In [531]:
import glob
import pandas as pd
import re
import locale
from time import strptime
%matplotlib inline
import matplotlib.pyplot as plt
from patsy import dmatrices

In [532]:
# Create container pickle
pickle_list = glob.glob('*.pickle')
pickle_list[:3]


Out[532]:
['the-numbers/1970.pickle',
 'the-numbers/1971.pickle',
 'the-numbers/1972.pickle']

In [533]:
# assimilate pickles into dataframe, remove first column, convert unicode to string
the_list = []
for pickle in pickle_list:
    dataframe_temp = pd.read_pickle(pickle)
    the_list.append(dataframe_temp)

df_numbers = pd.concat(the_list)
df_numbers = df_numbers.drop(df_numbers.columns[[0]], axis=1)
df_numbers.columns = ['date', 'year', 'title', 'budget', 'bo', 'bo_infl', 'bo_int', 'bo_world']

def unicode_to_string(df):
    """
    Will not work if columns contain any numeric formats
    Be sure to run all if using ipython or jupyter notebooks because the function will return an error if the result is already stored in memory
    """
    df_cols = list(df.columns.values)
    for col in df_cols:
        df[col] = [unicode(x).encode("utf-8") for x in df[col]]
    return df
df_numbers = unicode_to_string(df_numbers)
print df_numbers.shape
df_numbers.head(3)


(1218, 8)
Out[533]:
date year title budget bo bo_infl bo_int bo_world
0 Dec 31, 1970 1970 The Ballad of Tam Lin $0 $0 $0 $0 $0
0 Dec 31, 1971 1971 Sie tötete in Ekstase $0 $0 $0 $0 $0
0 Dec 31, 1972 1972 Whoever Slew Auntie Roo? $0 $0 $0 $0 $0

In [534]:
# some columns are misaligned: title and following columns begin at year (meaning no year for these cols)

# filter out misaligned entries
misalign_filter =  df_numbers['year'].str.isnumeric()
df_numbers = df_numbers[misalign_filter]

In [535]:
# drop columns
df_numbers = df_numbers.drop(df_numbers.columns[[5, 7]], axis=1)

print df_numbers.shape
df_numbers.head(3)


(1016, 6)
Out[535]:
date year title budget bo bo_int
0 Dec 31, 1970 1970 The Ballad of Tam Lin $0 $0 $0
0 Dec 31, 1971 1971 Sie tötete in Ekstase $0 $0 $0
0 Dec 31, 1972 1972 Whoever Slew Auntie Roo? $0 $0 $0

In [536]:
def replace_char(df, col, old, new):
    """
    df is dataframe, old is old char(s), new is new char(s)
    entries must all be strings
    """
    df[col] = [x.replace(old, new) for x in df[col]]
    return df

# Replace $ signs
df_numbers = replace_char(df_numbers, 'budget', '$', '')
df_numbers = replace_char(df_numbers, 'bo', '$', '')
df_numbers = replace_char(df_numbers, 'bo_int', '$', '')

print df_numbers.shape
df_numbers.head(3)


(1016, 6)
Out[536]:
date year title budget bo bo_int
0 Dec 31, 1970 1970 The Ballad of Tam Lin 0 0 0
0 Dec 31, 1971 1971 Sie tötete in Ekstase 0 0 0
0 Dec 31, 1972 1972 Whoever Slew Auntie Roo? 0 0 0

In [537]:
# convert strings to values and for dollar amounts convert comma delimited strings to numbers
locale.setlocale( locale.LC_ALL, 'en_US.UTF-8' ) 

df_numbers['year'] = [int(x) for x in df_numbers['year']]
df_numbers['budget'] = [locale.atoi(x) for x in df_numbers['budget']]
df_numbers['bo'] = [locale.atoi(x) for x in df_numbers['bo']]
df_numbers['bo_int'] = [locale.atoi(x) for x in df_numbers['bo_int']]

df_numbers['budget'] = [float(x) for x in df_numbers['budget']]
df_numbers['bo'] = [float(x) for x in df_numbers['bo']]
df_numbers['bo_int'] = [float(x) for x in df_numbers['bo_int']]

# lowercase titles
df_numbers['title'] = map(str.lower, df_numbers['title'])

# calculate total box
df_numbers['total_bo'] = df_numbers['bo'] + df_numbers['bo_int']

# get month
df_numbers['month'] = df_numbers['date'].str[:3]
df_numbers['month'] = [strptime(x, '%b').tm_mon for x in df_numbers['month']]

print df_numbers.shape
df_numbers.head(3)


(1016, 8)
Out[537]:
date year title budget bo bo_int total_bo month
0 Dec 31, 1970 1970 the ballad of tam lin 0.0 0.0 0.0 0.0 12
0 Dec 31, 1971 1971 sie tötete in ekstase 0.0 0.0 0.0 0.0 12
0 Dec 31, 1972 1972 whoever slew auntie roo? 0.0 0.0 0.0 0.0 12

In [549]:
# filter out box office revenues and budgets of zero

def remove_less_than(df, df_col, criterion):
    the_filter = df[df_col] > criterion
    df = df[the_filter]
    return df

df_numbers = remove_less_than(df_numbers, 'budget', 0)
df_numbers = remove_less_than(df_numbers, 'total_bo', 0)

print df_numbers.shape
df_numbers.head(3)


---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-549-31ca2e3d0e52> in <module>()
      6     return df
      7 
----> 8 df_numbers = remove_less_than(df_numbers, 'budget', 0)
      9 df_numbers = remove_less_than(df_numbers, 'total_bo', 0)
     10 df_numbers.shape

<ipython-input-549-31ca2e3d0e52> in remove_less_than(df, df_col, criterion)
      2 
      3 def remove_less_than(df, df_col, criterion):
----> 4     the_filter = df[df_col] > criterion
      5     df = df[the_filter]
      6     return df

/Users/peter/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc in __getitem__(self, key)
   1990             return self._getitem_multilevel(key)
   1991         else:
-> 1992             return self._getitem_column(key)
   1993 
   1994     def _getitem_column(self, key):

/Users/peter/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc in _getitem_column(self, key)
   1997         # get column
   1998         if self.columns.is_unique:
-> 1999             return self._get_item_cache(key)
   2000 
   2001         # duplicate columns & possible reduce dimensionality

/Users/peter/anaconda/lib/python2.7/site-packages/pandas/core/generic.pyc in _get_item_cache(self, item)
   1343         res = cache.get(item)
   1344         if res is None:
-> 1345             values = self._data.get(item)
   1346             res = self._box_item_values(item, values)
   1347             cache[item] = res

