Report SWEETVIZ and Pandas-Profile

Dataset statistics

Number of variables	12
Number of observations	891
Missing cells	866
Missing cells (%)	8.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	83.7 KiB
Average record size in memory	96.1 B

Variable types

Numeric	5
Categorical	7

Alerts

`Name` has a high cardinality: 891 distinct values	High cardinality
`Ticket` has a high cardinality: 681 distinct values	High cardinality
`Cabin` has a high cardinality: 147 distinct values	High cardinality
`Pclass` is highly correlated with `Fare` and 1 other fields	High correlation
`Fare` is highly correlated with `Pclass`	High correlation
`Survived` is highly correlated with `Sex`	High correlation
`Sex` is highly correlated with `Survived`	High correlation
`SibSp` is highly correlated with `Parch`	High correlation
`Parch` is highly correlated with `SibSp`	High correlation
`Embarked` is highly correlated with `Pclass`	High correlation
`Age` has 177 (19.9%) missing values	Missing
`Cabin` has 687 (77.1%) missing values	Missing
`PassengerId` is uniformly distributed	Uniform
`Name` is uniformly distributed	Uniform
`Ticket` is uniformly distributed	Uniform
`Cabin` is uniformly distributed	Uniform
`PassengerId` has unique values	Unique
`Name` has unique values	Unique
`SibSp` has 608 (68.2%) zeros	Zeros
`Parch` has 678 (76.1%) zeros	Zeros
`Fare` has 15 (1.7%) zeros	Zeros

Reproduction

Analysis started	2022-09-21 19:26:54.013630
Analysis finished	2022-09-21 19:26:56.385991
Duration	2.37 seconds
Software version	pandas-profiling v3.3.0
Download configuration	config.json

PassengerId
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	891
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	446

Minimum	1
Maximum	891
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	1
5-th percentile	45.5
Q1	223.5
median	446
Q3	668.5
95-th percentile	846.5
Maximum	891
Range	890
Interquartile range (IQR)	445

Descriptive statistics

Standard deviation	257.353842
Coefficient of variation (CV)	0.5770265516
Kurtosis	-1.2
Mean	446
Median Absolute Deviation (MAD)	223
Skewness	0
Sum	397386
Variance	66231
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.1%
599	1	0.1%
588	1	0.1%
589	1	0.1%
590	1	0.1%
591	1	0.1%
592	1	0.1%
593	1	0.1%
594	1	0.1%
595	1	0.1%
Other values (881)	881	98.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%
10	1	0.1%

Value	Count	Frequency (%)
891	1	0.1%
890	1	0.1%
889	1	0.1%
888	1	0.1%
887	1	0.1%
886	1	0.1%
885	1	0.1%
884	1	0.1%
883	1	0.1%
882	1	0.1%

Survived
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

0	549
1	342

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	891
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Most occurring characters

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	891	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	891	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	891	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	549	61.6%
1	342	38.4%

Pclass
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

3	491
1	216
2	184

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	891
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	1
3rd row	3
4th row	1
5th row	3

Common Values

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Most occurring characters

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	891	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	891	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	891	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	491	55.1%
1	216	24.2%
2	184	20.7%

Name
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	891
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

Braund, Mr. Owen Harris	1
Boulos, Mr. Hanna	1
Frolicher-Stehli, Mr. Maxmillian	1
Gilinski, Mr. Eliezer	1
Murdlin, Mr. Joseph	1
Other values (886)	886

Length

Max length	82
Median length	52
Mean length	26.96520763
Min length	12

Characters and Unicode

Total characters	24026
Distinct characters	60
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	891 ?
Unique (%)	100.0%

Sample

1st row	Braund, Mr. Owen Harris
2nd row	Cumings, Mrs. John Bradley (Florence Briggs Thayer)
3rd row	Heikkinen, Miss. Laina
4th row	Futrelle, Mrs. Jacques Heath (Lily May Peel)
5th row	Allen, Mr. William Henry

Common Values

Value	Count	Frequency (%)
Braund, Mr. Owen Harris	1	0.1%
Boulos, Mr. Hanna	1	0.1%
Frolicher-Stehli, Mr. Maxmillian	1	0.1%
Gilinski, Mr. Eliezer	1	0.1%
Murdlin, Mr. Joseph	1	0.1%
Rintamaki, Mr. Matti	1	0.1%
Stephenson, Mrs. Walter Bertram (Martha Eustis)	1	0.1%
Elsbury, Mr. William James	1	0.1%
Bourke, Miss. Mary	1	0.1%
Chapman, Mr. John Henry	1	0.1%
Other values (881)	881	98.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mr	521	14.4%
miss	182	5.0%
mrs	129	3.6%
william	64	1.8%
john	44	1.2%
master	40	1.1%
henry	35	1.0%
george	24	0.7%
james	24	0.7%
charles	23	0.6%
Other values (1515)	2538	70.0%

