In [67]:
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [16, 4]
import pickle
import pandas
import numpy as np
with open("final_project_dataset.pkl", "r") as data_file:
data_dict = pickle.load(data_file)
In [2]:
data_dict.items()[0]
Out[2]:
('METTS MARK',
{'bonus': 600000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'mark.metts@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 94299,
'from_messages': 29,
'from_poi_to_this_person': 38,
'from_this_person_to_poi': 1,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 1740,
'poi': False,
'restricted_stock': 585062,
'restricted_stock_deferred': 'NaN',
'salary': 365788,
'shared_receipt_with_poi': 702,
'to_messages': 807,
'total_payments': 1061827,
'total_stock_value': 585062})
In [3]:
data_dict.keys()
Out[3]:
['METTS MARK',
'BAXTER JOHN C',
'ELLIOTT STEVEN',
'CORDES WILLIAM R',
'HANNON KEVIN P',
'MORDAUNT KRISTINA M',
'MEYER ROCKFORD G',
'MCMAHON JEFFREY',
'HORTON STANLEY C',
'PIPER GREGORY F',
'HUMPHREY GENE E',
'UMANOFF ADAM S',
'BLACHMAN JEREMY M',
'SUNDE MARTIN',
'GIBBS DANA R',
'LOWRY CHARLES P',
'COLWELL WESLEY',
'MULLER MARK S',
'JACKSON CHARLENE R',
'WESTFAHL RICHARD K',
'WALTERS GARETH W',
'WALLS JR ROBERT H',
'KITCHEN LOUISE',
'CHAN RONNIE',
'BELFER ROBERT',
'SHANKMAN JEFFREY A',
'WODRASKA JOHN',
'BERGSIEKER RICHARD P',
'URQUHART JOHN A',
'BIBI PHILIPPE A',
'RIEKER PAULA H',
'WHALEY DAVID A',
'BECK SALLY W',
'HAUG DAVID L',
'ECHOLS JOHN B',
'MENDELSOHN JOHN',
'HICKERSON GARY J',
'CLINE KENNETH W',
'LEWIS RICHARD',
'HAYES ROBERT E',
'MCCARTY DANNY J',
'KOPPER MICHAEL J',
'LEFF DANIEL P',
'LAVORATO JOHN J',
'BERBERIAN DAVID',
'DETMERING TIMOTHY J',
'WAKEHAM JOHN',
'POWERS WILLIAM',
'GOLD JOSEPH',
'BANNANTINE JAMES M',
'DUNCAN JOHN H',
'SHAPIRO RICHARD S',
'SHERRIFF JOHN R',
'SHELBY REX',
'LEMAISTRE CHARLES',
'DEFFNER JOSEPH M',
'KISHKILL JOSEPH G',
'WHALLEY LAWRENCE G',
'MCCONNELL MICHAEL S',
'PIRO JIM',
'DELAINEY DAVID W',
'SULLIVAN-SHAKLOVITZ COLLEEN',
'WROBEL BRUCE',
'LINDHOLM TOD A',
'MEYER JEROME J',
'LAY KENNETH L',
'BUTTS ROBERT H',
'OLSON CINDY K',
'MCDONALD REBECCA',
'CUMBERLAND MICHAEL S',
'GAHN ROBERT S',
'MCCLELLAN GEORGE',
'HERMANN ROBERT J',
'SCRIMSHAW MATTHEW',
'GATHMANN WILLIAM D',
'HAEDICKE MARK E',
'BOWEN JR RAYMOND M',
'GILLIS JOHN',
'FITZGERALD JAY L',
'MORAN MICHAEL P',
'REDMOND BRIAN L',
'BAZELIDES PHILIP J',
'BELDEN TIMOTHY N',
'DURAN WILLIAM D',
'THORN TERENCE H',
'FASTOW ANDREW S',
'FOY JOE',
'CALGER CHRISTOPHER F',
'RICE KENNETH D',
'KAMINSKI WINCENTY J',
'LOCKHART EUGENE E',
'COX DAVID',
'OVERDYKE JR JERE C',
'PEREIRA PAULO V. FERRAZ',
'STABLER FRANK',
'SKILLING JEFFREY K',
'BLAKE JR. NORMAN P',
'SHERRICK JEFFREY B',
'PRENTICE JAMES',
'GRAY RODNEY',
'PICKERING MARK R',
'THE TRAVEL AGENCY IN THE PARK',
'NOLES JAMES L',
'KEAN STEVEN J',
'TOTAL',
'FOWLER PEGGY',
'WASAFF GEORGE',
'WHITE JR THOMAS E',
'CHRISTODOULOU DIOMEDES',
'ALLEN PHILLIP K',
'SHARP VICTORIA T',
'JAEDICKE ROBERT',
'WINOKUR JR. HERBERT S',
'BROWN MICHAEL',
'BADUM JAMES P',
'HUGHES JAMES A',
'REYNOLDS LAWRENCE',
'DIMICHELE RICHARD G',
'BHATNAGAR SANJAY',
'CARTER REBECCA C',
'BUCHANAN HAROLD G',
'YEAP SOON',
'MURRAY JULIA H',
'GARLAND C KEVIN',
'DODSON KEITH',
'YEAGER F SCOTT',
'HIRKO JOSEPH',
'DIETRICH JANET R',
'DERRICK JR. JAMES V',
'FREVERT MARK A',
'PAI LOU L',
'BAY FRANKLIN R',
'HAYSLETT RODERICK J',
'FUGH JOHN L',
'FALLON JAMES B',
'KOENIG MARK E',
'SAVAGE FRANK',
'IZZO LAWRENCE L',
'TILNEY ELIZABETH A',
'MARTIN AMANDA K',
'BUY RICHARD B',
'GRAMM WENDY L',
'CAUSEY RICHARD A',
'TAYLOR MITCHELL S',
'DONAHUE JR JEFFREY M',
'GLISAN JR BEN F']
In [4]:
expenses = map(lambda (x, y): (x,y['expenses']),data_dict.items())
expenses.sort(cmp = lambda (_1,expense1),(_2,expense2): cmp(expense1,expense2))
In [5]:
expenses
Out[5]:
[('MENDELSOHN JOHN', 148),
('HAUG DAVID L', 475),
('BUCHANAN HAROLD G', 600),
('BLAKE JR. NORMAN P', 1279),
('WINOKUR JR. HERBERT S', 1413),
('MEYER JEROME J', 2151),
('DIETRICH JANET R', 3475),
('BADUM JAMES P', 3486),
('HUMPHREY GENE E', 4994),
('KITCHEN LOUISE', 5774),
('MARTIN AMANDA K', 8211),