/Users/peter/anaconda/lib/python2.7/site-packages/pandas/core/internals.pyc in get(self, item, fastpath)
   3223 
   3224             if not isnull(item):
-> 3225                 loc = self.items.get_loc(item)
   3226             else:
   3227                 indexer = np.arange(len(self.items))[isnull(self.items)]

/Users/peter/anaconda/lib/python2.7/site-packages/pandas/indexes/base.pyc in get_loc(self, key, method, tolerance)
   1876                 return self._engine.get_loc(key)
   1877             except KeyError:
-> 1878                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   1879 
   1880         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4027)()

pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:3891)()

pandas/hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12408)()

pandas/hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12359)()

KeyError: 'budget'

In [539]:
# replace spaces with hyphens
df_numbers['title'] = df_numbers['title'].str.replace(' ', '-')

print df_numbers.shape
df_numbers.head(3)


Out[539]:
date year title budget bo bo_int total_bo month
0 Dec 26, 1973 1973 the-exorcist 12000000.0 204868002.0 197867132.0 402735134.0 12
0 Oct 18, 1974 1974 the-texas-chainsaw-massacre 140000.0 26572439.0 0.0 26572439.0 10
0 Jun 20, 1975 1975 jaws 12000000.0 260000000.0 210700000.0 470700000.0 6

In [540]:
# the-numbers inflation ratio doesn't make sense so just import cpi data from us gov http://www.bls.gov/cpi/
# assume box office revenues earned within each release year and that inflation in each year equals the cpi data that I imported

# read cpi csv
df_cpi =pd.read_csv('cpi.csv')
df_cpi['year'] = [int(float(x)) for x in df_cpi['year']] # cast to int

# merge cpi into numbers dataframe
df_numbers = pd.merge(df_numbers, df_cpi, on='year')

print df_numbers.shape
df_numbers.head(3)


Out[540]:
date year title budget bo bo_int total_bo month cpi cpi_ratio
0 Dec 26, 1973 1973 the-exorcist 12000000.0 204868002.0 197867132.0 402735134.0 12 44.425 0.187451
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 140000.0 26572439.0 0.0 26572439.0 10 49.317 0.208093
2 Jun 20, 1975 1975 jaws 12000000.0 260000000.0 210700000.0 470700000.0 6 53.825 0.227114

In [541]:
# adjust for inflation

df_numbers['budget_i'] = df_numbers['budget']/df_numbers['cpi_ratio']
df_numbers['bo_i'] = df_numbers['bo']/df_numbers['cpi_ratio']
df_numbers['bo_int_i'] = df_numbers['bo_int']/df_numbers['cpi_ratio']
df_numbers['total_bo_i'] = df_numbers['total_bo']/df_numbers['cpi_ratio']

print df_numbers.shape
df_numbers.head(3)


Out[541]:
date year title budget bo bo_int total_bo month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i
0 Dec 26, 1973 1973 the-exorcist 12000000.0 204868002.0 197867132.0 402735134.0 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 140000.0 26572439.0 0.0 26572439.0 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08
2 Jun 20, 1975 1975 jaws 12000000.0 260000000.0 210700000.0 470700000.0 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09

In [542]:
# drop columns
df_numbers = df_numbers.drop(df_numbers.columns[[3, 4, 5, 6]], axis=1)

print df_numbers.shape
df_numbers.head(3)


Out[542]:
date year title month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i
0 Dec 26, 1973 1973 the-exorcist 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08
2 Jun 20, 1975 1975 jaws 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09

In [543]:
# calculate profit, profit margin, and % box office that's international
df_numbers['profit_i'] = df_numbers['total_bo_i']-df_numbers['budget_i']
df_numbers['margin'] = df_numbers['profit_i']/df_numbers['budget_i']
df_numbers['percent_int'] = df_numbers['bo_int_i']/df_numbers['total_bo_i']

print df_numbers.shape
df_numbers.head(3)


(275, 13)
Out[543]:
date year title month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i profit_i margin percent_int
0 Dec 26, 1973 1973 the-exorcist 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09 2.084463e+09 32.561261 0.491308
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08 1.270222e+08 188.803136 0.000000
2 Jun 20, 1975 1975 jaws 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09 2.019686e+09 38.225000 0.447631

In [544]:
# read in metacritic data
df_metacritic = pd.read_pickle('metacritic/consolidated.pickle')
df_metacritic.head(3)


Out[544]:
index title metascore userscore
0 0 all-mistakes-buried 56 tbd
1 1 drunk-stoned-brilliant-dead-the-story-of-the-n... 74 tbd
2 2 fifty-shades-of-black 28 1.6

In [545]:
# drop index column
# drop columns
df_metacritic = df_metacritic.drop(df_metacritic.columns[[0]], axis=1)
print df_metacritic.shape
df_metacritic.head(3)


(7831, 3)
Out[545]:
title metascore userscore
0 all-mistakes-buried 56 tbd
1 drunk-stoned-brilliant-dead-the-story-of-the-n... 74 tbd
2 fifty-shades-of-black 28 1.6

In [546]:
# merge metacritic data with numbers data
df = pd.merge(df_numbers, df_metacritic, on='title')
df