Most occurring characters

Value	Count	Frequency (%)
	2735	11.4%
r	1958	8.1%
e	1703	7.1%
a	1657	6.9%
i	1325	5.5%
n	1304	5.4%
s	1297	5.4%
M	1128	4.7%
l	1067	4.4%
o	1008	4.2%
Other values (50)	8844	36.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	15446	64.3%
Uppercase Letter	3645	15.2%
Space Separator	2735	11.4%
Other Punctuation	1899	7.9%
Close Punctuation	144	0.6%
Open Punctuation	144	0.6%
Dash Punctuation	13	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	1958	12.7%
e	1703	11.0%
a	1657	10.7%
i	1325	8.6%
n	1304	8.4%
s	1297	8.4%
l	1067	6.9%
o	1008	6.5%
t	667	4.3%
h	517	3.3%
Other values (16)	2943	19.1%

Uppercase Letter

Value	Count	Frequency (%)
M	1128	30.9%
A	250	6.9%
J	215	5.9%
H	203	5.6%
S	180	4.9%
C	172	4.7%
E	166	4.6%
W	143	3.9%
B	140	3.8%
L	129	3.5%
Other values (15)	919	25.2%

Other Punctuation

Value	Count	Frequency (%)
.	892	47.0%
,	891	46.9%
"	106	5.6%
'	9	0.5%
/	1	0.1%

Space Separator

Value	Count	Frequency (%)
	2735	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	144	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	144	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	13	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	19091	79.5%
Common	4935	20.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	1958	10.3%
e	1703	8.9%
a	1657	8.7%
i	1325	6.9%
n	1304	6.8%
s	1297	6.8%
M	1128	5.9%
l	1067	5.6%
o	1008	5.3%
t	667	3.5%
Other values (41)	5977	31.3%

Common

Value	Count	Frequency (%)
	2735	55.4%
.	892	18.1%
,	891	18.1%
)	144	2.9%
(	144	2.9%
"	106	2.1%
-	13	0.3%
'	9	0.2%
/	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24026	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	2735	11.4%
r	1958	8.1%
e	1703	7.1%
a	1657	6.9%
i	1325	5.5%
n	1304	5.4%
s	1297	5.4%
M	1128	4.7%
l	1067	4.4%
o	1008	4.2%
Other values (50)	8844	36.8%

Sex
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

male	577
female	314

Length

Max length	6
Median length	4
Mean length	4.704826038
Min length	4

Characters and Unicode

Total characters	4192
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	male
2nd row	female
3rd row	female
4th row	female
5th row	male

Common Values

Value	Count	Frequency (%)
male	577	64.8%
female	314	35.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
male	577	64.8%
female	314	35.2%

Most occurring characters

Value	Count	Frequency (%)
e	1205	28.7%
m	891	21.3%
a	891	21.3%
l	891	21.3%
f	314	7.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4192	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1205	28.7%
m	891	21.3%
a	891	21.3%
l	891	21.3%
f	314	7.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4192	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1205	28.7%
m	891	21.3%
a	891	21.3%
l	891	21.3%
f	314	7.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4192	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1205	28.7%
m	891	21.3%
a	891	21.3%
l	891	21.3%
f	314	7.5%

Age
Real number (ℝ_≥0)

MISSING

Distinct	88
Distinct (%)	12.3%
Missing	177
Missing (%)	19.9%
Infinite	0
Infinite (%)	0.0%
Mean	29.69911765

Minimum	0.42
Maximum	80
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0.42
5-th percentile	4
Q1	20.125
median	28
Q3	38
95-th percentile	56
Maximum	80
Range	79.58
Interquartile range (IQR)	17.875

Descriptive statistics

Standard deviation	14.52649733
Coefficient of variation (CV)	0.4891221855
Kurtosis	0.1782741536
Mean	29.69911765
Median Absolute Deviation (MAD)	9
Skewness	0.3891077823
Sum	21205.17
Variance	211.0191247
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
24	30	3.4%
22	27	3.0%
18	26	2.9%
28	25	2.8%
30	25	2.8%
19	25	2.8%
21	24	2.7%
25	23	2.6%
36	22	2.5%
29	20	2.2%
Other values (78)	467	52.4%
(Missing)	177	19.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.42	1	0.1%
0.67	1	0.1%
0.75	2	0.2%
0.83	2	0.2%
0.92	1	0.1%
1	7	0.8%
2	10	1.1%
3	6	0.7%
4	10	1.1%
5	4	0.4%