('REYNOLDS LAWRENCE', 8409),
('BUTTS ROBERT H', 9410),
('JACKSON CHARLENE R', 10181),
('BAXTER JOHN C', 11200),
('BERBERIAN DAVID', 11892),
('ALLEN PHILLIP K', 13868),
('REDMOND BRIAN L', 14689),
('COLWELL WESLEY', 16514),
('STABLER FRANK', 16514),
('BELDEN TIMOTHY N', 17355),
('OVERDYKE JR JERE C', 18834),
('ECHOLS JOHN B', 21530),
('CUMBERLAND MICHAEL S', 22344),
('SHELBY REX', 22884),
('FITZGERALD JAY L', 23870),
('DURAN WILLIAM D', 25785),
('COX DAVID', 27861),
('PEREIRA PAULO V. FERRAZ', 27942),
('IZZO LAWRENCE L', 28093),
('DODSON KEITH', 28164),
('SKILLING JEFFREY K', 29336),
('CAUSEY RICHARD A', 30674),
('PICKERING MARK R', 31653),
('PAI LOU L', 32047),
('RIEKER PAULA H', 33271),
('WALTERS GARETH W', 33785),
('HANNON KEVIN P', 34039),
('MORDAUNT KRISTINA M', 35018),
('DIMICHELE RICHARD G', 35812),
('CALGER CHRISTOPHER F', 35818),
('BECK SALLY W', 37172),
('BIBI PHILIPPE A', 38559),
('DEFFNER JOSEPH M', 41626),
('KEAN STEVEN J', 41953),
('PIPER GREGORY F', 43057),
('THORN TERENCE H', 46145),
('RICE KENNETH D', 46950),
('HERMANN ROBERT J', 48357),
('GARLAND C KEVIN', 48405),
('BROWN MICHAEL', 49288),
('LAVORATO JOHN J', 49537),
('GAHN ROBERT S', 50080),
('WALLS JR ROBERT H', 50936),
('DERRICK JR. JAMES V', 51124),
('WESTFAHL RICHARD K', 51870),
('DETMERING TIMOTHY J', 52255),
('UMANOFF ADAM S', 53122),
('YEAGER F SCOTT', 53947),
('YEAP SOON', 55097),
('FASTOW ANDREW S', 55921),
('BANNANTINE JAMES M', 56301),
('MURRAY JULIA H', 57580),
('LINDHOLM TOD A', 57727),
('WHALLEY LAWRENCE G', 57838),
('BERGSIEKER RICHARD P', 59175),
('OLSON CINDY K', 63791),
('BOWEN JR RAYMOND M', 65907),
('HAEDICKE MARK E', 76169),
('HIRKO JOSEPH', 77978),
('ELLIOTT STEVEN', 78552),
('WHITE JR THOMAS E', 81353),
('MCCONNELL MICHAEL S', 81364),
('KAMINSKI WINCENTY J', 83585),
('BLACHMAN JEREMY M', 84208),
('DELAINEY DAVID W', 86174),
('FREVERT MARK A', 86987),
('METTS MARK', 94299),
('FALLON JAMES B', 95924),
('DONAHUE JR JEFFREY M', 96268),
('HICKERSON GARY J', 98849),
('LAY KENNETH L', 99832),
('WAKEHAM JOHN', 103773),
('KISHKILL JOSEPH G', 116335),
('SHARP VICTORIA T', 116337),
('KOPPER MICHAEL J', 118134),
('GLISAN JR BEN F', 125978),
('KOENIG MARK E', 127017),
('BAY FRANKLIN R', 129142),
('MCMAHON JEFFREY', 137108),
('SHAPIRO RICHARD S', 137767),
('SHANKMAN JEFFREY A', 178979),
('URQUHART JOHN A', 228656),
('MCCLELLAN GEORGE', 228763),
('TOTAL', 5235198),
('CORDES WILLIAM R', 'NaN'),
('MEYER ROCKFORD G', 'NaN'),
('HORTON STANLEY C', 'NaN'),
('SUNDE MARTIN', 'NaN'),
('GIBBS DANA R', 'NaN'),
('LOWRY CHARLES P', 'NaN'),
('MULLER MARK S', 'NaN'),
('CHAN RONNIE', 'NaN'),
('BELFER ROBERT', 'NaN'),
('WODRASKA JOHN', 'NaN'),
('WHALEY DAVID A', 'NaN'),
('CLINE KENNETH W', 'NaN'),
('LEWIS RICHARD', 'NaN'),
('HAYES ROBERT E', 'NaN'),
('MCCARTY DANNY J', 'NaN'),
('LEFF DANIEL P', 'NaN'),
('POWERS WILLIAM', 'NaN'),
('GOLD JOSEPH', 'NaN'),
('DUNCAN JOHN H', 'NaN'),
('SHERRIFF JOHN R', 'NaN'),
('LEMAISTRE CHARLES', 'NaN'),
('PIRO JIM', 'NaN'),
('SULLIVAN-SHAKLOVITZ COLLEEN', 'NaN'),
('WROBEL BRUCE', 'NaN'),
('MCDONALD REBECCA', 'NaN'),
('SCRIMSHAW MATTHEW', 'NaN'),
('GATHMANN WILLIAM D', 'NaN'),
('GILLIS JOHN', 'NaN'),
('MORAN MICHAEL P', 'NaN'),
('BAZELIDES PHILIP J', 'NaN'),
('FOY JOE', 'NaN'),
('LOCKHART EUGENE E', 'NaN'),
('SHERRICK JEFFREY B', 'NaN'),
('PRENTICE JAMES', 'NaN'),
('GRAY RODNEY', 'NaN'),
('THE TRAVEL AGENCY IN THE PARK', 'NaN'),
('NOLES JAMES L', 'NaN'),
('FOWLER PEGGY', 'NaN'),
('WASAFF GEORGE', 'NaN'),
('CHRISTODOULOU DIOMEDES', 'NaN'),
('JAEDICKE ROBERT', 'NaN'),
('HUGHES JAMES A', 'NaN'),
('BHATNAGAR SANJAY', 'NaN'),
('CARTER REBECCA C', 'NaN'),
('HAYSLETT RODERICK J', 'NaN'),
('FUGH JOHN L', 'NaN'),
('SAVAGE FRANK', 'NaN'),
('TILNEY ELIZABETH A', 'NaN'),
('BUY RICHARD B', 'NaN'),
('GRAMM WENDY L', 'NaN'),
('TAYLOR MITCHELL S', 'NaN')]
In [6]:
(people, values) = zip(*expenses)
plt.scatter(range(len(values)),values)
Out[6]:
<matplotlib.collections.PathCollection at 0x10d6063d0>
There is an outlier: TOTAL. This certainly a column for totals. Let's remove it before proceeding.