Out[546]:
date year title month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i profit_i margin percent_int metascore userscore
0 Dec 26, 1973 1973 the-exorcist 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09 2.084463e+09 32.561261 0.491308 82 8.8
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08 1.270222e+08 188.803136 0.000000 38 6.6
2 Oct 17, 2003 2003 the-texas-chainsaw-massacre 10 184.000 0.776388 1.159215e+07 1.035437e+08 3.528606e+07 1.388297e+08 1.272376e+08 10.976187 0.254168 38 6.6
3 Jun 20, 1975 1975 jaws 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09 2.019686e+09 38.225000 0.447631 79 8.7
4 Nov 16, 1976 1976 carrie 11 56.933 0.240229 7.492860e+06 1.077230e+08 0.000000e+00 1.077230e+08 1.002301e+08 13.376752 0.000000 53 6.1
5 Oct 18, 2013 2013 carrie 10 232.964 0.982991 3.051909e+07 3.587684e+07 4.795862e+07 8.383546e+07 5.331637e+07 1.746984 0.572056 53 6.1
6 Jun 25, 1976 1976 the-omen 6 56.933 0.240229 1.165556e+07 2.021860e+08 0.000000e+00 2.021860e+08 1.905305e+08 16.346745 0.000000 43 6.4
7 Jun 6, 2006 2006 the-omen 6 201.558 0.850474 2.939538e+07 6.420820e+07 7.606138e+07 1.402696e+08 1.108742e+08 3.771823 0.542251 43 6.4
8 Oct 17, 1978 1978 halloween 10 65.242 0.275289 1.180580e+06 1.707300e+08 8.354871e+07 2.542787e+08 2.530981e+08 214.384615 0.328571 47 5.7
9 Aug 31, 2007 2007 halloween 8 207.344 0.874888 1.714506e+07 6.660187e+07 2.199740e+07 8.859926e+07 7.145420e+07 4.167627 0.248280 47 5.7
10 Apr 20, 1979 1979 dawn-of-the-dead 4 72.583 0.306264 4.897738e+06 1.665231e+07 1.629314e+08 1.795837e+08 1.746860e+08 35.666667 0.907273 59 8.6
11 Mar 19, 2004 2004 dawn-of-the-dead 3 188.908 0.797097 3.512747e+07 7.400701e+07 5.578005e+07 1.297871e+08 9.465959e+07 2.694746 0.429781 59 8.6
12 May 23, 1980 1980 the-shining 5 82.383 0.347615 5.465818e+07 1.266268e+08 1.142054e+06 1.277689e+08 7.311069e+07 1.337598 0.008938 61 8.8
13 May 9, 1980 1980 friday-the-13th 5 82.383 0.347615 1.582211e+06 1.143639e+08 5.753493e+07 1.718988e+08 1.703166e+08 107.644729 0.334702 34 6.3
14 Feb 13, 2009 2009 friday-the-13th 2 214.565 0.905357 1.877713e+07 7.179714e+07 3.056057e+07 1.023577e+08 8.358058e+07 4.451190 0.298566 34 6.3
15 Feb 1, 1980 1980 the-fog 2 82.383 0.347615 2.876746e+06 6.150012e+07 0.000000e+00 6.150012e+07 5.862338e+07 20.378361 0.000000 27 2.0
16 Oct 14, 2005 2005 the-fog 10 195.267 0.823929 2.184655e+07 3.581755e+07 9.148138e+06 4.496569e+07 2.311914e+07 1.058251 0.203447 27 2.0
17 Oct 30, 1981 1981 halloween-ii 10 90.933 0.383692 6.515649e+06 6.654776e+07 0.000000e+00 6.654776e+07 6.003211e+07 9.213527 0.000000 40 6.6
18 Jun 4, 1982 1982 poltergeist 6 96.533 0.407321 2.626922e+07 1.834083e+08 1.153882e+08 2.987965e+08 2.725272e+08 10.374394 0.386176 47 3.6
19 May 22, 2015 2015 poltergeist 5 236.995 1.000000 3.500000e+07 4.742512e+07 4.840000e+07 9.582512e+07 6.082512e+07 1.737861 0.505087 47 3.6
20 Oct 21, 1983 1983 the-dead-zone 10 99.583 0.420190 2.379874e+07 4.590286e+07 0.000000e+00 4.590286e+07 2.210412e+07 0.928794 0.000000 69 8.8
21 Feb 4, 1983 1983 videodrome 2 99.583 0.420190 1.416501e+07 5.046378e+06 0.000000e+00 5.046378e+06 -9.118633e+06 -0.643743 0.000000 60 3.8
22 Jul 31, 1987 1987 the-lost-boys 7 113.617 0.479407 1.773025e+07 6.326921e+07 0.000000e+00 6.326921e+07 4.553896e+07 2.568434 0.000000 63 8.9
23 Mar 13, 1987 1987 evil-dead-ii 3 113.617 0.479407 7.300690e+06 1.235495e+07 0.000000e+00 1.235495e+07 5.054255e+06 0.692298 0.000000 69 8.6
24 Jul 31, 1992 1992 buffy-the-vampire-slayer 7 140.308 0.592029 1.182374e+07 2.307683e+07 0.000000e+00 2.307683e+07 1.125310e+07 0.951738 0.000000 48 8.0
25 Feb 19, 1993 1993 army-of-darkness 2 144.475 0.609612 1.804426e+07 1.886934e+07 1.640388e+07 3.527322e+07 1.722895e+07 0.954816 0.465052 57 8.5
26 Oct 27, 1995 1995 vampire-in-brooklyn 10 152.383 0.642980 2.177362e+07 3.041538e+07 0.000000e+00 3.041538e+07 8.641757e+06 0.396891 0.000000 27 8.5
27 Dec 12, 1997 1997 scream-2 12 160.525 0.677335 3.543299e+07 1.496075e+08 0.000000e+00 1.496075e+08 1.141745e+08 3.222266 0.000000 63 8.9
28 Oct 17, 1997 1997 i-know-what-you-did-last-summer 10 160.525 0.677335 2.509836e+07 1.066229e+08 7.824784e+07 1.848707e+08 1.597723e+08 6.365847 0.423257 52 2.2
29 Aug 15, 1997 1997 event-horizon 8 160.525 0.677335 8.858246e+07 3.937209e+07 0.000000e+00 3.937209e+07 -4.921038e+07 -0.555532 0.000000 35 6.9
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
