja incluir atributo datetime64[ns] y también no se puede repetir 2 atributos con el mismo valor.
+class DataType(enum.Enum):
+    str          = "Alfanumerico"
+    int          = "Entero"
+    float        = "Decimal"
+    datetime     = "Fecha"
+    Moneda       = "Moneda"
+    vacio        = "Vacío"
+
+class Moneda:
+    def __init__(self,value,simbolo):
+        self.value = value
+        self.simbolo = simbolo
+    def __str__(self):
+        return self.value
+
+try:
+    with open(cfg.coins_file,'r',encoding="utf8") as file:
+        coins = json.load(file)
+except FileNotFoundError as er:
+    logger.error("No se encuetra el archivo de símbolos de monedas. Por favor configúrelo en el archivo de configuración")
+    exit(0)
+    
+
+def set_data_type(x):           
+    for tp in [float,int,datetime.datetime.strptime,str]:
+        try:
+            if tp==float and len(str(x).split("."))==1 : continue
+            if tp==float and len(str(x).split("."))==2 and int(str(x).split(".")[-1])==0: continue
+            if tp==datetime.datetime.strptime:
+                for pars in cfg.parse_dates:
+                    try: 
+                        x = tp(x,pars)
+                        break
+                    except Exception as err:
+                        continue
+            else:
+                x = tp(x)
+            if(type(x).__name__==DataType.str.name): 
+                for i in coins["Monedas"]:
+                    key = list(i.keys())[0]
+                    if x.startswith(i[key]):
+                        _ = float(x.replace(i[key],"").replace(",",""))
+                        x = Moneda(x,i[key])
+                        break
+            break
+        except ValueError as er:
+            continue
+        except TypeError as er:
+            continue
+    return x
+
+def proccess_file(file_path,header):
+    if header: 
+        df = dd.read_csv(file_path,sep=cfg.sep)
+    else: 
+        df = dd.read_csv(file_path,sep=cfg.sep,header=None)
+        df.columns = df.columns +1
+    news = df.compute()
+    # Get type data column 
+    for col in news.columns:
+        news[col] = news[col].replace(np.nan,"")
+        news[col] = news[col].apply(set_data_type)
+    news = dd.from_pandas(news,npartitions=3)
+    
+    return news
+
+def proccess_dir(dir_path,header):
+    files = os.listdir(dir_path)
+    finals = []
+    for file in files:
+        df = proccess_file(dir_path+"/"+file,header)
+        finals.append(df)
+    return finals,files
+
+
+def write_from_file(df,output_file='',input_file='',output_dir='',split=True):
+    data = {}
+    time_ = datetime.datetime.now()
+    data.update({"Archivo Procesado":input_file,"Hora Procesado":time_.strftime(cfg.datetime_format_string),"Columnas":[]})
+    if output_file.find(".")!=-1 and len(output_file)>1:
+        logger.info("Creando archivo json")
+    else:
+        logger.info("No hay archivo de salida seleccionado, mostrando solo en pantalla")
+    start = time.time()
+    
+    for num_col,col in enumerate(df.columns):
+        min_lenght,max_lenght = '',''
+        min_value,max_value,mean_value = '','',''
+        nan_values,no_nan_values = '',''
+        counts = ''
+
+        if df[col].dtype=='object':
+            data_type = [i.__name__ for i in df[col].apply(type).compute().value_counts().index.values]
+            if len(data_type)>1:
+                types = [DataType[i].value for i in data_type]
+                types = ','.join(types)
+
+                nan_values = df[col].isna().sum().compute()
+                no_nan_values = df[col].notnull().count().compute() - nan_values
+                counts = [i for i in df[col].apply(type).compute().value_counts().values]
+                counts = {DataType[i].value:j for i,j in zip(data_type,counts)}
+                data["Columnas"].append({"Columna":col,"Caracteristicas":[{"Tipos de Dato":types,"Tipo":[],
+                "Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values)}]})
+                for i,j in enumerate(data_type):
+                    data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"].append({DataType[j].value:[]})
+                    aux = [type(x).__name__==j for x in df[col].compute()]
+                    aux = df[col].compute().loc[aux]
+                    count = aux.shape[0]
+                    random_row = aux.sample(n=1).values[0]
+                    if j==DataType.int.name or j==DataType.float.name:
+                        if aux.isnull().all():