In [7]:
del data_dict['TOTAL']
In [44]:
df = pandas.DataFrame.from_dict(data_dict, orient='index')
In [45]:
df.head()
Out[45]:
salary
to_messages
deferral_payments
total_payments
exercised_stock_options
bonus
restricted_stock
shared_receipt_with_poi
restricted_stock_deferred
total_stock_value
...
loan_advances
from_messages
other
from_this_person_to_poi
poi
director_fees
deferred_income
long_term_incentive
email_address
from_poi_to_this_person
ALLEN PHILLIP K
201955
2902
2869717
4484442
1729541
4175000
126027
1407
-126027
1729541
...
NaN
2195
152
65
False
NaN
-3081055
304805
phillip.allen@enron.com
47
BADUM JAMES P
NaN
NaN
178980
182466
257817
NaN
NaN
NaN
NaN
257817
...
NaN
NaN
NaN
NaN
False
NaN
NaN
NaN
NaN
NaN
BANNANTINE JAMES M
477
566
NaN
916197
4046157
NaN
1757552
465
-560222
5243487
...
NaN
29
864523
0
False
NaN
-5104
NaN
james.bannantine@enron.com
39
BAXTER JOHN C
267102
NaN
1295738
5634343
6680544
1200000
3942714
NaN
NaN
10623258
...
NaN
NaN
2660303
NaN
False
NaN
-1386055
1586055
NaN
NaN
BAY FRANKLIN R
239671
NaN
260455
827696
NaN
400000
145796
NaN
-82782
63014
...
NaN
NaN
69
NaN
False
NaN
-201641
NaN
frank.bay@enron.com
NaN
5 rows × 21 columns
In [13]:
print "Dataset size: %d rows x %d columns"%df.shape
Dataset size: 145 rows x 21 columns
In [52]:
df.dtypes
Out[52]:
salary object
to_messages object
deferral_payments object
total_payments object
exercised_stock_options object
bonus object
restricted_stock object
shared_receipt_with_poi object
restricted_stock_deferred object
total_stock_value object
expenses object
loan_advances object
from_messages object
other object
from_this_person_to_poi object
poi bool
director_fees object
deferred_income object
long_term_incentive object
email_address object
from_poi_to_this_person object
dtype: object
In [56]:
print "Feature | Missing values"
print "---|---"
for column in df.columns:
if column != 'poi':
print "%s | %d"%(column,(df[column] == 'NaN').sum())
Feature | Missing values
---|---
salary | 51
to_messages | 59
deferral_payments | 107
total_payments | 21
exercised_stock_options | 44
bonus | 64
restricted_stock | 36
shared_receipt_with_poi | 59
restricted_stock_deferred | 128
total_stock_value | 20
expenses | 51
loan_advances | 142
from_messages | 59
other | 53
from_this_person_to_poi | 59
director_fees | 129
deferred_income | 97
long_term_incentive | 80
email_address | 34
from_poi_to_this_person | 59
In [83]:
df['poi'].hist( figsize=(5,3))
plt.xticks(np.array([0.05,0.95]), ['Non POI', 'POI'], rotation='horizontal')
plt.tick_params(bottom='on',top='off', right='off', left='on')
In [ ]:
In [19]:
df['expenses'] = df['expenses'].astype('float')
df['salary'] = df['salary'].astype('float')
df['from_this_person_to_poi'] = df['from_this_person_to_poi'].astype('float')
df['from_poi_to_this_person'] = df['from_poi_to_this_person'].astype('float')
In [20]:
df['expenses'] = df['expenses'].astype('float')
df['expenses'].hist(bins=100)
plt.figure()
df['expenses'].hist(bins=50)
plt.figure()
df['expenses'].hist(bins=20)
Out[20]:
<matplotlib.axes._subplots.AxesSubplot at 0x10dde7cd0>
We can see that there are three employees spend considerably more than others.
In [21]:
df[df['expenses']>150000]
Out[21]:
salary
to_messages
deferral_payments
total_payments
exercised_stock_options
bonus
restricted_stock
shared_receipt_with_poi
restricted_stock_deferred
total_stock_value
...
loan_advances
from_messages
other
from_this_person_to_poi
poi
director_fees
deferred_income
long_term_incentive
email_address
from_poi_to_this_person
MCCLELLAN GEORGE
263413
1744
NaN
1318763
506765
900000
441096
1469
NaN
947861
...