Value	Count	Frequency (%)
80	1	0.1%
74	1	0.1%
71	2	0.2%
70.5	1	0.1%
70	2	0.2%
66	1	0.1%
65	3	0.3%
64	2	0.2%
63	2	0.2%
62	4	0.4%

SibSp
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.5230078563

Minimum	0
Maximum	8
Zeros	608
Zeros (%)	68.2%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	3
Maximum	8
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.102743432
Coefficient of variation (CV)	2.108464374
Kurtosis	17.88041973
Mean	0.5230078563
Median Absolute Deviation (MAD)	0
Skewness	3.695351727
Sum	466
Variance	1.216043077
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	608	68.2%
1	209	23.5%
2	28	3.1%
4	18	2.0%
3	16	1.8%
8	7	0.8%
5	5	0.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	608	68.2%
1	209	23.5%
2	28	3.1%
3	16	1.8%
4	18	2.0%
5	5	0.6%
8	7	0.8%

Value	Count	Frequency (%)
8	7	0.8%
5	5	0.6%
4	18	2.0%
3	16	1.8%
2	28	3.1%
1	209	23.5%
0	608	68.2%

Parch
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3815937149

Minimum	0
Maximum	6
Zeros	678
Zeros (%)	76.1%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	6
Range	6
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8060572211
Coefficient of variation (CV)	2.112344071
Kurtosis	9.778125179
Mean	0.3815937149
Median Absolute Deviation (MAD)	0
Skewness	2.749117047
Sum	340
Variance	0.6497282437
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	678	76.1%
1	118	13.2%
2	80	9.0%
5	5	0.6%
3	5	0.6%
4	4	0.4%
6	1	0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	678	76.1%
1	118	13.2%
2	80	9.0%
3	5	0.6%
4	4	0.4%
5	5	0.6%
6	1	0.1%

Value	Count	Frequency (%)
6	1	0.1%
5	5	0.6%
4	4	0.4%
3	5	0.6%
2	80	9.0%
1	118	13.2%
0	678	76.1%

Ticket
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	681
Distinct (%)	76.4%
Missing	0
Missing (%)	0.0%
Memory size	7.1 KiB

347082	7
CA. 2343	7
1601	7
3101295	6
CA 2144	6
Other values (676)	858

Length

Max length	18
Median length	17
Mean length	6.750841751
Min length	3

Characters and Unicode

Total characters	6015
Distinct characters	35
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	547 ?
Unique (%)	61.4%

Sample

1st row	A/5 21171
2nd row	PC 17599
3rd row	STON/O2. 3101282
4th row	113803
5th row	373450

Common Values

Value	Count	Frequency (%)
347082	7	0.8%
CA. 2343	7	0.8%
1601	7	0.8%
3101295	6	0.7%
CA 2144	6	0.7%
347088	6	0.7%
S.O.C. 14879	5	0.6%
382652	5	0.6%
LINE	4	0.4%
PC 17757	4	0.4%
Other values (671)	834	93.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
pc	60	5.3%
c.a	27	2.4%
a/5	17	1.5%
ca	14	1.2%
ston/o	12	1.1%
2	12	1.1%
sc/paris	9	0.8%
w./c	9	0.8%
soton/o.q	8	0.7%
347082	7	0.6%
Other values (709)	955	84.5%

Most occurring characters

Value	Count	Frequency (%)
3	746	12.4%
1	689	11.5%
2	594	9.9%
7	490	8.1%
4	464	7.7%
6	422	7.0%
0	406	6.7%
5	387	6.4%
9	328	5.5%
8	282	4.7%
Other values (25)	1207	20.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4808	79.9%
Uppercase Letter	652	10.8%
Other Punctuation	295	4.9%
Space Separator	239	4.0%
Lowercase Letter	21	0.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
C	151	23.2%
O	100	15.3%
P	98	15.0%
A	82	12.6%
S	74	11.3%
N	40	6.1%
T	36	5.5%
W	16	2.5%
Q	15	2.3%
I	11	1.7%
Other values (6)	29	4.4%

