koorukuroo

import pandas as pd
import pandas.io.data
import datetime

#text = """A, AAPL, AMCC, AMD, AMGN, AMKR, AMNT.OB, AMZN, APC, ASOG.PK, AULO.OB, BAC, BBD-A.TO, BBD-B.TO, BEEI.OB, BKSD.OB, BP.BA, BPMI.PK, C, CAJT.PK, CAT, CGFI.OB, CHINA, CHKP, CIEN, CL, CLEC, CLNE, CNLG, COKE, CPAH.OB, CPHD, CPRT, CRDN, CRGN, CSCO, CSRVE.OB, CTS, CTXS, CVM, CVX, DE, DELL, DLTR, DO, DOG, DSCM, DVNNF.OB, DYN, EGN, ELNK, ELX, EP, ERJ, ETFC, EVEH.OB, FARO, FDO, FILE, FLIR, FNLY.OB, FNPR.OB, FORC.OB, FPP, GAGO.PK, GBVS.OB, GCAP.PK, GDKI.PK, GDTI.OB, GE, GEPT.PK, GERN, GFCI.PK, GILD, GLW, GOOG, GRDB.OB, GRMN, GS, GTXO.OB, GWGI.PK, HAL, HAST, HCKT, HD, HK, HPQ, HRAL.PK, IBM, IMDS.OB, IMGM.OB, INFY, INTC, IOC, IRF, JAVA, JCP, JDSU, JNJ, JNPR, JYHW.OB, K, KDSM.OB, KKD, KLDO.OB, KO, LEG, LOW, LRCX, LU, medx, MINI, MKC, MLNK, MNLU.OB, MO, MON, MOT, MRK, MSFT, MVBY.PK, MYL, NGEN, NGLS, NOIZ, NOK, NOVL, NOVOE.OB, NTGR, NVDA, NVS, NXRA.PK, OMI, ORCL, OSTK, PDLI, PEGA, PEP, PFE, PG, PHLI.OB, PNM, PPBV.OB, PWER, PYTO.OB, PZE, PZZA, Q, QCOM, QPCIE.

koorukuroo

# -*- coding: utf-8 -*-
"""
Created on Wed Jun 18 01:37:57 2014
@author: Kyunghoon Kim
"""
import urllib2
import json
from collections import OrderedDict

s = "나는 밥을 먹었습니다" # input sentence

koorukuroo

# -*- coding: utf8 -*-
import Umorpheme.morpheme as um
from collections import OrderedDict

s = "나는 멸치 볶음 보리 밥을 롯데리아에서 한예슬과 함께 먹었습니다. 롯데리아에는 맥도날드 해피밀이 없습니다." # input sentence
data = um.analyzer(s, '23485900349', "[롯데리아,맥도날드]", 1)
temp = {}
for key, value in data.items():
    temp[int(key)] = value
data = OrderedDict(sorted(temp.items()))

koorukuroo

"""
**********
Matplotlib
**********

Draw networks with matplotlib.

See Also
--------

koorukuroo

// Includes functions for exporting active sheet or all sheets as JSON object (also Python object syntax compatible).
// Tweak the makePrettyJSON_ function to customize what kind of JSON to export.

var FORMAT_ONELINE   = 'One-line';
var FORMAT_MULTILINE = 'Multi-line';
var FORMAT_PRETTY    = 'Pretty';

var LANGUAGE_JS      = 'JavaScript';
var LANGUAGE_PYTHON  = 'Python';

koorukuroo

#!/usr/bin/env python2
# coding: utf-8
from __future__ import print_function
import sys
import re
import json
import urllib
from colorama import init, Fore, Back, Style

URL = 'http://csearch.naver.com/dcontent/spellchecker.nhn'

koorukuroo

#!/usr/bin/env python2
# coding: utf-8
from __future__ import print_function
import os
import sys
from wand.image import Image

DIMENSIONS = {
    'OSX': [
        ('icon_16x16.png',        16),

koorukuroo

# coding: utf-8
import re
import urllib
from bs4 import BeautifulSoup

class MelonSong(object):
    ARTIST_REGEXP = re.compile(r'.*goArtistDetail.*')
    ALBUM_REGEXP = re.compile(r'.*goAlbumDetail.*')
    SONG_REGEXP = re.compile(r'.*playSong.*')
    NUMBER_PARAM_REGEXP = re.compile(r'[\'\",(\s](\d+)[\'\",)]')

koorukuroo

"FROST, CARMILLA","AA2 35"
"KILLRAVEN/JONATHAN R","AA2 35"
"M'SHULLA","AA2 35"
"24-HOUR MAN/EMMANUEL","AA2 35"
"OLD SKULL","AA2 35"
"G'RATH","AA2 35"
"3-D MAN/CHARLES CHAN","M/PRM 35"
"3-D MAN/CHARLES CHAN","M/PRM 36"
"3-D MAN/CHARLES CHAN","M/PRM 37"
"HUMAN ROBOT","WI? 9"

koorukuroo

import gspread
import pandas
 
gc = gspread.login('my@email.com', 'supersecretepassword')
book = gc.open('Spreadsheet name')
sheet = book.sheet1 #choose the first sheet
dataframe = pandas.DataFrame(sheet.get_all_records())