+                            min_value,max_value,mean_value = '','', ''
+                            min_lenght = ''
+                            max_lenght = ''
+                            random_row = ''
+                            data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),"Mínimo Valor":min_value,
+                            "Máximo Valor":max_value,"Valor Promedio":mean_value,"Mínimo dígitos":min_lenght,
+                            "Máximo dígitos":max_lenght,"Valor Ejemplo":random_row})
+                        elif j==DataType.float.name:
+                            integer_part = aux.apply(lambda x:str(float(x))).apply(lambda x: x.split(".")[0])
+                            decimal_part = aux.apply(lambda x:str(float(x))).apply(lambda x: "" if x.split(".")[1]=="0" else x.split(".")[1])
+                            min_value,max_value,mean_value = aux.min(), aux.max(), round(aux.mean(),2)
+                            min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+                            min_decimal, max_decimal = decimal_part.str.len().min(), decimal_part.str.len().max()
+                            data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),"Mínimo Valor":str(min_value),
+                            "Máximo Valor":str(max_value),"Valor Promedio":str(mean_value),"Mínimo dígitos enteros":str(min_lenght),
+                            "Máximo dígitos enteros":str(max_lenght),"Mínimo dígitos decimales":str(min_decimal),"Máximo dígitos decimales":str(max_decimal),
+                            "Valor Ejemplo":str(random_row)})
+                        else:
+                            integer_part = aux.apply(lambda x:str(float(x))).apply(lambda x: x.split(".")[0])
+                            min_value,max_value,mean_value = aux.min(), aux.max(), round(aux.mean(),2)
+                            min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+                            data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),"Mínimo Valor":str(min_value),
+                            "Máximo Valor":str(max_value),"Valor Promedio":str(mean_value),"Mínimo dígitos":str(min_lenght),
+                            "Máximo dígitos":str(max_lenght),"Valor Ejemplo":str(random_row)})
+
+                    elif j==DataType.datetime.name:
+                        min_value,max_value = aux.min().strftime(cfg.datetime_format_string), aux.max().strftime(cfg.datetime_format_string)
+                        random_row = random_row.strftime(cfg.datetime_format_string)
+                        data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),"Fecha Mínima":str(min_value),
+                        "Fecha Máxima":str(max_value),"Valor Ejemplo":str(random_row)})
+                        
+                    elif j==DataType.Moneda.name:                        
+                        integer_part =  aux.apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float).astype(str).\
+                                    apply(lambda x: x.split(".")[0])
+                        decimal_part =  aux.apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float).astype(str).\
+                                    apply(lambda x: "" if x.split(".")[1]=="0" else x.split(".")[1])
+                        min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+                        min_decimal, max_decimal = decimal_part.str.len().min(), decimal_part.str.len().max()
+                        value_part = aux.apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float)
+                        min_value = random_row.simbolo+ format(value_part.min(),',.3f')
+                        max_value = random_row.simbolo+ format(value_part.max(),',.3f')
+
+                        data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),
+                        "Valor Mínimo":min_value,"Valor Máximo":max_value,"Mínimo dígitos enteros":str(min_lenght),"Máximo dígitos enteros":str(max_lenght),
+                        "Mínimo dígitos decimales":str(min_decimal),"Máximo dígitos decimales":str(max_decimal),"Valor Ejemplo":str(random_row)})
+                    else:
+                        min_lenght = aux.astype(str).str.len().min()
+                        max_lenght = aux.astype(str).str.len().max()
+                        data["Columnas"][num_col]["Caracteristicas"][0]["Tipo"][i][DataType[j].value].append({"Cantidad":str(count),
+                        "Mínima Longitud":str(min_lenght),"Máxima Longitud":str(max_lenght),"Valor Ejemplo":str(random_row)})