134 Mar 9, 2012 2012 silent-house 3 229.596 0.968780 2.064452e+06 1.315029e+07 3.995771e+06 1.714606e+07 1.508161e+07 7.305380 0.233043 49 8.1
135 Feb 3, 2012 2012 the-innkeepers 2 229.596 0.968780 7.741696e+05 8.092240e+04 9.632105e+05 1.044133e+06 2.699633e+05 0.348713 0.922498 64 6.2
136 Feb 3, 2012 2012 kill-list 2 229.596 0.968780 8.257809e+05 2.999959e+04 4.471015e+05 4.771011e+05 -3.486798e+05 -0.422243 0.937121 67 6.5
137 Nov 30, 2012 2012 the-collection 11 229.596 0.968780 1.032226e+07 7.030239e+06 2.146349e+06 9.176588e+06 -1.145674e+06 -0.110991 0.233894 36 6.8
138 Oct 19, 2012 2012 paranormal-activity-4 10 229.596 0.968780 5.161131e+06 5.563734e+07 8.951381e+07 1.451511e+08 1.399900e+08 27.123904 0.616694 40 4.6
139 Sep 21, 2012 2012 house-at-the-end-of-the-street 9 229.596 0.968780 7.122361e+06 3.263065e+07 1.289464e+07 4.552528e+07 3.840292e+07 5.391881 0.283241 31 5.3
140 Aug 24, 2012 2012 the-apparition 8 229.596 0.968780 1.754784e+07 5.095914e+06 5.884166e+06 1.098008e+07 -6.567765e+06 -0.374278 0.535895 18 3.8
141 Aug 17, 2012 2012 the-awakening 8 229.596 0.968780 5.057908e+06 9.902455e+04 7.048441e+06 7.147465e+06 2.089557e+06 0.413127 0.986146 53 6.7
142 Apr 19, 2013 2013 the-lords-of-salem 4 232.964 0.982991 1.525955e+06 1.186054e+06 3.817430e+05 1.567797e+06 4.184269e+04 0.027421 0.243490 57 5.8
143 Apr 5, 2013 2013 evil-dead 4 232.964 0.982991 1.729415e+07 5.517837e+07 4.429185e+07 9.947022e+07 8.217607e+07 4.751668 0.445277 57 7.4
144 Mar 1, 2013 2013 the-last-exorcism-part-ii 3 232.964 0.982991 4.069212e+06 1.544195e+07 1.044710e+07 2.588905e+07 2.181984e+07 5.362177 0.403533 35 3.3
145 Jan 18, 2013 2013 mama 1 232.964 0.982991 1.525955e+07 7.286757e+07 7.779051e+07 1.506581e+08 1.353985e+08 8.873038 0.516338 57 6.4
146 Jan 4, 2013 2013 texas-chainsaw-3d 1 232.964 0.982991 2.034606e+07 3.493617e+07 1.355462e+07 4.849078e+07 2.814472e+07 1.383301 0.279530 31 4.5
147 Oct 11, 2013 2013 all-the-boys-love-mandy-lane 10 232.964 0.982991 7.629773e+05 0.000000e+00 1.994444e+06 1.994444e+06 1.231467e+06 1.614028 1.000000 44 6.4
148 Sep 13, 2013 2013 insidious-chapter-2 9 232.964 0.982991 5.086516e+06 8.503275e+07 7.969051e+07 1.647233e+08 1.596367e+08 31.384303 0.483784 40 6.7
149 Jul 23, 2013 2013 twixt 7 232.964 0.982991 7.121122e+06 0.000000e+00 1.228397e+06 1.228397e+06 -5.892725e+06 -0.827500 1.000000 40 5.2
150 Jul 19, 2013 2013 the-conjuring 7 232.964 0.982991 2.034606e+07 1.397776e+08 1.837249e+08 3.235025e+08 3.031565e+08 14.900007 0.567924 68 8.2
151 Apr 11, 2014 2014 oculus 4 236.715 0.998819 5.005914e+06 2.772801e+07 1.643967e+07 4.416768e+07 3.916176e+07 7.823099 0.372210 61 3.4
152 Oct 24, 2014 2014 ouija 10 236.715 0.998819 5.005914e+06 5.091617e+07 5.279664e+07 1.037128e+08 9.870689e+07 19.718054 0.509066 38 8.0
153 Oct 3, 2014 2014 annabelle 10 236.715 0.998819 6.507689e+06 8.437350e+07 1.665968e+08 2.509703e+08 2.444626e+08 37.565202 0.663811 37 5.2
154 Sep 19, 2014 2014 tusk 9 236.715 0.998819 3.003549e+06 1.824138e+06 0.000000e+00 1.824138e+06 -1.179410e+06 -0.392672 0.000000 55 6.0
155 Jul 2, 2014 2014 deliver-us-from-evil 7 236.715 0.998819 3.003549e+07 3.061329e+07 5.744737e+07 8.806066e+07 5.802517e+07 1.931887 0.652361 86 8.0
156 Jun 5, 2015 2015 insidious-chapter-3 6 236.995 1.000000 1.000000e+07 5.221856e+07 6.845989e+07 1.206784e+08 1.106784e+08 11.067844 0.567292 52 6.8
157 Apr 17, 2015 2015 unfriended 4 236.995 1.000000 1.000000e+06 3.248209e+07 3.007936e+07 6.256145e+07 6.156145e+07 61.561449 0.480797 59 5.6
158 Mar 13, 2015 2015 it-follows 3 236.995 1.000000 2.000000e+06 1.467408e+07 5.975697e+06 2.064977e+07 1.864977e+07 9.324887 0.289383 83 7.8
159 Feb 27, 2015 2015 the-lazarus-effect 2 236.995 1.000000 5.000000e+06 2.580157e+07 2.300000e+06 2.810157e+07 2.310157e+07 4.620314 0.081846 31 4.8
160 Oct 16, 2015 2015 goosebumps 10 236.995 1.000000 5.800000e+07 8.006946e+07 7.683984e+07 1.569093e+08 9.890930e+07 1.705333 0.489709 60 6.7
161 Sep 25, 2015 2015 the-green-inferno 9 236.995 1.000000 1.000000e+06 7.192291e+06 1.609576e+06 8.801867e+06 7.801867e+06 7.801867 0.182868 38 4.7
162 Aug 21, 2015 2015 sinister-2 8 236.995 1.000000 1.000000e+07 2.774096e+07 2.494919e+07 5.269015e+07 4.269015e+07 4.269015 0.473508 32 5.9
163 Jul 24, 2015 2015 the-vatican-tapes 7 236.995 1.000000 1.300000e+07 1.784763e+06 1.120143e+07 1.298619e+07 -1.381100e+04 -0.001062 0.862565 37 4.2

