sergiolucero

import spotipy
import spotipy.util as util
from creds import CLIENT_ID, CLIENT_SECRET

token = util.prompt_for_user_token(username = 'sergiolucero', scope='',
                                   client_id=CLIENT_ID,
                                   client_secret=CLIENT_SECRET,
                                   redirect_uri='http://quant.cl/what'
                                  )

sergiolucero

import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from IPython.display import HTML

trace = go.Sunburst(
    labels=["Carlina", "Alejandro", "Sylvia", "Daniel", "Ingrid", "Juan", "Caty", "Sergio", "Laura", "Miguel"],
    parents=["", "Carlina", "Carlina", "Sylvia", "Sylvia", "Carlina", "Carlina", "Caty", "Carlina", "Carlina"],
    values=[10, 14, 12, 10, 2, 6, 6, 4, 4, 6],
    outsidetextfont = {"size": 20, "color": "#377eb8"},    marker = {"line": {"width": 2}},
)

sergiolucero

from pptx import Presentation
from pptx.util import Inches
import glob

SLIDE_LAYOUT_TITLE_AND_CONTENT = 1
FILTER = 'fotos/*.jpg'     # what to include

prs = Presentation()
slide_layout = prs.slide_layouts[SLIDE_LAYOUT_TITLE_AND_CONTENT]

sergiolucero

from math import atan
import folium, pandas as pd

viajes = pd.read_html('http://quant.cl/blc_read')[0]

fm = folium.Map(location=[-33.41,-70.59], zoom_start=14, 
                width=1000, height=400, tiles='stamenwatercolor')

for idx, row in viajes.iterrows():
    fromloc, toloc = eval(row['fromloc']), eval(row['toloc'])      # viene como "string"

sergiolucero

import requests, pandas as pd
from bs4 import BeautifulSoup
pd.set_option('max_colwidth',-1)

base_url = 'https://www.cntv.cl/cntv/site/tax/port/all/taxport_16___1.html'
bs = BeautifulSoup(requests.get(base_url).text, 'lxml')

top = pd.DataFrame()
links = [link for link in bs.find_all('a') if 'más' in link.text]
print(f'{len(links)} meses de denuncias')

sergiolucero

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):

sergiolucero

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):

sergiolucero

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

sergiolucero

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

sergiolucero

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)