NaN
49
51587
0
False
NaN
-125000
NaN
george.mcclellan@enron.com
52
SHANKMAN JEFFREY A
304110
3221
NaN
3038702
1441898
2000000
630137
1730
NaN
2072035
...
NaN
2681
1191
83
False
NaN
NaN
554422
jeffrey.shankman@enron.com
94
URQUHART JOHN A
NaN
NaN
NaN
228656
NaN
NaN
NaN
NaN
NaN
NaN
...
NaN
NaN
NaN
NaN
False
36666
-36666
NaN
NaN
NaN
3 rows × 21 columns
In [22]:
df['salary'] = df['salary'].astype('float')
df['salary'].hist(bins=100)
plt.figure()
df['salary'].hist(bins=50)
plt.figure()
df['salary'].hist(bins=20)
Out[22]:
<matplotlib.axes._subplots.AxesSubplot at 0x10e6cad10>
There are four people with a considerably higher salary than other employees (>\$600K).
In [23]:
df[df['salary']>600000]
Out[23]:
salary
to_messages
deferral_payments
total_payments
exercised_stock_options
bonus
restricted_stock
shared_receipt_with_poi
restricted_stock_deferred
total_stock_value
...
loan_advances
from_messages
other
from_this_person_to_poi
poi
director_fees
deferred_income
long_term_incentive
email_address
from_poi_to_this_person
FREVERT MARK A
1060932
3275
6426990
17252530
10433518
2000000
4188667
2979
NaN
14622185
...
2000000
21
7427621
6
False
NaN
-3367011
1617011
mark.frevert@enron.com
242
LAY KENNETH L
1072321
4273
202911
103559793
34348384
7000000
14761694
2411
NaN
49110078
...
81525000
36
10359729
16
True
NaN
-300000
3600000
kenneth.lay@enron.com
123
PICKERING MARK R
655037
898
NaN
1386690
28798
300000
NaN
728
NaN
28798
...
400000
67
NaN
0
False
NaN
NaN
NaN
mark.pickering@enron.com
7
SKILLING JEFFREY K
1111258
3627
NaN
8682716
19250000
5600000
6843672
2042
NaN
26093672
...
NaN
108
22122
30
True
NaN
NaN
1920000
jeff.skilling@enron.com
88
4 rows × 21 columns
Top salary employees are not the same as top expenses employees.
In [25]:
df[['from_this_person_to_poi','from_poi_to_this_person']].hist(bins=20)
Out[25]:
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x10ee66310>,
<matplotlib.axes._subplots.AxesSubplot object at 0x10e6feed0>]], dtype=object)
In [26]:
df[df['from_this_person_to_poi']>280]
Out[26]:
salary
to_messages
deferral_payments
total_payments
exercised_stock_options
bonus
restricted_stock
shared_receipt_with_poi
restricted_stock_deferred
total_stock_value
...
loan_advances
from_messages
other
from_this_person_to_poi
poi
director_fees
deferred_income
long_term_incentive
email_address
from_poi_to_this_person
BECK SALLY W
231330
7315
NaN
969068
NaN
700000
126027
2639
NaN
126027
...
NaN
4343
566
386
False
NaN
NaN
NaN
sally.beck@enron.com
144
DELAINEY DAVID W
365163
3093
NaN
4747979
2291113
3000000
1323148
2097
NaN
3614261
...
NaN
3069
1661
609
True
NaN
NaN
1294981
david.delainey@enron.com
66
KEAN STEVEN J
404338
12754
NaN
1747522
2022048
1000000
4131594
3639
NaN
6153642
...
NaN
6759
1231
387
False
NaN
NaN
300000
steven.kean@enron.com
140
LAVORATO JOHN J
339288
7259
NaN
10425757
4158995
8000000
1008149
3962
NaN
5167144
...
NaN
2585
1552
411
False
NaN
NaN
2035380
john.lavorato@enron.com
528
4 rows × 21 columns
In [27]:
df[df['from_poi_to_this_person']>300]
Out[27]:
salary
to_messages
deferral_payments
total_payments
exercised_stock_options
bonus
restricted_stock
shared_receipt_with_poi
restricted_stock_deferred
total_stock_value
...
loan_advances
from_messages
other
from_this_person_to_poi
poi
director_fees
deferred_income
long_term_incentive
email_address
from_poi_to_this_person
DIETRICH JANET R
250100
2572
NaN
1410464
1550019
600000
315068
1902
NaN
1865087
...
NaN
63
473
14
False
NaN
NaN
556416
janet.dietrich@enron.com
305
LAVORATO JOHN J
339288
7259
NaN
10425757
4158995
8000000
1008149
3962
NaN
5167144
...
NaN
2585
1552
411
False
NaN
NaN
2035380
john.lavorato@enron.com
528
2 rows × 21 columns
In [28]:
df[['from_this_person_to_poi','from_poi_to_this_person']].sort('from_poi_to_this_person').plot()
/Users/luiscruz/dev/udacity_data_analyst/venv/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)
if __name__ == '__main__':
Out[28]:
<matplotlib.axes._subplots.AxesSubplot at 0x10eac0690>
High 'from_this_person_to_poi' does not necessarily mean high 'from_poi_to_this_person', so both variables should evaluated.