+                
+                    
+            else:
+                counts = df[col].count().compute()
+                if df[col].apply(lambda x:True if x=="" else False).compute().all():
+                    min_lenght,max_lenght = '',''
+                    nan_values, no_nan_values = counts, 0
+                    random_row = ""
+                    data_type = DataType.vacio.name
+                else:
+                    data_type = str(data_type[0])
+                    min_lenght = df[col].astype(str).str.len().min().compute()
+                    max_lenght = df[col].astype(str).str.len().max().compute()
+                    nan_values = df[col].isna().sum().compute()
+                    no_nan_values = df[col].notnull().count().compute() - nan_values
+                    random_row = df[col].sample(n=1).values.compute()[0]
+                data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[data_type].value,"Cantidad de Datos":str(counts),
+                "Mínima Longitud":str(min_lenght),"Máxima Longitud":str(max_lenght),"Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+                "Valor Ejemplo":str(random_row)}]})
+
+            
+        elif df[col].dtype==DataType.datetime.name or df[col].dtype=='datetime64[ns]':
+            data_type = DataType.datetime.name
+            
+            min_value,max_value = df[col].min().compute().strftime(cfg.datetime_format_string), df[col].max().compute().strftime(cfg.datetime_format_string)
+            
+            counts = df[col].count().compute()
+            nan_values = df[col].isna().sum().compute()
+            no_nan_values = df[col].notnull().count().compute() - nan_values
+            random_row = df[col].sample(n=1).values.compute()
+            random_row = pd.to_datetime(str(random_row[0])).strftime(cfg.datetime_format_string)
+            data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[str(data_type)].value,"Cantidad de Datos":str(counts),
+            "Mínima Fecha":str(min_value),"Máxima Fecha":str(max_value),"Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+            "Valor Ejemplo":str(random_row)}]})
+            
+
+        elif df[col].dtype==DataType.Moneda.name:
+            data_type = df[col].dtype
+            random_row = df[col].sample(n=1).values.compute()
+            integer_part =  df[col].apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float).astype(str).\
+                                    apply(lambda x: x.split(".")[0])
+            decimal_part =  df[col].apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float).astype(str).\
+                                    apply(lambda x: "" if x.split(".")[1]=="0" else x.split(".")[1])
+            min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+            min_decimal, max_decimal = decimal_part.str.len().min(), decimal_part.str.len().max()
+            value_part = df[col].apply(lambda x:str(x).replace(x.simbolo,"").replace(",","")).astype(float)
+            min_value = random_row.simbolo+ format(value_part.min(),',.3f')
+            max_value = random_row.simbolo+ format(value_part.max(),',.3f')
+
+            data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[str(data_type)].value,"Cantidad de Datos":str(counts),
+            "Valor Mínimo":min_value,"Valor Máximo":max_value,"Mínimo dígitos enteros":str(min_lenght),"Máximo dígitos enteros":str(max_lenght),
+            "Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+            "Mínimo dígitos decimales":str(min_decimal),"Máximo dígitos decimales":str(max_decimal),"Valor Ejemplo":str(random_row[0])}]})
+
+        else:
+            data_type = DataType.int.name if df[col].dtype=="int64" else df[col].dtype
+            data_type = DataType.float.name if df[col].dtype=="float64" else data_type
+            random_row = df[col].sample(n=1).values.compute()[0]
+            counts = df[col].count().compute()
+            nan_values = df[col].isna().sum().compute()
+            no_nan_values = df[col].notnull().count().compute() - nan_values
+            min_value,max_value,mean_value = df[col].min().compute(), df[col].max().compute(), round(df[col].mean().compute(),2)
+            if df[col].isnull().compute().all():
+                min_value,max_value,mean_value = '', '', ''
+                random_row = ''
+                min_lenght = ''
+                max_lenght = ''
+                data_type = 'vacio'