164 rows × 15 columns


In [547]:
# filter out movies that were not reviewed and any NaNs
# assume opinions held about movies now are same as they were when movies were released
def filter_out_not_equal(df, df_col, criterion):
    the_filter = df[df_col] != criterion
    df = df[the_filter]
    return df

df = filter_out_not_equal(df, 'userscore','tbd')
df.dropna(thresh=1)

df


Out[547]:
date year title month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i profit_i margin percent_int metascore userscore
0 Dec 26, 1973 1973 the-exorcist 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09 2.084463e+09 32.561261 0.491308 82 8.8
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08 1.270222e+08 188.803136 0.000000 38 6.6
2 Oct 17, 2003 2003 the-texas-chainsaw-massacre 10 184.000 0.776388 1.159215e+07 1.035437e+08 3.528606e+07 1.388297e+08 1.272376e+08 10.976187 0.254168 38 6.6
3 Jun 20, 1975 1975 jaws 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09 2.019686e+09 38.225000 0.447631 79 8.7
4 Nov 16, 1976 1976 carrie 11 56.933 0.240229 7.492860e+06 1.077230e+08 0.000000e+00 1.077230e+08 1.002301e+08 13.376752 0.000000 53 6.1
5 Oct 18, 2013 2013 carrie 10 232.964 0.982991 3.051909e+07 3.587684e+07 4.795862e+07 8.383546e+07 5.331637e+07 1.746984 0.572056 53 6.1
6 Jun 25, 1976 1976 the-omen 6 56.933 0.240229 1.165556e+07 2.021860e+08 0.000000e+00 2.021860e+08 1.905305e+08 16.346745 0.000000 43 6.4
7 Jun 6, 2006 2006 the-omen 6 201.558 0.850474 2.939538e+07 6.420820e+07 7.606138e+07 1.402696e+08 1.108742e+08 3.771823 0.542251 43 6.4
8 Oct 17, 1978 1978 halloween 10 65.242 0.275289 1.180580e+06 1.707300e+08 8.354871e+07 2.542787e+08 2.530981e+08 214.384615 0.328571 47 5.7
9 Aug 31, 2007 2007 halloween 8 207.344 0.874888 1.714506e+07 6.660187e+07 2.199740e+07 8.859926e+07 7.145420e+07 4.167627 0.248280 47 5.7
10 Apr 20, 1979 1979 dawn-of-the-dead 4 72.583 0.306264 4.897738e+06 1.665231e+07 1.629314e+08 1.795837e+08 1.746860e+08 35.666667 0.907273 59 8.6
11 Mar 19, 2004 2004 dawn-of-the-dead 3 188.908 0.797097 3.512747e+07 7.400701e+07 5.578005e+07 1.297871e+08 9.465959e+07 2.694746 0.429781 59 8.6
12 May 23, 1980 1980 the-shining 5 82.383 0.347615 5.465818e+07 1.266268e+08 1.142054e+06 1.277689e+08 7.311069e+07 1.337598 0.008938 61 8.8
13 May 9, 1980 1980 friday-the-13th 5 82.383 0.347615 1.582211e+06 1.143639e+08 5.753493e+07 1.718988e+08 1.703166e+08 107.644729 0.334702 34 6.3
14 Feb 13, 2009 2009 friday-the-13th 2 214.565 0.905357 1.877713e+07 7.179714e+07 3.056057e+07 1.023577e+08 8.358058e+07 4.451190 0.298566 34 6.3
15 Feb 1, 1980 1980 the-fog 2 82.383 0.347615 2.876746e+06 6.150012e+07 0.000000e+00 6.150012e+07 5.862338e+07 20.378361 0.000000 27 2.0
16 Oct 14, 2005 2005 the-fog 10 195.267 0.823929 2.184655e+07 3.581755e+07 9.148138e+06 4.496569e+07 2.311914e+07 1.058251 0.203447 27 2.0
17 Oct 30, 1981 1981 halloween-ii 10 90.933 0.383692 6.515649e+06 6.654776e+07 0.000000e+00 6.654776e+07 6.003211e+07 9.213527 0.000000 40 6.6
18 Jun 4, 1982 1982 poltergeist 6 96.533 0.407321 2.626922e+07 1.834083e+08 1.153882e+08 2.987965e+08 2.725272e+08 10.374394 0.386176 47 3.6
19 May 22, 2015 2015 poltergeist 5 236.995 1.000000 3.500000e+07 4.742512e+07 4.840000e+07 9.582512e+07 6.082512e+07 1.737861 0.505087 47 3.6
20 Oct 21, 1983 1983 the-dead-zone 10 99.583 0.420190 2.379874e+07 4.590286e+07 0.000000e+00 4.590286e+07 2.210412e+07 0.928794 0.000000 69 8.8
21 Feb 4, 1983 1983 videodrome 2 99.583 0.420190 1.416501e+07 5.046378e+06 0.000000e+00 5.046378e+06 -9.118633e+06 -0.643743 0.000000 60 3.8
22 Jul 31, 1987 1987 the-lost-boys 7 113.617 0.479407 1.773025e+07 6.326921e+07 0.000000e+00 6.326921e+07 4.553896e+07 2.568434 0.000000 63 8.9
23 Mar 13, 1987 1987 evil-dead-ii 3 113.617 0.479407 7.300690e+06 1.235495e+07 0.000000e+00 1.235495e+07 5.054255e+06 0.692298 0.000000 69 8.6
24 Jul 31, 1992 1992 buffy-the-vampire-slayer 7 140.308 0.592029 1.182374e+07 2.307683e+07 0.000000e+00 2.307683e+07 1.125310e+07 0.951738 0.000000 48 8.0
25 Feb 19, 1993 1993 army-of-darkness 2 144.475 0.609612 1.804426e+07 1.886934e+07 1.640388e+07 3.527322e+07 1.722895e+07 0.954816 0.465052 57 8.5
26 Oct 27, 1995 1995 vampire-in-brooklyn 10 152.383 0.642980 2.177362e+07 3.041538e+07 0.000000e+00 3.041538e+07 8.641757e+06 0.396891 0.000000 27 8.5
27 Dec 12, 1997 1997 scream-2 12 160.525 0.677335 3.543299e+07 1.496075e+08 0.000000e+00 1.496075e+08 1.141745e+08 3.222266 0.000000 63 8.9
28 Oct 17, 1997 1997 i-know-what-you-did-last-summer 10 160.525 0.677335 2.509836e+07 1.066229e+08 7.824784e+07 1.848707e+08 1.597723e+08 6.365847 0.423257 52 2.2