In [33]:
df['bonus'] = df['bonus'].astype('float')
In [37]:
df[['salary','bonus']].plot(kind='scatter', x='salary', y='bonus')
Out[37]:
<matplotlib.axes._subplots.AxesSubplot at 0x10ded8690>
Perhaps makes sense combining salary with bonus. A new feature could be salary+bonus
In [43]:
df['salary+bonus']=df['salary']+df['bonus']
In [44]:
list(df.columns)
Out[44]:
['salary',
'to_messages',
'deferral_payments',
'total_payments',
'exercised_stock_options',
'bonus',
'restricted_stock',
'shared_receipt_with_poi',
'restricted_stock_deferred',
'total_stock_value',
'expenses',
'loan_advances',
'from_messages',
'other',
'from_this_person_to_poi',
'poi',
'director_fees',
'deferred_income',
'long_term_incentive',
'email_address',
'from_poi_to_this_person',
'salary_bonus',
'salary+bonus']
In [53]:
1+np.nan
Out[53]:
nan
In [76]:
for _,obj in data_dict.items():
salary_bonus_ratio = np.float(obj['bonus'])/np.float(obj['salary'])
if np.isnan(salary_bonus_ratio):
salary_bonus_ratio = -1
obj['salary_bonus_ratio'] = salary_bonus_ratio
In [77]:
data_dict.items()
Out[77]:
[('METTS MARK',
{'bonus': 600000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'mark.metts@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 94299,
'from_messages': 29,
'from_poi_to_this_person': 38,
'from_this_person_to_poi': 1,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 1740,
'poi': False,
'restricted_stock': 585062,
'restricted_stock_deferred': 'NaN',
'salary': 365788,
'salary+bonus': 965788.0,
'salary_bonus_ratio': 1.6402943781644013,
'shared_receipt_with_poi': 702,
'to_messages': 807,
'total_payments': 1061827,
'total_stock_value': 585062}),
('BAXTER JOHN C',
{'bonus': 1200000,
'deferral_payments': 1295738,
'deferred_income': -1386055,
'director_fees': 'NaN',
'email_address': 'NaN',
'exercised_stock_options': 6680544,
'expenses': 11200,
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 1586055,
'other': 2660303,
'poi': False,
'restricted_stock': 3942714,
'restricted_stock_deferred': 'NaN',
'salary': 267102,
'salary+bonus': 1467102.0,
'salary_bonus_ratio': 4.492665723206865,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 5634343,
'total_stock_value': 10623258}),
('ELLIOTT STEVEN',
{'bonus': 350000,
'deferral_payments': 'NaN',
'deferred_income': -400729,
'director_fees': 'NaN',
'email_address': 'steven.elliott@enron.com',
'exercised_stock_options': 4890344,
'expenses': 78552,
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 12961,
'poi': False,
'restricted_stock': 1788391,
'restricted_stock_deferred': 'NaN',
'salary': 170941,
'salary+bonus': 520941.0,
'salary_bonus_ratio': 2.047490069673162,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 211725,
'total_stock_value': 6678735}),
('CORDES WILLIAM R',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'bill.cordes@enron.com',
'exercised_stock_options': 651850,
'expenses': 'NaN',
'from_messages': 12,
'from_poi_to_this_person': 10,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 386335,
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 58,
'to_messages': 764,
'total_payments': 'NaN',
'total_stock_value': 1038185}),
('HANNON KEVIN P',
{'bonus': 1500000,
'deferral_payments': 'NaN',
'deferred_income': -3117011,
'director_fees': 'NaN',
'email_address': 'kevin.hannon@enron.com',
'exercised_stock_options': 5538001,
'expenses': 34039,
'from_messages': 32,
'from_poi_to_this_person': 32,
'from_this_person_to_poi': 21,
'loan_advances': 'NaN',
'long_term_incentive': 1617011,
'other': 11350,
'poi': True,
'restricted_stock': 853064,
'restricted_stock_deferred': 'NaN',
'salary': 243293,
'salary+bonus': 1743293.0,
'salary_bonus_ratio': 6.165405498719651,
'shared_receipt_with_poi': 1035,
'to_messages': 1045,
'total_payments': 288682,
'total_stock_value': 6391065}),
('MORDAUNT KRISTINA M',
{'bonus': 325000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'kristina.mordaunt@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 35018,
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 1411,
'poi': False,
'restricted_stock': 208510,
'restricted_stock_deferred': 'NaN',
'salary': 267093,
'salary+bonus': 592093.0,
'salary_bonus_ratio': 1.2168046335920448,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 628522,
'total_stock_value': 208510}),
('MEYER ROCKFORD G',
{'bonus': 'NaN',
'deferral_payments': 1848227,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'rockford.meyer@enron.com',
'exercised_stock_options': 493489,
'expenses': 'NaN',
'from_messages': 28,
'from_poi_to_this_person': 0,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 462384,
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 22,
'to_messages': 232,
'total_payments': 1848227,
'total_stock_value': 955873}),
('MCMAHON JEFFREY',
{'bonus': 2600000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'jeffrey.mcmahon@enron.com',
'exercised_stock_options': 1104054,
'expenses': 137108,
'from_messages': 48,
'from_poi_to_this_person': 58,
'from_this_person_to_poi': 26,
'loan_advances': 'NaN',
'long_term_incentive': 694862,
'other': 297353,
'poi': False,
'restricted_stock': 558801,
'restricted_stock_deferred': 'NaN',
'salary': 370448,
'salary+bonus': 2970448.0,
'salary_bonus_ratio': 7.018528916339135,
'shared_receipt_with_poi': 2228,
'to_messages': 2355,
'total_payments': 4099771,
'total_stock_value': 1662855}),
('HORTON STANLEY C',
{'bonus': 'NaN',
'deferral_payments': 3131860,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'stanley.horton@enron.com',
'exercised_stock_options': 5210569,
'expenses': 'NaN',
'from_messages': 1073,
'from_poi_to_this_person': 44,
'from_this_person_to_poi': 15,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 2046079,