Decimal Number

Value	Count	Frequency (%)
3	746	15.5%
1	689	14.3%
2	594	12.4%
7	490	10.2%
4	464	9.7%
6	422	8.8%
0	406	8.4%
5	387	8.0%
9	328	6.8%
8	282	5.9%

Lowercase Letter

Value	Count	Frequency (%)
a	6	28.6%
s	5	23.8%
r	4	19.0%
i	4	19.0%
l	1	4.8%
e	1	4.8%

Other Punctuation

Value	Count	Frequency (%)
.	197	66.8%
/	98	33.2%

Space Separator

Value	Count	Frequency (%)
	239	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5342	88.8%
Latin	673	11.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
C	151	22.4%
O	100	14.9%
P	98	14.6%
A	82	12.2%
S	74	11.0%
N	40	5.9%
T	36	5.3%
W	16	2.4%
Q	15	2.2%
I	11	1.6%
Other values (12)	50	7.4%

Common

Value	Count	Frequency (%)
3	746	14.0%
1	689	12.9%
2	594	11.1%
7	490	9.2%
4	464	8.7%
6	422	7.9%
0	406	7.6%
5	387	7.2%
9	328	6.1%
8	282	5.3%
Other values (3)	534	10.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6015	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	746	12.4%
1	689	11.5%
2	594	9.9%
7	490	8.1%
4	464	7.7%
6	422	7.0%
0	406	6.7%
5	387	6.4%
9	328	5.5%
8	282	4.7%
Other values (25)	1207	20.1%

Fare
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	248
Distinct (%)	27.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	32.20420797

Minimum	0
Maximum	512.3292
Zeros	15
Zeros (%)	1.7%
Negative	0
Negative (%)	0.0%
Memory size	7.1 KiB

Quantile statistics

Minimum	0
5-th percentile	7.225
Q1	7.9104
median	14.4542
Q3	31
95-th percentile	112.07915
Maximum	512.3292
Range	512.3292
Interquartile range (IQR)	23.0896

Descriptive statistics

Standard deviation	49.6934286
Coefficient of variation (CV)	1.543072528
Kurtosis	33.39814088
Mean	32.20420797
Median Absolute Deviation (MAD)	6.9042
Skewness	4.78731652
Sum	28693.9493
Variance	2469.436846
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8.05	43	4.8%
13	42	4.7%
7.8958	38	4.3%
7.75	34	3.8%
26	31	3.5%
10.5	24	2.7%
7.925	18	2.0%
7.775	16	1.8%
7.2292	15	1.7%
0	15	1.7%
Other values (238)	615	69.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	15	1.7%
4.0125	1	0.1%
5	1	0.1%
6.2375	1	0.1%
6.4375	1	0.1%
6.45	1	0.1%
6.4958	2	0.2%
6.75	2	0.2%
6.8583	1	0.1%
6.95	1	0.1%

Value	Count	Frequency (%)
512.3292	3	0.3%
263	4	0.4%
262.375	2	0.2%
247.5208	2	0.2%
227.525	4	0.4%
221.7792	1	0.1%
211.5	1	0.1%
211.3375	3	0.3%
164.8667	2	0.2%
153.4625	3	0.3%

Cabin
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	147
Distinct (%)	72.1%
Missing	687
Missing (%)	77.1%
Memory size	7.1 KiB

C23 C25 C27	4
G6	4
B96 B98	4
C22 C26	3
D	3
Other values (142)	186

Length

Max length	15
Median length	3
Mean length	3.588235294
Min length	1

Characters and Unicode

Total characters	732
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	101 ?
Unique (%)	49.5%

Sample

1st row	C85
2nd row	C123
3rd row	E46
4th row	G6
5th row	C103

Common Values

Value	Count	Frequency (%)
C23 C25 C27	4	0.4%
G6	4	0.4%
B96 B98	4	0.4%
C22 C26	3	0.3%
D	3	0.3%
F33	3	0.3%
E101	3	0.3%
F2	3	0.3%
B20	2	0.2%
E67	2	0.2%
Other values (137)	173	19.4%
(Missing)	687	77.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
c23	4	1.7%
c27	4	1.7%
g6	4	1.7%
b96	4	1.7%
b98	4	1.7%
f	4	1.7%
c25	4	1.7%
f33	3	1.3%
e101	3	1.3%
f2	3	1.3%
Other values (151)	201	84.5%