29 Aug 15, 1997 1997 event-horizon 8 160.525 0.677335 8.858246e+07 3.937209e+07 0.000000e+00 3.937209e+07 -4.921038e+07 -0.555532 0.000000 35 6.9
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
134 Mar 9, 2012 2012 silent-house 3 229.596 0.968780 2.064452e+06 1.315029e+07 3.995771e+06 1.714606e+07 1.508161e+07 7.305380 0.233043 49 8.1
135 Feb 3, 2012 2012 the-innkeepers 2 229.596 0.968780 7.741696e+05 8.092240e+04 9.632105e+05 1.044133e+06 2.699633e+05 0.348713 0.922498 64 6.2
136 Feb 3, 2012 2012 kill-list 2 229.596 0.968780 8.257809e+05 2.999959e+04 4.471015e+05 4.771011e+05 -3.486798e+05 -0.422243 0.937121 67 6.5
137 Nov 30, 2012 2012 the-collection 11 229.596 0.968780 1.032226e+07 7.030239e+06 2.146349e+06 9.176588e+06 -1.145674e+06 -0.110991 0.233894 36 6.8
138 Oct 19, 2012 2012 paranormal-activity-4 10 229.596 0.968780 5.161131e+06 5.563734e+07 8.951381e+07 1.451511e+08 1.399900e+08 27.123904 0.616694 40 4.6
139 Sep 21, 2012 2012 house-at-the-end-of-the-street 9 229.596 0.968780 7.122361e+06 3.263065e+07 1.289464e+07 4.552528e+07 3.840292e+07 5.391881 0.283241 31 5.3
140 Aug 24, 2012 2012 the-apparition 8 229.596 0.968780 1.754784e+07 5.095914e+06 5.884166e+06 1.098008e+07 -6.567765e+06 -0.374278 0.535895 18 3.8
141 Aug 17, 2012 2012 the-awakening 8 229.596 0.968780 5.057908e+06 9.902455e+04 7.048441e+06 7.147465e+06 2.089557e+06 0.413127 0.986146 53 6.7
142 Apr 19, 2013 2013 the-lords-of-salem 4 232.964 0.982991 1.525955e+06 1.186054e+06 3.817430e+05 1.567797e+06 4.184269e+04 0.027421 0.243490 57 5.8
143 Apr 5, 2013 2013 evil-dead 4 232.964 0.982991 1.729415e+07 5.517837e+07 4.429185e+07 9.947022e+07 8.217607e+07 4.751668 0.445277 57 7.4
144 Mar 1, 2013 2013 the-last-exorcism-part-ii 3 232.964 0.982991 4.069212e+06 1.544195e+07 1.044710e+07 2.588905e+07 2.181984e+07 5.362177 0.403533 35 3.3
145 Jan 18, 2013 2013 mama 1 232.964 0.982991 1.525955e+07 7.286757e+07 7.779051e+07 1.506581e+08 1.353985e+08 8.873038 0.516338 57 6.4
146 Jan 4, 2013 2013 texas-chainsaw-3d 1 232.964 0.982991 2.034606e+07 3.493617e+07 1.355462e+07 4.849078e+07 2.814472e+07 1.383301 0.279530 31 4.5
147 Oct 11, 2013 2013 all-the-boys-love-mandy-lane 10 232.964 0.982991 7.629773e+05 0.000000e+00 1.994444e+06 1.994444e+06 1.231467e+06 1.614028 1.000000 44 6.4
148 Sep 13, 2013 2013 insidious-chapter-2 9 232.964 0.982991 5.086516e+06 8.503275e+07 7.969051e+07 1.647233e+08 1.596367e+08 31.384303 0.483784 40 6.7
149 Jul 23, 2013 2013 twixt 7 232.964 0.982991 7.121122e+06 0.000000e+00 1.228397e+06 1.228397e+06 -5.892725e+06 -0.827500 1.000000 40 5.2
150 Jul 19, 2013 2013 the-conjuring 7 232.964 0.982991 2.034606e+07 1.397776e+08 1.837249e+08 3.235025e+08 3.031565e+08 14.900007 0.567924 68 8.2
151 Apr 11, 2014 2014 oculus 4 236.715 0.998819 5.005914e+06 2.772801e+07 1.643967e+07 4.416768e+07 3.916176e+07 7.823099 0.372210 61 3.4
152 Oct 24, 2014 2014 ouija 10 236.715 0.998819 5.005914e+06 5.091617e+07 5.279664e+07 1.037128e+08 9.870689e+07 19.718054 0.509066 38 8.0
153 Oct 3, 2014 2014 annabelle 10 236.715 0.998819 6.507689e+06 8.437350e+07 1.665968e+08 2.509703e+08 2.444626e+08 37.565202 0.663811 37 5.2
154 Sep 19, 2014 2014 tusk 9 236.715 0.998819 3.003549e+06 1.824138e+06 0.000000e+00 1.824138e+06 -1.179410e+06 -0.392672 0.000000 55 6.0
155 Jul 2, 2014 2014 deliver-us-from-evil 7 236.715 0.998819 3.003549e+07 3.061329e+07 5.744737e+07 8.806066e+07 5.802517e+07 1.931887 0.652361 86 8.0
156 Jun 5, 2015 2015 insidious-chapter-3 6 236.995 1.000000 1.000000e+07 5.221856e+07 6.845989e+07 1.206784e+08 1.106784e+08 11.067844 0.567292 52 6.8
157 Apr 17, 2015 2015 unfriended 4 236.995 1.000000 1.000000e+06 3.248209e+07 3.007936e+07 6.256145e+07 6.156145e+07 61.561449 0.480797 59 5.6
158 Mar 13, 2015 2015 it-follows 3 236.995 1.000000 2.000000e+06 1.467408e+07 5.975697e+06 2.064977e+07 1.864977e+07 9.324887 0.289383 83 7.8
159 Feb 27, 2015 2015 the-lazarus-effect 2 236.995 1.000000 5.000000e+06 2.580157e+07 2.300000e+06 2.810157e+07 2.310157e+07 4.620314 0.081846 31 4.8
160 Oct 16, 2015 2015 goosebumps 10 236.995 1.000000 5.800000e+07 8.006946e+07 7.683984e+07 1.569093e+08 9.890930e+07 1.705333 0.489709 60 6.7
161 Sep 25, 2015 2015 the-green-inferno 9 236.995 1.000000 1.000000e+06 7.192291e+06 1.609576e+06 8.801867e+06 7.801867e+06 7.801867 0.182868 38 4.7
162 Aug 21, 2015 2015 sinister-2 8 236.995 1.000000 1.000000e+07 2.774096e+07 2.494919e+07 5.269015e+07 4.269015e+07 4.269015 0.473508 32 5.9
163 Jul 24, 2015 2015 the-vatican-tapes 7 236.995 1.000000 1.300000e+07 1.784763e+06 1.120143e+07 1.298619e+07 -1.381100e+04 -0.001062 0.862565 37 4.2