+                data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[str(data_type)].value,"Cantidad de Datos":str(counts),
+                "Mínimo Valor":str(min_value),
+                "Máximo Valor":str(max_value),"Valor Promedio":str(mean_value),"Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+                "Valor Ejemplo":str(random_row)}]})
+            elif df[col].dtype==DataType.float.name:
+                
+                integer_part = df[col].compute().apply(lambda x:str(float(x))).apply(lambda x: x.split(".")[0])
+                decimal_part = df[col].compute().apply(lambda x:str(float(x))).apply(lambda x: "" if x.split(".")[1]=="0" else x.split(".")[1])
+                min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+                min_decimal, max_decimal = decimal_part.str.len().min(), decimal_part.str.len().max()
+            
+                data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[str(data_type)].value,"Cantidad de Datos":str(counts),
+                "Mínimo dígitos enteros":str(min_lenght),"Máximo dígitos enteros":str(max_lenght),"Mínimo dígitos decimales":str(min_decimal),
+                "Máximo dígitos decimales":str(max_decimal),"Mínimo Valor":str(min_value),"Máximo Valor":str(max_value),
+                "Valor Promedio":str(mean_value),"Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+                "Valor Ejemplo":str(random_row)}]})
+            else:
+                integer_part = df[col].compute().apply(lambda x:str(float(x))).apply(lambda x: x.split(".")[0])
+                min_lenght, max_lenght = integer_part.str.len().min(), integer_part.str.len().max()
+                data["Columnas"].append({"Columna":col,"Características":[{"Tipo de Dato":DataType[str(data_type)].value,"Cantidad de Datos":str(counts),
+                "Mínimo dígitos":str(min_lenght),"Máximo dígitos":str(max_lenght),"Mínimo Valor":str(min_value),
+                "Máximo Valor":str(max_value),"Valor Promedio":str(mean_value),"Valores Nulos":str(nan_values),"Valores No Nulos":str(no_nan_values),
+                "Valor Ejemplo":str(random_row)}]})
+    
+    if split:
+        
+        print(json.dumps(data,indent=3,ensure_ascii=False))   
+
+
+    if output_file.find(".")!=-1 and len(output_file)>2:
+        if output_dir!='':
+            with open(output_dir+"/"+output_file,'w') as file:   
+                json.dump(data,file,indent=4)
+                logger.info("Archivo "+output_file+" procesado y guardado en la carpeta "+output_dir)
+        else:
+            if split:
+                if os.path.isdir(output_file)==False:
+                    os.makedirs(os.path.dirname(output_file))
+                with open(output_file,'w') as file:   
+                    json.dump(data,file,indent=4)
+                    logger.info("Archivo procesado y guardado en "+output_file)
+            else:
+                return data
+
+    logger.info("Fin de creación de archivo json, tomó "+str(round(time.time() - start,3))+" segundos") 
+    
+
+
+        
+
+def write_from_dir(dfs,files,output,input_dir,split_files):
+    if split_files and output!='':
+        if os.path.exists(output)==False: os.makedirs(output) 
+        for df,file in zip(dfs,files):
+            if output!='':
+                logger.info("Procesando archivo "+file+". Se genera el archivo de salida "+file+cfg.sufijo+" y se guardara en la carpeta "+output)
+                write_from_file(df,file+cfg.sufijo,file,output)
+            else:
+                write_from_file(df,'',file)
+    else:
+
+        final = {}
+        final.update({"Archivos_Procesados":[]})
+        for df,file in zip(dfs,files):
+            logger.info("Procesando archivo "+file)
+            aux = write_from_file(df,output,file,'',False)
+            final["Archivos_Procesados"].append(aux)
+        print(json.dumps(final,indent=3,ensure_ascii=False))
+
+
+
+
+
+
+
+
+
+
+
+
+
+

requirements.txt

+bokeh==2.3.2
+click==8.0.1
+cloudpickle==1.6.0
+coloredlogs==15.0.1
+dask==2.19.0
+distributed==2.19.0
+fsspec==2021.6.1
+HeapDict==1.0.1
+humanfriendly==9.2
+Jinja2==3.0.1
+locket==0.2.1
+MarkupSafe==2.0.1
+msgpack==1.0.2
+numpy==1.21.0
+packaging==20.9
+pandas==1.2.4
+partd==1.2.0
+Pillow==8.2.0
+psutil==5.8.0
+pyparsing==2.4.7
+python-dateutil==2.8.1
+pytz==2021.1
+PyYAML==5.4.1
+six==1.16.0
+sortedcontainers==2.4.0
+tblib==1.7.0
+toolz==0.11.1
+tornado==6.1
+typing-extensions==3.10.0.0
+zict==2.0.0

test_files/prueba11.csv

+Vt6,150,593;22;0.2;1
+123;G_G;T_T;1
+4.2;4.11;ASD;1.2
+3333.22;25003;roberto;1332.3313