Most occurring characters

Value	Count	Frequency (%)
2	72	9.8%
C	71	9.7%
B	64	8.7%
1	61	8.3%
3	59	8.1%
6	51	7.0%
5	45	6.1%
4	37	5.1%
8	37	5.1%
	34	4.6%
Other values (9)	201	27.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	460	62.8%
Uppercase Letter	238	32.5%
Space Separator	34	4.6%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	72	15.7%
1	61	13.3%
3	59	12.8%
6	51	11.1%
5	45	9.8%
4	37	8.0%
8	37	8.0%
7	34	7.4%
9	33	7.2%
0	31	6.7%

Uppercase Letter

Value	Count	Frequency (%)
C	71	29.8%
B	64	26.9%
D	34	14.3%
E	33	13.9%
A	15	6.3%
F	13	5.5%
G	7	2.9%
T	1	0.4%

Space Separator

Value	Count	Frequency (%)
	34	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	494	67.5%
Latin	238	32.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	72	14.6%
1	61	12.3%
3	59	11.9%
6	51	10.3%
5	45	9.1%
4	37	7.5%
8	37	7.5%
	34	6.9%
7	34	6.9%
9	33	6.7%

Latin

Value	Count	Frequency (%)
C	71	29.8%
B	64	26.9%
D	34	14.3%
E	33	13.9%
A	15	6.3%
F	13	5.5%
G	7	2.9%
T	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	732	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	72	9.8%
C	71	9.7%
B	64	8.7%
1	61	8.3%
3	59	8.1%
6	51	7.0%
5	45	6.1%
4	37	5.1%
8	37	5.1%
	34	4.6%
Other values (9)	201	27.5%

Embarked
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	2
Missing (%)	0.2%
Memory size	7.1 KiB

S	644
C	168
Q	77

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	889
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	S
2nd row	C
3rd row	S
4th row	S
5th row	S

Common Values

Value	Count	Frequency (%)
S	644	72.3%
C	168	18.9%
Q	77	8.6%
(Missing)	2	0.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
s	644	72.4%
c	168	18.9%
q	77	8.7%

Most occurring characters

Value	Count	Frequency (%)
S	644	72.4%
C	168	18.9%
Q	77	8.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	889	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	644	72.4%
C	168	18.9%
Q	77	8.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	889	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	644	72.4%
C	168	18.9%
Q	77	8.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	889	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
S	644	72.4%
C	168	18.9%
Q	77	8.7%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	0	A/5 21171	7.2500	NaN	S
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38.0	1	0	PC 17599	71.2833	C85	C
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	0	STON/O2. 3101282	7.9250	NaN	S
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	0	113803	53.1000	C123	S
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	0	373450	8.0500	NaN	S
5	6	0	3	Moran, Mr. James	male	NaN	0	0	330877	8.4583	NaN	Q
6	7	0	1	McCarthy, Mr. Timothy J	male	54.0	0	0	17463	51.8625	E46	S
7	8	0	3	Palsson, Master. Gosta Leonard	male	2.0	3	1	349909	21.0750	NaN	S
8	9	1	3	Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)	female	27.0	0	2	347742	11.1333	NaN	S
9	10	1	2	Nasser, Mrs. Nicholas (Adele Achem)	female	14.0	1	0	237736	30.0708	NaN	C

Last rows

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
881	882	0	3	Markun, Mr. Johann	male	33.0	0	0	349257	7.8958	NaN	S
882	883	0	3	Dahlberg, Miss. Gerda Ulrika	female	22.0	0	0	7552	10.5167	NaN	S
883	884	0	2	Banfield, Mr. Frederick James	male	28.0	0	0	C.A./SOTON 34068	10.5000	NaN	S
884	885	0	3	Sutehall, Mr. Henry Jr	male	25.0	0	0	SOTON/OQ 392076	7.0500	NaN	S
885	886	0	3	Rice, Mrs. William (Margaret Norton)	female	39.0	0	5	382652	29.1250	NaN	Q
886	887	0	2	Montvila, Rev. Juozas	male	27.0	0	0	211536	13.0000	NaN	S
887	888	1	1	Graham, Miss. Margaret Edith	female	19.0	0	0	112053	30.0000	B42	S
888	889	0	3	Johnston, Miss. Catherine Helen "Carrie"	female	NaN	1	2	W./C. 6607	23.4500	NaN	S
889	890	1	1	Behr, Mr. Karl Howell	male	26.0	0	0	111369	30.0000	C148	C
890	891	0	3	Dooley, Mr. Patrick	male	32.0	0	0	370376	7.7500	NaN	Q

Report SWEETVIZ and Pandas-Profile

Pandas Profiling

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Close Punctuation

Open Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Lowercase Letter

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values