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 1074,
'to_messages': 2350,
'total_payments': 3131860,
'total_stock_value': 7256648}),
('PIPER GREGORY F',
{'bonus': 400000,
'deferral_payments': 1130036,
'deferred_income': -33333,
'director_fees': 'NaN',
'email_address': 'greg.piper@enron.com',
'exercised_stock_options': 880290,
'expenses': 43057,
'from_messages': 222,
'from_poi_to_this_person': 61,
'from_this_person_to_poi': 48,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 778,
'poi': False,
'restricted_stock': 409554,
'restricted_stock_deferred': -409554,
'salary': 197091,
'salary+bonus': 597091.0,
'salary_bonus_ratio': 2.0295193590777862,
'shared_receipt_with_poi': 742,
'to_messages': 1238,
'total_payments': 1737629,
'total_stock_value': 880290}),
('HUMPHREY GENE E',
{'bonus': 'NaN',
'deferral_payments': 2964506,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'gene.humphrey@enron.com',
'exercised_stock_options': 2282768,
'expenses': 4994,
'from_messages': 17,
'from_poi_to_this_person': 10,
'from_this_person_to_poi': 17,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 130724,
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 119,
'to_messages': 128,
'total_payments': 3100224,
'total_stock_value': 2282768}),
('UMANOFF ADAM S',
{'bonus': 788750,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'adam.umanoff@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 53122,
'from_messages': 18,
'from_poi_to_this_person': 12,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 288589,
'salary+bonus': 1077339.0,
'salary_bonus_ratio': 2.7331256562100426,
'shared_receipt_with_poi': 41,
'to_messages': 111,
'total_payments': 1130461,
'total_stock_value': 'NaN'}),
('BLACHMAN JEREMY M',
{'bonus': 850000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'jeremy.blachman@enron.com',
'exercised_stock_options': 765313,
'expenses': 84208,
'from_messages': 14,
'from_poi_to_this_person': 25,
'from_this_person_to_poi': 2,
'loan_advances': 'NaN',
'long_term_incentive': 831809,
'other': 272,
'poi': False,
'restricted_stock': 189041,
'restricted_stock_deferred': 'NaN',
'salary': 248546,
'salary+bonus': 1098546.0,
'salary_bonus_ratio': 3.419890080709406,
'shared_receipt_with_poi': 2326,
'to_messages': 2475,
'total_payments': 2014835,
'total_stock_value': 954354}),
('SUNDE MARTIN',
{'bonus': 700000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'marty.sunde@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 'NaN',
'from_messages': 38,
'from_poi_to_this_person': 37,
'from_this_person_to_poi': 13,
'loan_advances': 'NaN',
'long_term_incentive': 476451,
'other': 111122,
'poi': False,
'restricted_stock': 698920,
'restricted_stock_deferred': 'NaN',
'salary': 257486,
'salary+bonus': 957486.0,
'salary_bonus_ratio': 2.7185944090164127,
'shared_receipt_with_poi': 2565,
'to_messages': 2647,
'total_payments': 1545059,
'total_stock_value': 698920}),
('GIBBS DANA R',
{'bonus': 'NaN',
'deferral_payments': 504610,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'dana.gibbs@enron.com',
'exercised_stock_options': 2218275,
'expenses': 'NaN',
'from_messages': 12,
'from_poi_to_this_person': 0,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 461912,
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 23,
'to_messages': 169,
'total_payments': 966522,
'total_stock_value': 2218275}),
('LOWRY CHARLES P',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'NaN',
'exercised_stock_options': 372205,
'expenses': 'NaN',
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 153686,
'restricted_stock_deferred': -153686,
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 'NaN',
'total_stock_value': 372205}),
('COLWELL WESLEY',
{'bonus': 1200000,
'deferral_payments': 27610,
'deferred_income': -144062,
'director_fees': 'NaN',
'email_address': 'wes.colwell@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 16514,
'from_messages': 40,
'from_poi_to_this_person': 240,
'from_this_person_to_poi': 11,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 101740,
'poi': True,
'restricted_stock': 698242,
'restricted_stock_deferred': 'NaN',
'salary': 288542,
'salary+bonus': 1488542.0,
'salary_bonus_ratio': 4.158839960906905,
'shared_receipt_with_poi': 1132,
'to_messages': 1758,
'total_payments': 1490344,
'total_stock_value': 698242}),
('MULLER MARK S',
{'bonus': 1100000,
'deferral_payments': 842924,
'deferred_income': -719000,
'director_fees': 'NaN',
'email_address': 's..muller@enron.com',
'exercised_stock_options': 1056320,
'expenses': 'NaN',
'from_messages': 16,
'from_poi_to_this_person': 12,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 1725545,
'other': 947,
'poi': False,
'restricted_stock': 360528,
'restricted_stock_deferred': 'NaN',
'salary': 251654,
'salary+bonus': 1351654.0,
'salary_bonus_ratio': 4.3710809285765375,
'shared_receipt_with_poi': 114,
'to_messages': 136,
'total_payments': 3202070,
'total_stock_value': 1416848}),
('JACKSON CHARLENE R',
{'bonus': 250000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'charlene.jackson@enron.com',
'exercised_stock_options': 185063,
'expenses': 10181,
'from_messages': 56,
'from_poi_to_this_person': 25,
'from_this_person_to_poi': 19,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 2435,
'poi': False,
'restricted_stock': 540672,
'restricted_stock_deferred': 'NaN',
'salary': 288558,
'salary+bonus': 538558.0,
'salary_bonus_ratio': 0.8663769502145149,
'shared_receipt_with_poi': 117,
'to_messages': 258,
'total_payments': 551174,
'total_stock_value': 725735}),
('WESTFAHL RICHARD K',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': -10800,
'director_fees': 'NaN',
