#!/usr/bin/env python
# coding: utf-8

# In[7]:


# %load get_rotten.py
__author__ = 'ju'
import json
import pandas as pd
import numpy as np
import requests
from urllib2 import Request, urlopen, URLError
from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh.models import HoverTool, BoxSelectTool
import bokeh

output_notebook()
# df = pd.read_csv('IMDB_7000.txt',sep='\t')
# df = df[df['Votes']>=50000]
# print df
#
# #print '%'.join(['The','Shawshank'])
# imdb = []
# rt = []
# rated = []
# year = []
# genre = []
#
# for i in df.index:
#     url = 'http://www.omdbapi.com/?t='+'%25'.join(df.loc[i,'Title'].split(' '))+'&y='+str(int(df.loc[i,'Year']))+'&tomatoes=true'
#     result = json.load(urlopen(url))
#     print df.loc[i,'Title']
#     if 'imdbRating' in result:
#         imdb.append(result['imdbRating'])
#     else:
#         imdb.append(np.nan)
#     if 'tomatoMeter' in result:
#         rt.append(result['tomatoMeter'])
#     else: rt.append(np.nan)
#     if 'Year' in result:
#         year.append(result['Year'])
#     else: year.append(np.nan)
#     if 'Genre' in result:
#         genre.append(result['Genre'])
#     else: genre.append(np.nan)
#     if 'Rated' in result:
#         rated.append(result['Rated'])
#     else: rated.append(np.nan)
# df['Year'] = pd.Series(year,index=df.index)
# df['Genre'] = pd.Series(genre,index=df.index)
# df['Rated'] = pd.Series(rated,index=df.index)
# df['IMDB Rating'] = pd.Series(imdb,index=df.index)
# df['Rotten Tomatoes'] = pd.Series(rt, index=df.index)
#
# df=df.dropna()
# print df
# df.to_csv('IMDB_RT_some.txt',sep='\t',index=False)



df = pd.read_csv('IMDB_RT_some.txt',sep='\t')
#df=df.drop('Unnamed: 0',axis=1)
df=df.dropna()

allgen = []
for i in df['Genre']:
    allgen=allgen+i.split(', ')
#print set(allgen)
#print set(df['Rated'])


output_file("toolbar.html")
source = ColumnDataSource(
        data=dict(
            x=df['Rank'].tolist(),
            y=df['Rotten Tomatoes'].tolist(),
            desc=df['Title'].tolist(),
        )
    )

hover = HoverTool(
        tooltips=[
            ("Title", "@desc"),
            ("(x,y)", "($x, $y)"),


        ]
    )




hover = HoverTool(
        tooltips=[
            #("index", "$index"),
            ("Title", "@desc"),
            ('IMDB Rating', '@ra'),
            ('Rotten Tomatoes', '@rt')
            #("(x,y)", "($x, $y)"),

        ]
    )
r = df[df['Rated']=='R']
rsource = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in r['Rank'].tolist()],
            rt=[str(int(i)) for i in r['Rotten Tomatoes'].tolist()],
            desc=r['Title'].tolist(),
        )
    )
pg13 = df[df['Rated']=='PG-13']
pg13source = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in pg13['Rank'].tolist()],
            rt=[str(int(i)) for i in pg13['Rotten Tomatoes'].tolist()],
            desc=pg13['Title'].tolist(),
        )
    )
pg = df[df['Rated']=='PG']
pgsource = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in pg['Rank'].tolist()],
            rt=[str(int(i)) for i in pg['Rotten Tomatoes'].tolist()],
            desc=pg['Title'].tolist(),
        )
    )
g = df[df['Rated']=='G']
gsource = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in g['Rank'].tolist()],
            rt=[str(int(i)) for i in g['Rotten Tomatoes'].tolist()],
            desc=g['Title'].tolist(),
        )
    )
nc17 = df[df['Rated']=='NC-17']
nc17source = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in nc17['Rank'].tolist()],
            rt=[str(int(i)) for i in nc17['Rotten Tomatoes'].tolist()],
            desc=nc17['Title'].tolist(),
        )
    )
other = df[df['Rated'].isin(['GP','M','NOT RATED','PASSED','X','UNRATED','APPROVED'])]
othersource = ColumnDataSource(
        data=dict(
            ra=[str(i) for i in other['Rank'].tolist()],
            rt=[str(int(i)) for i in other['Rotten Tomatoes'].tolist()],
            desc=other['Title'].tolist(),
        )
    )


p = figure(title='IMDB vs. RT', tools=[hover], x_axis_label='IMDB Rating',y_axis_label='Rotten Tomatoes Rating')
#p.scatter(df['Rank'].tolist(), df['Rotten Tomatoes'], size=5, source=source)
p.scatter(nc17['Rank'].tolist(), nc17['Rotten Tomatoes'].tolist(), size=5, source=nc17source,color='orange',legend='NC-17')
p.scatter(r['Rank'].tolist(), r['Rotten Tomatoes'].tolist(), size=5, source=rsource, color='red',legend='R')
p.scatter(pg13['Rank'].tolist(), pg13['Rotten Tomatoes'].tolist(), size=5, source=pg13source,color='blue',legend='PG-13')
p.scatter(pg['Rank'].tolist(), pg['Rotten Tomatoes'].tolist(), size=5,source=pgsource, color='green',legend='PG')
p.scatter(g['Rank'].tolist(), g['Rotten Tomatoes'].tolist(), size=5, source=gsource,color='#32cd32',legend='G')
p.scatter(other['Rank'].tolist(), other['Rotten Tomatoes'].tolist(), source=othersource,size=5,color='grey',legend='other')

p.legend.orientation = 'bottom_right'


show(p)


# In[8]:


from IPython.display import HTML


# In[9]:


HTML('''<script>
code_show=true; 
function code_toggle() {
 if (code_show){
 $('div.input').hide();
 } else {
 $('div.input').show();
 }
 code_show = !code_show
} 
$( document ).ready(code_toggle);
</script>
The raw code for this IPython notebook is by default hidden for easier reading.
To toggle on/off the raw code, click <a href="javascript:code_toggle()">here</a>.''')


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