alex2awesome

import pandas as pd 
from gensim.sklearn_api import LdaTransformer
from gensim.corpora import Dictionary
from sklearn.base import BaseEstimator, MetaEstimatorMixin
import re
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import CountVectorizer
from collections import defaultdict

alex2awesome

## Because Seaborn doesn't allow custom formatting for annotations, you have to do this crazy workaround to access the text:

def formatFloat(fmt, val):
  ret = fmt % val
  if ret.startswith("0."):
    return ret[1:]
  if ret.startswith("-0."):
    return "-" + ret[2:]
  return ret

alex2awesome

//so far, this opens a new page and embeds the video in this page. 

javascript:

window.open().document.write(
    '<iframe id = \"video\" title=\"YouTube video player\" class=\"youtube-player\" type=\"text/html\"' +
    'width=\"560 \" height=\"315\" src=\"http://www.youtube.com/embed/
' + location.search.split(/=/)[1] + '\"' +
    'frameborder=\"0\" allowFullScreen></iframe>')