'email_address': 'dick.westfahl@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 51870,
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 256191,
'other': 401130,
'poi': False,
'restricted_stock': 384930,
'restricted_stock_deferred': 'NaN',
'salary': 63744,
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 762135,
'total_stock_value': 384930}),
('WALTERS GARETH W',
{'bonus': 'NaN',
'deferral_payments': 53625,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'NaN',
'exercised_stock_options': 1030329,
'expenses': 33785,
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 87410,
'total_stock_value': 1030329}),
('WALLS JR ROBERT H',
{'bonus': 850000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'rob.walls@enron.com',
'exercised_stock_options': 4346544,
'expenses': 50936,
'from_messages': 146,
'from_poi_to_this_person': 17,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 540751,
'other': 2,
'poi': False,
'restricted_stock': 1552453,
'restricted_stock_deferred': 'NaN',
'salary': 357091,
'salary+bonus': 1207091.0,
'salary_bonus_ratio': 2.380345626184922,
'shared_receipt_with_poi': 215,
'to_messages': 671,
'total_payments': 1798780,
'total_stock_value': 5898997}),
('KITCHEN LOUISE',
{'bonus': 3100000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'louise.kitchen@enron.com',
'exercised_stock_options': 81042,
'expenses': 5774,
'from_messages': 1728,
'from_poi_to_this_person': 251,
'from_this_person_to_poi': 194,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 93925,
'poi': False,
'restricted_stock': 466101,
'restricted_stock_deferred': 'NaN',
'salary': 271442,
'salary+bonus': 3371442.0,
'salary_bonus_ratio': 11.420487617981005,
'shared_receipt_with_poi': 3669,
'to_messages': 8305,
'total_payments': 3471141,
'total_stock_value': 547143}),
('CHAN RONNIE',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': -98784,
'director_fees': 98784,
'email_address': 'NaN',
'exercised_stock_options': 'NaN',
'expenses': 'NaN',
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 32460,
'restricted_stock_deferred': -32460,
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 'NaN',
'total_stock_value': 'NaN'}),
('BELFER ROBERT',
{'bonus': 'NaN',
'deferral_payments': -102500,
'deferred_income': 'NaN',
'director_fees': 3285,
'email_address': 'NaN',
'exercised_stock_options': 3285,
'expenses': 'NaN',
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 44093,
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 102500,
'total_stock_value': -44093}),
('SHANKMAN JEFFREY A',
{'bonus': 2000000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'jeffrey.shankman@enron.com',
'exercised_stock_options': 1441898,
'expenses': 178979,
'from_messages': 2681,
'from_poi_to_this_person': 94,
'from_this_person_to_poi': 83,
'loan_advances': 'NaN',
'long_term_incentive': 554422,
'other': 1191,
'poi': False,
'restricted_stock': 630137,
'restricted_stock_deferred': 'NaN',
'salary': 304110,
'salary+bonus': 2304110.0,
'salary_bonus_ratio': 6.576567689322943,
'shared_receipt_with_poi': 1730,
'to_messages': 3221,
'total_payments': 3038702,
'total_stock_value': 2072035}),
('WODRASKA JOHN',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'john.wodraska@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 'NaN',
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 189583,
'poi': False,
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'director_fees': 'NaN',
'email_address': 'elizabeth.tilney@enron.com',
'exercised_stock_options': 591250,
'expenses': 'NaN',
'from_messages': 19,
'from_poi_to_this_person': 10,
'from_this_person_to_poi': 11,
'loan_advances': 'NaN',
'long_term_incentive': 275000,
'other': 152055,
'poi': False,
'restricted_stock': 576792,
'restricted_stock_deferred': 'NaN',
'salary': 247338,
'salary+bonus': 547338.0,
'salary_bonus_ratio': 1.2129151201998885,
'shared_receipt_with_poi': 379,
'to_messages': 460,
'total_payments': 399393,
'total_stock_value': 1168042}),
('MARTIN AMANDA K',
{'bonus': 'NaN',
'deferral_payments': 85430,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'a..martin@enron.com',
'exercised_stock_options': 2070306,
'expenses': 8211,
'from_messages': 230,
'from_poi_to_this_person': 8,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 5145434,
'other': 2818454,
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 349487,
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 477,
'to_messages': 1522,
'total_payments': 8407016,
'total_stock_value': 2070306}),
('BUY RICHARD B',
{'bonus': 900000,
'deferral_payments': 649584,
'deferred_income': -694862,
'director_fees': 'NaN',
'email_address': 'rick.buy@enron.com',
'exercised_stock_options': 2542813,
'expenses': 'NaN',
'from_messages': 1053,
'from_poi_to_this_person': 156,
'from_this_person_to_poi': 71,
'loan_advances': 'NaN',
'long_term_incentive': 769862,
'other': 400572,
'poi': False,
'restricted_stock': 901657,
'restricted_stock_deferred': 'NaN',
'salary': 330546,
'salary+bonus': 1230546.0,
'salary_bonus_ratio': 2.722767784211577,
'shared_receipt_with_poi': 2333,
'to_messages': 3523,
'total_payments': 2355702,
'total_stock_value': 3444470}),
('GRAMM WENDY L',
{'bonus': 'NaN',
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 119292,
'email_address': 'NaN',
'exercised_stock_options': 'NaN',
'expenses': 'NaN',
'from_messages': 'NaN',
'from_poi_to_this_person': 'NaN',
'from_this_person_to_poi': 'NaN',
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 'NaN',
'restricted_stock_deferred': 'NaN',
'salary': 'NaN',
'salary+bonus': -1,
'salary_bonus_ratio': -1,
'shared_receipt_with_poi': 'NaN',
'to_messages': 'NaN',
'total_payments': 119292,
'total_stock_value': 'NaN'}),
