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# galería de gráficos: gasolinas (heatmap+violines) + ipsa + other good ones
import seaborn as sns
import pandas as pd

#1 IPSA:
#2 CNE
#3 

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import boto3
import os, sys

s3 = boto3.resource('s3')

def down(canal,token):
    x = os.popen(f'lss3 matinales/audio/{canal}/|find "{token}"').read()
    files=[f for f in x.split() if 'mp3' in f]
    print(files)
    for f in files:

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# https://gis.stackexchange.com/questions/113799/how-to-read-a-shapefile-in-python
# http://geospatialpython.com/2011/09/reading-shapefiles-from-cloud.html
# https://medium.com/@loldja/reading-shapefile-zips-from-a-url-in-python-3-93ea8d727856
# http://andrewgaidus.com/Reading_Zipped_Shapefiles/
# https://gis.stackexchange.com/questions/113799/how-to-read-a-shapefile-in-python

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import os, requests, time
import sqlite3, pandas as pd
from bs4 import BeautifulSoup

STATIC_FOLDER = os.getenv('STATIC_FOLDER')
CANALES = ['rec-tv','canal-13-c','mega','canal-13','tvn','chilevision','ucv-tv',
            'tnt','la-red','fox','tnt','hbo','sony','axn','warner','a-e-mundo',
            'universal-channel','space','fx']
#        'tvn-24h'

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import pandas as pd
from geopandas import GeoDataFrame
from shapely.geometry import Point
import fiona

df = pd.read_csv('data.csv')

geometry = [Point(xy) for xy in zip(df.x, df.y)]
crs = {'init': 'epsg:2263'} #http://www.spatialreference.org/ref/epsg/2263/
geo_df = GeoDataFrame(df, crs=crs, geometry=geometry)

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import os, time
from pprint import pprint
from collections import defaultdict
from win32com.client import Dispatch

t0 = time.time()
outlook=Dispatch("Outlook.Application").GetNamespace("MAPI")
#inbox = outlook.GetDefaultFolder("6")
confi = outlook.Folders(2).Folders(2)    # found by trial and error
counts = defaultdict(int)

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from flask import Flask
from flask_sqlalchemy import SQLAlchemy
import os
import graphene
from graphene_sqlalchemy import SQLAlchemyObjectType, SQLAlchemyConnectionField
from flask_graphql import GraphQLView
#################################
app = Flask(__name__)
app.debug = True

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{
  "nodes": [
    {
      "id": "DAG INGENIERIA Y CONSTRU",
      "group": 0
    },
    {
      "id": "ALBEMARLE LIMITADA (ROCK",
      "group": 1
    },

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import requests, pandas as pd
from bs4 import BeautifulSoup

CLIO_DEF = 'https://www.yapo.cl/chile/inmuebles?ca=15_s&l=0&q=casa&cmn=&st=a'

def text_search(bs, classname):
    return [p0.text.strip() 
            for p0 in bs.find_all('span', attrs={'class': classname})]

def scrape_yapo(url = CLIO_DEF):

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import requests, pandas as pd
from bs4 import BeautifulSoup

CLIO_DEF = 'https://www.yapo.cl/chile/inmuebles?ca=15_s&l=0&q=casa&cmn=&st=a'

def text_search(bs, classname):
    return [p0.text.strip() 
            for p0 in bs.find_all('span', attrs={'class': classname})]

def scrape_yapo(url = CLIO_DEF):