passenger_class
int8
1
3
is_male
bool
2 classes
age
float64
-1
80
sibsp
float64
0
8
parch
float64
0
6
ticket
stringlengths
3
20
fare
float64
0
512
cabin
stringlengths
1
17
embarked
stringclasses
4 values
has_survived
class label
2 classes
3
true
22
1
0
'A/5 21171'
7.25
''
S
0no
1
false
38
1
0
'PC 17599'
71.2833
C85
C
1yes
3
false
26
0
0
'STON/O2. 3101282'
7.925
''
S
1yes
1
false
35
1
0
113803
53.1
C123
S
1yes
3
true
35
0
0
373450
8.05
''
S
0no
3
true
-1
0
0
330877
8.4583
''
Q
0no
1
true
54
0
0
17463
51.8625
E46
S
0no
3
true
2
3
1
349909
21.075
''
S
0no
3
false
27
0
2
347742
11.1333
''
S
1yes
2
false
14
1
0
237736
30.0708
''
C
1yes
3
false
4
1
1
'PP 9549'
16.7
G6
S
1yes
1
false
58
0
0
113783
26.55
C103
S
1yes
3
true
20
0
0
'A/5. 2151'
8.05
''
S
0no
3
true
39
1
5
347082
31.275
''
S
0no
3
false
14
0
0
350406
7.8542
''
S
0no
2
false
55
0
0
248706
16
''
S
1yes
3
true
2
4
1
382652
29.125
''
Q
0no
2
true
-1
0
0
244373
13
''
S
1yes
3
false
31
1
0
345763
18
''
S
0no
3
false
-1
0
0
2649
7.225
''
C
1yes
2
true
35
0
0
239865
26
''
S
0no
2
true
34
0
0
248698
13
D56
S
1yes
3
false
15
0
0
330923
8.0292
''
Q
1yes
1
true
28
0
0
113788
35.5
A6
S
1yes
3
false
8
3
1
349909
21.075
''
S
0no
3
false
38
1
5
347077
31.3875
''
S
1yes
3
true
-1
0
0
2631
7.225
''
C
0no
1
true
19
3
2
19950
263
'C23 C25 C27'
S
0no
3
false
-1
0
0
330959
7.8792
''
Q
1yes
3
true
-1
0
0
349216
7.8958
''
S
0no
1
true
40
0
0
'PC 17601'
27.7208
''
C
0no
1
false
-1
1
0
'PC 17569'
146.5208
B78
C
1yes
3
false
-1
0
0
335677
7.75
''
Q
1yes
2
true
66
0
0
'C.A. 24579'
10.5
''
S
0no
1
true
28
1
0
'PC 17604'
82.1708
''
C
0no
1
true
42
1
0
113789
52
''
S
0no
3
true
-1
0
0
2677
7.2292
''
C
1yes
3
true
21
0
0
'A./5. 2152'
8.05
''
S
0no
3
false
18
2
0
345764
18
''
S
0no
3
false
14
1
0
2651
11.2417
''
C
1yes
3
false
40
1
0
7546
9.475
''
S
0no
2
false
27
1
0
11668
21
''
S
0no
3
true
-1
0
0
349253
7.8958
''
C
0no
2
false
3
1
2
'SC/Paris 2123'
41.5792
''
C
1yes
3
false
19
0
0
330958
7.8792
''
Q
1yes
3
true
-1
0
0
'S.C./A.4. 23567'
8.05
''
S
0no
3
true
-1
1
0
370371
15.5
''
Q
0no
3
false
-1
0
0
14311
7.75
''
Q
1yes
3
true
-1
2
0
2662
21.6792
''
C
0no
3
false
18
1
0
349237
17.8
''
S
0no
3
true
7
4
1
3101295
39.6875
''
S
0no
3
true
21
0
0
'A/4. 39886'
7.8
''
S
0no
1
false
49
1
0
'PC 17572'
76.7292
D33
C
1yes
2
false
29
1
0
2926
26
''
S
1yes
1
true
65
0
1
113509
61.9792
B30
C
0no
1
true
-1
0
0
19947
35.5
C52
S
1yes
2
false
21
0
0
'C.A. 31026'
10.5
''
S
1yes
3
true
28.5
0
0
2697
7.2292
''
C
0no
2
false
5
1
2
'C.A. 34651'
27.75
''
S
1yes
3
true
11
5
2
'CA 2144'
46.9
''
S
0no
3
true
22
0
0
2669
7.2292
''
C
0no
1
false
38
0
0
113572
80
B28
''
1yes
1
true
45
1
0
36973
83.475
C83
S
0no
3
true
4
3
2
347088
27.9
''
S
0no
1
true
-1
0
0
'PC 17605'
27.7208
''
C
0no
3
true
-1
1
1
2661
15.2458
''
C
1yes
2
false
29
0
0
'C.A. 29395'
10.5
F33
S
1yes
3
true
19
0
0
'S.P. 3464'
8.1583
''
S
0no
3
false
17
4
2
3101281
7.925
''
S
1yes
3
true
26
2
0
315151
8.6625
''
S
0no
2
true
32
0
0
'C.A. 33111'
10.5
''
S
0no
3
false
16
5
2
'CA 2144'
46.9
''
S
0no
2
true
21
0
0
'S.O.C. 14879'
73.5
''
S
0no
3
true
26
1
0
2680
14.4542
''
C
0no
3
true
32
0
0
1601
56.4958
''
S
1yes
3
true
25
0
0
348123
7.65
'F G73'
S
0no
3
true
-1
0
0
349208
7.8958
''
S
0no
3
true
-1
0
0
374746
8.05
''
S
0no
2
true
0.83
0
2
248738
29
''
S
1yes
3
false
30
0
0
364516
12.475
''
S
1yes
3
true
22
0
0
345767
9
''
S
0no
3
true
29
0
0
345779
9.5
''
S
1yes
3
false
-1
0
0
330932
7.7875
''
Q
1yes
1
true
28
0
0
113059
47.1
''
S
0no
2
false
17
0
0
'SO/C 14885'
10.5
''
S
1yes
3
false
33
3
0
3101278
15.85
''
S
1yes
3
true
16
1
3
'W./C. 6608'
34.375
''
S
0no
3
true
-1
0
0
'SOTON/OQ 392086'
8.05
''
S
0no
1
false
23
3
2
19950
263
'C23 C25 C27'
S
1yes
3
true
24
0
0
343275
8.05
''
S
0no
3
true
29
0
0
343276
8.05
''
S
0no
3
true
20
0
0
347466
7.8542
''
S
0no
1
true
46
1
0
'W.E.P. 5734'
61.175
E31
S
0no
3
true
26
1
2
'C.A. 2315'
20.575
''
S
0no
3
true
59
0
0
364500
7.25
''
S
0no
3
true
-1
0
0
374910
8.05
''
S
0no
1
true
71
0
0
'PC 17754'
34.6542
A5
C
0no
1
true
23
0
1
'PC 17759'
63.3583
'D10 D12'
C
1yes
2
false
34
0
1
231919
23
''
S
1yes
2
true
34
1
0
244367
26
''
S
0no
YAML Metadata Error: "configs[0]" must be of type object

Titanic

The Titanic dataset from Kaggle.

Configurations and tasks

Configuration Task Description
survival Binary classification Has the passanger survived?

Usage

from datasets import load_dataset

dataset = load_dataset("mstz/titanic")["train"]
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