164 rows × 15 columns


In [548]:
# fix scores for texas chainsaw massacre 1974
df.iloc[1,-2] = 78
df.iloc[1,-1] = 7.9

# use rotten tomatoes rank for carrie
# http://www.rottentomatoes.com/m/1003625-carrie/
df.iloc[4,-2] = 93
df.iloc[4,-1] = 7.6

# use rotten tomatoes rank for the omen
# http://www.rottentomatoes.com/m/1015517-omen/
df.iloc[6,-2] = 86
df.iloc[6,-1] = 8.0

# use rotten tomatoes rank for dawn of the dead
# http://www.rottentomatoes.com/m/1005339-dawn_of_the_dead/
df.iloc[10,-2] = 92
df.iloc[10,-1] = 9.0

# use rotten tomatoes rank for friday-the-13th
# http://www.rottentomatoes.com/m/friday_the_13th_part_1/
df.iloc[13,-2] = 58
df.iloc[13,-1] = 6.1

# use rotten tomatoes rank for the fog user score
# http://www.rottentomatoes.com/m/1007617-fog/
df.iloc[15,-2] = 74
df.iloc[15,-1] = 5.8

# use rotten tomatoes rank for poltergeist
# http://www.rottentomatoes.com/m/1016513-poltergeist/
df.iloc[18,-2] = 88
df.iloc[18,-1] = 7.8




df


Out[548]:
date year title month cpi cpi_ratio budget_i bo_i bo_int_i total_bo_i profit_i margin percent_int metascore userscore
0 Dec 26, 1973 1973 the-exorcist 12 44.425 0.187451 6.401666e+07 1.092914e+09 1.055566e+09 2.148480e+09 2.084463e+09 32.561261 0.491308 82 8.8
1 Oct 18, 1974 1974 the-texas-chainsaw-massacre 10 49.317 0.208093 6.727761e+05 1.276950e+08 0.000000e+00 1.276950e+08 1.270222e+08 188.803136 0.000000 78 7.9
2 Oct 17, 2003 2003 the-texas-chainsaw-massacre 10 184.000 0.776388 1.159215e+07 1.035437e+08 3.528606e+07 1.388297e+08 1.272376e+08 10.976187 0.254168 38 6.6
3 Jun 20, 1975 1975 jaws 6 53.825 0.227114 5.283679e+07 1.144797e+09 9.277259e+08 2.072523e+09 2.019686e+09 38.225000 0.447631 79 8.7
4 Nov 16, 1976 1976 carrie 11 56.933 0.240229 7.492860e+06 1.077230e+08 0.000000e+00 1.077230e+08 1.002301e+08 13.376752 0.000000 93 7.6
5 Oct 18, 2013 2013 carrie 10 232.964 0.982991 3.051909e+07 3.587684e+07 4.795862e+07 8.383546e+07 5.331637e+07 1.746984 0.572056 53 6.1
6 Jun 25, 1976 1976 the-omen 6 56.933 0.240229 1.165556e+07 2.021860e+08 0.000000e+00 2.021860e+08 1.905305e+08 16.346745 0.000000 86 8
7 Jun 6, 2006 2006 the-omen 6 201.558 0.850474 2.939538e+07 6.420820e+07 7.606138e+07 1.402696e+08 1.108742e+08 3.771823 0.542251 43 6.4
8 Oct 17, 1978 1978 halloween 10 65.242 0.275289 1.180580e+06 1.707300e+08 8.354871e+07 2.542787e+08 2.530981e+08 214.384615 0.328571 47 5.7
9 Aug 31, 2007 2007 halloween 8 207.344 0.874888 1.714506e+07 6.660187e+07 2.199740e+07 8.859926e+07 7.145420e+07 4.167627 0.248280 47 5.7
10 Apr 20, 1979 1979 dawn-of-the-dead 4 72.583 0.306264 4.897738e+06 1.665231e+07 1.629314e+08 1.795837e+08 1.746860e+08 35.666667 0.907273 92 9
11 Mar 19, 2004 2004 dawn-of-the-dead 3 188.908 0.797097 3.512747e+07 7.400701e+07 5.578005e+07 1.297871e+08 9.465959e+07 2.694746 0.429781 59 8.6
12 May 23, 1980 1980 the-shining 5 82.383 0.347615 5.465818e+07 1.266268e+08 1.142054e+06 1.277689e+08 7.311069e+07 1.337598 0.008938 61 8.8
13 May 9, 1980 1980 friday-the-13th 5 82.383 0.347615 1.582211e+06 1.143639e+08 5.753493e+07 1.718988e+08 1.703166e+08 107.644729 0.334702 58 6.1
14 Feb 13, 2009 2009 friday-the-13th 2 214.565 0.905357 1.877713e+07 7.179714e+07 3.056057e+07 1.023577e+08 8.358058e+07 4.451190 0.298566 34 6.3
15 Feb 1, 1980 1980 the-fog 2 82.383 0.347615 2.876746e+06 6.150012e+07 0.000000e+00 6.150012e+07 5.862338e+07 20.378361 0.000000 74 5.8
16 Oct 14, 2005 2005 the-fog 10 195.267 0.823929 2.184655e+07 3.581755e+07 9.148138e+06 4.496569e+07 2.311914e+07 1.058251 0.203447 27 2.0
17 Oct 30, 1981 1981 halloween-ii 10 90.933 0.383692 6.515649e+06 6.654776e+07 0.000000e+00 6.654776e+07 6.003211e+07 9.213527 0.000000 40 6.6
18 Jun 4, 1982 1982 poltergeist 6 96.533 0.407321 2.626922e+07 1.834083e+08 1.153882e+08 2.987965e+08 2.725272e+08 10.374394 0.386176 88 7.8
19 May 22, 2015 2015 poltergeist 5 236.995 1.000000 3.500000e+07 4.742512e+07 4.840000e+07 9.582512e+07 6.082512e+07 1.737861 0.505087 47 3.6
20 Oct 21, 1983 1983 the-dead-zone 10 99.583 0.420190 2.379874e+07 4.590286e+07 0.000000e+00 4.590286e+07 2.210412e+07 0.928794 0.000000 69 8.8
21 Feb 4, 1983 1983 videodrome 2 99.583 0.420190 1.416501e+07 5.046378e+06 0.000000e+00 5.046378e+06 -9.118633e+06 -0.643743 0.000000 60 3.8
22 Jul 31, 1987 1987 the-lost-boys 7 113.617 0.479407 1.773025e+07 6.326921e+07 0.000000e+00 6.326921e+07 4.553896e+07 2.568434 0.000000 63 8.9
23 Mar 13, 1987 1987 evil-dead-ii 3 113.617 0.479407 7.300690e+06 1.235495e+07 0.000000e+00 1.235495e+07 5.054255e+06 0.692298 0.000000 69 8.6
24 Jul 31, 1992 1992 buffy-the-vampire-slayer 7 140.308 0.592029 1.182374e+07 2.307683e+07 0.000000e+00 2.307683e+07 1.125310e+07 0.951738 0.000000 48 8.0
25 Feb 19, 1993 1993 army-of-darkness 2 144.475 0.609612 1.804426e+07 1.886934e+07 1.640388e+07 3.527322e+07 1.722895e+07 0.954816 0.465052 57 8.5
26 Oct 27, 1995 1995 vampire-in-brooklyn 10 152.383 0.642980 2.177362e+07 3.041538e+07 0.000000e+00 3.041538e+07 8.641757e+06 0.396891 0.000000 27 8.5