+esto es una cadena;11123123;123123.12312312;otra cadena
+20/01/2005 17:16:17;1;algo;12.11
+Vt5,150.222;23;0.9;2

test_files/prueba12.csv

+Vt6,150,593;22;0.2;1;10/02/2005 17:16:17
+123;G_G;T_T;1;20-01-2005 12:16:17
+4.2;4.11;ASD;1.2;20/01/2010 17:16:44
+3333.22;25003;roberto;1332.3313;05/09/1998 04:22:17
+esto es una cadena;11123123;123123.12312312;otra cadena;25/05/2015 12:16:17
+20/01/2005 17:16:17;1;algo;12.11;20-1-2005 17:16:11
+Vt5,150.222;23;0.9;2;20/01/2005

test_files/train.csv

+PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
+1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
+2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
+3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
+4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
+5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
+6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
+7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
+8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
+9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
+10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
+11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
+12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
+13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
+14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
+15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
+16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
+17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q
+18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
+19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S
+20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C
+21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S
+22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S
+23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q
+24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
+25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S
+26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
+27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
+28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
+29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
+30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
+31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C
+32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C
+33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q
+34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S
+35,0,1,"Meyer, Mr. Edgar Joseph",male,28,1,0,PC 17604,82.1708,,C
+36,0,1,"Holverson, Mr. Alexander Oskar",male,42,1,0,113789,52,,S
+37,1,3,"Mamee, Mr. Hanna",male,,0,0,2677,7.2292,,C
+38,0,3,"Cann, Mr. Ernest Charles",male,21,0,0,A./5. 2152,8.05,,S
+39,0,3,"Vander Planke, Miss. Augusta Maria",female,18,2,0,345764,18,,S
+40,1,3,"Nicola-Yarred, Miss. Jamila",female,14,1,0,2651,11.2417,,C
+41,0,3,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,1,0,7546,9.475,,S
+42,0,2,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,1,0,11668,21,,S
+43,0,3,"Kraeff, Mr. Theodor",male,,0,0,349253,7.8958,,C
+44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C
+45,1,3,"Devaney, Miss. Margaret Delia",female,19,0,0,330958,7.8792,,Q
+46,0,3,"Rogers, Mr. William John",male,,0,0,S.C./A.4. 23567,8.05,,S
+47,0,3,"Lennon, Mr. Denis",male,,1,0,370371,15.5,,Q
+48,1,3,"O'Driscoll, Miss. Bridget",female,,0,0,14311,7.75,,Q
+49,0,3,"Samaan, Mr. Youssef",male,,2,0,2662,21.6792,,C
+50,0,3,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,1,0,349237,17.8,,S
+51,0,3,"Panula, Master. Juha Niilo",male,7,4,1,3101295,39.6875,,S
+52,0,3,"Nosworthy, Mr. Richard Cater",male,21,0,0,A/4. 39886,7.8,,S
+53,1,1,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,1,0,PC 17572,76.7292,D33,C
+54,1,2,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,1,0,2926,26,,S
+55,0,1,"Ostby, Mr. Engelhart Cornelius",male,65,0,1,113509,61.9792,B30,C
+56,1,1,"Woolner, Mr. Hugh",male,,0,0,19947,35.5,C52,S
+57,1,2,"Rugg, Miss. Emily",female,21,0,0,C.A. 31026,10.5,,S
+58,0,3,"Novel, Mr. Mansouer",male,28.5,0,0,2697,7.2292,,C
+59,1,2,"West, Miss. Constance Mirium",female,5,1,2,C.A. 34651,27.75,,S
+60,0,3,"Goodwin, Master. William Frederick",male,11,5,2,CA 2144,46.9,,S
+61,0,3,"Sirayanian, Mr. Orsen",male,22,0,0,2669,7.2292,,C
+62,1,1,"Icard, Miss. Amelie",female,38,0,0,113572,80,B28,
+63,0,1,"Harris, Mr. Henry Birkhardt",male,45,1,0,36973,83.475,C83,S
+64,0,3,"Skoog, Master. Harald",male,4,3,2,347088,27.9,,S
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