Titanic

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pclass	survived	name	sex	age	sibsp	parch	ticket	fare	cabin	embarked	boat	body	home.dest
1	1	Allen, Miss. Elisabeth Walton	female	29.0	0	0	24160	211.3375	B5	S	2		St Louis, MO
1	1	Allison, Master. Hudson Trevor	male	0.9167	1	2	113781	151.55	C22 C26	S	11		Montreal, PQ / Chesterville, ON
1	0	Allison, Miss. Helen Loraine	female	2.0	1	2	113781	151.55	C22 C26	S			Montreal, PQ / Chesterville, ON
1	0	Allison, Mr. Hudson Joshua Creighton	male	30.0	1	2	113781	151.55	C22 C26	S		135.0	Montreal, PQ / Chesterville, ON
1	0	Allison, Mrs. Hudson J C (Bessie Waldo Daniels)	female	25.0	1	2	113781	151.55	C22 C26	S			Montreal, PQ / Chesterville, ON
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
3	0	Zabour, Miss. Hileni	female	14.5	1	0	2665	14.4542		C		328.0
3	0	Zabour, Miss. Thamine	female		1	0	2665	14.4542		C
3	0	Zakarian, Mr. Mapriededer	male	26.5	0	0	2656	7.225		C		304.0
3	0	Zakarian, Mr. Ortin	male	27.0	0	0	2670	7.225		C
3	0	Zimmerman, Mr. Leo	male	29.0	0	0	315082	7.875		S

1309 rows ✕ 14 columns.

`pclass`

Int64DType

Null values: 0 (0.0%)
Mean ± Std: 2.29 ± 0.838
Median ± IQR: 3 ± 1
Min ; Max: 1 ; 3

`survived`

CategoricalDtype

Null values: 0 (0.0%)
Unique values: 2 (0.2%)

Most frequent values

List:

['0', '1']

`name`

ObjectDType

Null values: 0 (0.0%)
Unique values: 1307 (99.8%)

Most frequent values

Kelly, Mr. James

Connolly, Miss. Kate

Brandeis, Mr. Emil

Andrews, Miss. Kornelia Theodosia

Willey, Mr. Edward

Astor, Mrs. John Jacob (Madeleine Talmadge Force)

Zimmerman, Mr. Leo

Allen, Miss. Elisabeth Walton

Allison, Master. Hudson Trevor

Allison, Miss. Helen Loraine

List:

['Kelly, Mr. James', 'Connolly, Miss. Kate', 'Brandeis, Mr. Emil', 'Andrews, Miss. Kornelia Theodosia', 'Willey, Mr. Edward', 'Astor, Mrs. John Jacob (Madeleine Talmadge Force)', 'Zimmerman, Mr. Leo', 'Allen, Miss. Elisabeth Walton', 'Allison, Master. Hudson Trevor', 'Allison, Miss. Helen Loraine']

`sex`

CategoricalDtype

Null values: 0 (0.0%)
Unique values: 2 (0.2%)

Most frequent values

male

female

List:

['male', 'female']

`age`

Float64DType

Null values: 263 (20.1%)
Mean ± Std: 29.9 ± 14.4
Median ± IQR: 28.0 ± 18.0
Min ; Max: 0.167 ; 80.0

`sibsp`

Int64DType

Null values: 0 (0.0%)
Mean ± Std: 0.499 ± 1.04
Median ± IQR: 0 ± 1
Min ; Max: 0 ; 8

`parch`

Int64DType

Null values: 0 (0.0%)
Mean ± Std: 0.385 ± 0.866
Median ± IQR: 0 ± 0
Min ; Max: 0 ; 9

`ticket`

ObjectDType

Null values: 0 (0.0%)
Unique values: 929 (71.0%)

Most frequent values

CA. 2343

CA 2144

S.O.C. 14879

PC 17608

List:

['CA. 2343', '1601', 'CA 2144', '347082', 'S.O.C. 14879', 'PC 17608', '3101295', '347077', '347088', '19950']

`fare`

Float64DType

Null values: 1 (< 0.1%)
Mean ± Std: 33.3 ± 51.8
Median ± IQR: 14.5 ± 23.4
Min ; Max: 0.00 ; 512.

`cabin`

ObjectDType

Null values: 1014 (77.5%)
Unique values: 186 (14.2%)

Most frequent values

C23 C25 C27

B57 B59 B63 B66

G6

F4

F33

C78

F2

C22 C26

B96 B98

List:

['C23 C25 C27', 'B57 B59 B63 B66', 'G6', 'D', 'F4', 'F33', 'C78', 'F2', 'C22 C26', 'B96 B98']

`embarked`

CategoricalDtype

Null values: 2 (0.2%)
Unique values: 3 (0.2%)

Most frequent values

List:

['S', 'C', 'Q']

`boat`

ObjectDType

Null values: 823 (62.9%)
Unique values: 27 (2.1%)

Most frequent values

List:

['13', 'C', '15', '14', '4', '10', '5', '3', '9', '11']

`body`

Float64DType

Null values: 1188 (90.8%)
Mean ± Std: 161. ± 97.7
Median ± IQR: 155. ± 184.
Min ; Max: 1.00 ; 328.

`home.dest`

ObjectDType

Null values: 564 (43.1%)
Unique values: 369 (28.2%)

Most frequent values

New York, NY

London

Montreal, PQ

Paris, France

Cornwall / Akron, OH

Wiltshire, England Niagara Falls, NY

Winnipeg, MB

Philadelphia, PA

Brooklyn, NY

Belfast

List:

['New York, NY', 'London', 'Montreal, PQ', 'Paris, France', 'Cornwall / Akron, OH', 'Wiltshire, England Niagara Falls, NY', 'Winnipeg, MB', 'Philadelphia, PA', 'Brooklyn, NY', 'Belfast']

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The table below shows the strength of association between the most similar columns in the dataframe. Cramér's V statistic is a number between 0 and 1. When it is close to 1 the columns are strongly associated — they contain similar information. In this case, one of them may be redundant and for some models (such as linear models) it might be beneficial to remove it.

Column 1	Column 2	Cramér's V
survived	boat	0.948
sibsp	ticket	0.619
pclass	cabin	0.599
pclass	home.dest	0.537
survived	sex	0.529
sex	boat	0.506
pclass	fare	0.446
pclass	boat	0.422
fare	cabin	0.409
sibsp	home.dest	0.395
parch	ticket	0.368
pclass	age	0.343
ticket	home.dest	0.341
cabin	home.dest	0.327
pclass	survived	0.313
survived	cabin	0.309
ticket	fare	0.308
ticket	cabin	0.284
pclass	embarked	0.284
fare	boat	0.274