27 Dec 12, 1997 1997 scream-2 12 160.525 0.677335 3.543299e+07 1.496075e+08 0.000000e+00 1.496075e+08 1.141745e+08 3.222266 0.000000 63 8.9
28 Oct 17, 1997 1997 i-know-what-you-did-last-summer 10 160.525 0.677335 2.509836e+07 1.066229e+08 7.824784e+07 1.848707e+08 1.597723e+08 6.365847 0.423257 52 2.2
29 Aug 15, 1997 1997 event-horizon 8 160.525 0.677335 8.858246e+07 3.937209e+07 0.000000e+00 3.937209e+07 -4.921038e+07 -0.555532 0.000000 35 6.9
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
134 Mar 9, 2012 2012 silent-house 3 229.596 0.968780 2.064452e+06 1.315029e+07 3.995771e+06 1.714606e+07 1.508161e+07 7.305380 0.233043 49 8.1
135 Feb 3, 2012 2012 the-innkeepers 2 229.596 0.968780 7.741696e+05 8.092240e+04 9.632105e+05 1.044133e+06 2.699633e+05 0.348713 0.922498 64 6.2
136 Feb 3, 2012 2012 kill-list 2 229.596 0.968780 8.257809e+05 2.999959e+04 4.471015e+05 4.771011e+05 -3.486798e+05 -0.422243 0.937121 67 6.5
137 Nov 30, 2012 2012 the-collection 11 229.596 0.968780 1.032226e+07 7.030239e+06 2.146349e+06 9.176588e+06 -1.145674e+06 -0.110991 0.233894 36 6.8
138 Oct 19, 2012 2012 paranormal-activity-4 10 229.596 0.968780 5.161131e+06 5.563734e+07 8.951381e+07 1.451511e+08 1.399900e+08 27.123904 0.616694 40 4.6
139 Sep 21, 2012 2012 house-at-the-end-of-the-street 9 229.596 0.968780 7.122361e+06 3.263065e+07 1.289464e+07 4.552528e+07 3.840292e+07 5.391881 0.283241 31 5.3
140 Aug 24, 2012 2012 the-apparition 8 229.596 0.968780 1.754784e+07 5.095914e+06 5.884166e+06 1.098008e+07 -6.567765e+06 -0.374278 0.535895 18 3.8
141 Aug 17, 2012 2012 the-awakening 8 229.596 0.968780 5.057908e+06 9.902455e+04 7.048441e+06 7.147465e+06 2.089557e+06 0.413127 0.986146 53 6.7
142 Apr 19, 2013 2013 the-lords-of-salem 4 232.964 0.982991 1.525955e+06 1.186054e+06 3.817430e+05 1.567797e+06 4.184269e+04 0.027421 0.243490 57 5.8
143 Apr 5, 2013 2013 evil-dead 4 232.964 0.982991 1.729415e+07 5.517837e+07 4.429185e+07 9.947022e+07 8.217607e+07 4.751668 0.445277 57 7.4
144 Mar 1, 2013 2013 the-last-exorcism-part-ii 3 232.964 0.982991 4.069212e+06 1.544195e+07 1.044710e+07 2.588905e+07 2.181984e+07 5.362177 0.403533 35 3.3
145 Jan 18, 2013 2013 mama 1 232.964 0.982991 1.525955e+07 7.286757e+07 7.779051e+07 1.506581e+08 1.353985e+08 8.873038 0.516338 57 6.4
146 Jan 4, 2013 2013 texas-chainsaw-3d 1 232.964 0.982991 2.034606e+07 3.493617e+07 1.355462e+07 4.849078e+07 2.814472e+07 1.383301 0.279530 31 4.5
147 Oct 11, 2013 2013 all-the-boys-love-mandy-lane 10 232.964 0.982991 7.629773e+05 0.000000e+00 1.994444e+06 1.994444e+06 1.231467e+06 1.614028 1.000000 44 6.4
148 Sep 13, 2013 2013 insidious-chapter-2 9 232.964 0.982991 5.086516e+06 8.503275e+07 7.969051e+07 1.647233e+08 1.596367e+08 31.384303 0.483784 40 6.7
149 Jul 23, 2013 2013 twixt 7 232.964 0.982991 7.121122e+06 0.000000e+00 1.228397e+06 1.228397e+06 -5.892725e+06 -0.827500 1.000000 40 5.2
150 Jul 19, 2013 2013 the-conjuring 7 232.964 0.982991 2.034606e+07 1.397776e+08 1.837249e+08 3.235025e+08 3.031565e+08 14.900007 0.567924 68 8.2
151 Apr 11, 2014 2014 oculus 4 236.715 0.998819 5.005914e+06 2.772801e+07 1.643967e+07 4.416768e+07 3.916176e+07 7.823099 0.372210 61 3.4
152 Oct 24, 2014 2014 ouija 10 236.715 0.998819 5.005914e+06 5.091617e+07 5.279664e+07 1.037128e+08 9.870689e+07 19.718054 0.509066 38 8.0
153 Oct 3, 2014 2014 annabelle 10 236.715 0.998819 6.507689e+06 8.437350e+07 1.665968e+08 2.509703e+08 2.444626e+08 37.565202 0.663811 37 5.2
154 Sep 19, 2014 2014 tusk 9 236.715 0.998819 3.003549e+06 1.824138e+06 0.000000e+00 1.824138e+06 -1.179410e+06 -0.392672 0.000000 55 6.0
155 Jul 2, 2014 2014 deliver-us-from-evil 7 236.715 0.998819 3.003549e+07 3.061329e+07 5.744737e+07 8.806066e+07 5.802517e+07 1.931887 0.652361 86 8.0
156 Jun 5, 2015 2015 insidious-chapter-3 6 236.995 1.000000 1.000000e+07 5.221856e+07 6.845989e+07 1.206784e+08 1.106784e+08 11.067844 0.567292 52 6.8
157 Apr 17, 2015 2015 unfriended 4 236.995 1.000000 1.000000e+06 3.248209e+07 3.007936e+07 6.256145e+07 6.156145e+07 61.561449 0.480797 59 5.6
158 Mar 13, 2015 2015 it-follows 3 236.995 1.000000 2.000000e+06 1.467408e+07 5.975697e+06 2.064977e+07 1.864977e+07 9.324887 0.289383 83 7.8
159 Feb 27, 2015 2015 the-lazarus-effect 2 236.995 1.000000 5.000000e+06 2.580157e+07 2.300000e+06 2.810157e+07 2.310157e+07 4.620314 0.081846 31 4.8
160 Oct 16, 2015 2015 goosebumps 10 236.995 1.000000 5.800000e+07 8.006946e+07 7.683984e+07 1.569093e+08 9.890930e+07 1.705333 0.489709 60 6.7
161 Sep 25, 2015 2015 the-green-inferno 9 236.995 1.000000 1.000000e+06 7.192291e+06 1.609576e+06 8.801867e+06 7.801867e+06 7.801867 0.182868 38 4.7
162 Aug 21, 2015 2015 sinister-2 8 236.995 1.000000 1.000000e+07 2.774096e+07 2.494919e+07 5.269015e+07 4.269015e+07 4.269015 0.473508 32 5.9
163 Jul 24, 2015 2015 the-vatican-tapes 7 236.995 1.000000 1.300000e+07 1.784763e+06 1.120143e+07 1.298619e+07 -1.381100e+04 -0.001062 0.862565 37 4.2

164 rows × 15 columns


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