('CAUSEY RICHARD A',
{'bonus': 1000000,
'deferral_payments': 'NaN',
'deferred_income': -235000,
'director_fees': 'NaN',
'email_address': 'richard.causey@enron.com',
'exercised_stock_options': 'NaN',
'expenses': 30674,
'from_messages': 49,
'from_poi_to_this_person': 58,
'from_this_person_to_poi': 12,
'loan_advances': 'NaN',
'long_term_incentive': 350000,
'other': 307895,
'poi': True,
'restricted_stock': 2502063,
'restricted_stock_deferred': 'NaN',
'salary': 415189,
'salary+bonus': 1415189.0,
'salary_bonus_ratio': 2.4085416521150607,
'shared_receipt_with_poi': 1585,
'to_messages': 1892,
'total_payments': 1868758,
'total_stock_value': 2502063}),
('TAYLOR MITCHELL S',
{'bonus': 600000,
'deferral_payments': 227449,
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'mitchell.taylor@enron.com',
'exercised_stock_options': 3181250,
'expenses': 'NaN',
'from_messages': 29,
'from_poi_to_this_person': 0,
'from_this_person_to_poi': 0,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 'NaN',
'poi': False,
'restricted_stock': 563798,
'restricted_stock_deferred': 'NaN',
'salary': 265214,
'salary+bonus': 865214.0,
'salary_bonus_ratio': 2.2623240100447184,
'shared_receipt_with_poi': 300,
'to_messages': 533,
'total_payments': 1092663,
'total_stock_value': 3745048}),
('DONAHUE JR JEFFREY M',
{'bonus': 800000,
'deferral_payments': 'NaN',
'deferred_income': -300000,
'director_fees': 'NaN',
'email_address': 'jeff.donahue@enron.com',
'exercised_stock_options': 765920,
'expenses': 96268,
'from_messages': 22,
'from_poi_to_this_person': 188,
'from_this_person_to_poi': 11,
'loan_advances': 'NaN',
'long_term_incentive': 'NaN',
'other': 891,
'poi': False,
'restricted_stock': 315068,
'restricted_stock_deferred': 'NaN',
'salary': 278601,
'salary+bonus': 1078601.0,
'salary_bonus_ratio': 2.8714900520816506,
'shared_receipt_with_poi': 772,
'to_messages': 865,
'total_payments': 875760,
'total_stock_value': 1080988}),
('GLISAN JR BEN F',
{'bonus': 600000,
'deferral_payments': 'NaN',
'deferred_income': 'NaN',
'director_fees': 'NaN',
'email_address': 'ben.glisan@enron.com',
'exercised_stock_options': 384728,
'expenses': 125978,
'from_messages': 16,
'from_poi_to_this_person': 52,
'from_this_person_to_poi': 6,
'loan_advances': 'NaN',
'long_term_incentive': 71023,
'other': 200308,
'poi': True,
'restricted_stock': 393818,
'restricted_stock_deferred': 'NaN',
'salary': 274975,
'salary+bonus': 874975.0,
'salary_bonus_ratio': 2.1820165469588146,
'shared_receipt_with_poi': 874,
'to_messages': 873,
'total_payments': 1272284,
'total_stock_value': 778546})]
In [84]:
import sys
sys.path.append("./tools/")
from feature_format import featureFormat, targetFeatureSplit
import numpy as np
features_all = [
'poi',
'salary',
'to_messages',
'deferral_payments',
'total_payments',
'exercised_stock_options',
'bonus',
'restricted_stock',
'shared_receipt_with_poi',
'restricted_stock_deferred',
'total_stock_value',
'expenses',
'loan_advances',
'from_messages',
'other',
'from_this_person_to_poi',
'director_fees',
'deferred_income',
'long_term_incentive',
# 'email_address',
'from_poi_to_this_person',
'salary_bonus_ratio',
]
features_list=features_all
data = featureFormat(data_dict, features_list, sort_keys = True)
labels, features = targetFeatureSplit(data)
In [ ]:
In [85]:
from sklearn.feature_selection import SelectKBest, f_classif
# Perform feature selection
selector = SelectKBest(f_classif, k=5)
selector.fit(features, labels)
# Get the raw p-values for each feature, and transform from p-values into scores
scores = -np.log10(selector.pvalues_)
scores= selector.scores_
predictors = features_list[1:]
sort_indices = np.argsort(scores)[::-1]
# Plot the scores. See how "Pclass", "Sex", "Title", and "Fare" are the best?
X=np.arange(len(predictors))
Y=scores[sort_indices]
X_labels = map(lambda x: x.replace("_"," ").title(),np.array(predictors)[sort_indices])
ax = plt.subplot(111)
ax.bar(X, Y,edgecolor='white',facecolor='#9999ff')
plt.xticks(X+0.4, X_labels, rotation='vertical')
for x,y in zip(X,Y):
ax.text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom')
pass
plt.tick_params(bottom='off',top='off', right='off', left='off')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
In [86]:
zip(np.array(predictors)[sort_indices],scores[sort_indices])
Out[86]:
[('exercised_stock_options', 25.380105299760199),
('total_stock_value', 24.752523020258508),
('bonus', 21.327890413979102),
('salary', 18.861795316466416),
('salary_bonus_ratio', 12.278007938540965),
('deferred_income', 11.732698076065354),
('long_term_incentive', 10.222904205832778),
('restricted_stock', 9.4807432034789336),
('total_payments', 8.9678193476776205),
('shared_receipt_with_poi', 8.9038215571655712),
('loan_advances', 7.3014066515360359),
('expenses', 6.3746144901977475),
('from_poi_to_this_person', 5.4466874833253529),
('other', 4.2635766381444693),
('from_this_person_to_poi', 2.470521222656084),
('director_fees', 2.0893098994318806),
('to_messages', 1.7516942790340737),
('deferral_payments', 0.20970584227026345),
('from_messages', 0.1587702392129193),
('restricted_stock_deferred', 0.064477028038728595)]
In [87]:
list(np.array(predictors)[sort_indices])
Out[87]:
['exercised_stock_options',
'total_stock_value',
'bonus',
'salary',
'salary_bonus_ratio',
'deferred_income',
'long_term_incentive',
'restricted_stock',
'total_payments',
'shared_receipt_with_poi',
'loan_advances',
'expenses',
'from_poi_to_this_person',
'other',
'from_this_person_to_poi',
'director_fees',
'to_messages',
'deferral_payments',
'from_messages',
'restricted_stock_deferred']
In [ ]:
Content source: luiscruz/udacity_data_analyst
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