Overview

Dataset statistics

Number of variables4
Number of observations5663
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory182.6 KiB
Average record size in memory33.0 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description서울특별시 다중이용업소 중 고시원 정보에 대한 데이터로 상호명, 업종명, 법정동 주소 등을 포함하여 제공합니다.
Author서울특별시
URLhttps://www.data.go.kr/data/15030030/fileData.do

Alerts

업종 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:59:33.645625
Analysis finished2024-04-21 01:59:34.790767
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct5663
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2832
Minimum1
Maximum5663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-04-21T10:59:35.102945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile284.1
Q11416.5
median2832
Q34247.5
95-th percentile5379.9
Maximum5663
Range5662
Interquartile range (IQR)2831

Descriptive statistics

Standard deviation1634.9116
Coefficient of variation (CV)0.5772993
Kurtosis-1.2
Mean2832
Median Absolute Deviation (MAD)1416
Skewness0
Sum16037616
Variance2672936
MonotonicityStrictly increasing
2024-04-21T10:59:35.343662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3806 1
 
< 0.1%
3782 1
 
< 0.1%
3781 1
 
< 0.1%
3780 1
 
< 0.1%
3779 1
 
< 0.1%
3778 1
 
< 0.1%
3777 1
 
< 0.1%
3776 1
 
< 0.1%
3775 1
 
< 0.1%
Other values (5653) 5653
99.8%
ValueCountFrequency (%)
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%
ValueCountFrequency (%)
5663 1
< 0.1%
5662 1
< 0.1%
5661 1
< 0.1%
5660 1
< 0.1%
5659 1
< 0.1%
5658 1
< 0.1%
5657 1
< 0.1%
5656 1
< 0.1%
5655 1
< 0.1%
5654 1
< 0.1%

상호
Text

Distinct4198
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-04-21T10:59:36.390452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length5.9816352
Min length2

Characters and Unicode

Total characters33874
Distinct characters662
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3624 ?
Unique (%)64.0%

Sample

1st row운현고시원
2nd row주식회사 에스에스디에이
3rd row원룸텔경복궁굿스테이
4th row영하호
5th row대보빌딩(코쿤하우스)
ValueCountFrequency (%)
고시원 76
 
1.2%
원룸텔 60
 
1.0%
고시텔 35
 
0.6%
해피하우스 34
 
0.6%
코코리빙텔 30
 
0.5%
싱글하우스 29
 
0.5%
소호리빙텔 27
 
0.4%
레지던스 26
 
0.4%
심플하우스 26
 
0.4%
하우스 26
 
0.4%
Other values (4209) 5794
94.0%
2024-04-21T10:59:37.614625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2550
 
7.5%
원 2539
 
7.5%
고 2530
 
7.5%
스 1757
 
5.2%
텔 1594
 
4.7%
우 1021
 
3.0%
하 1019
 
3.0%
리 836
 
2.5%
빙 587
 
1.7%
빌 559
 
1.7%
Other values (652) 18882
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31047
91.7%
Uppercase Letter 598
 
1.8%
Space Separator 501
 
1.5%
Close Punctuation 471
 
1.4%
Open Punctuation 471
 
1.4%
Decimal Number 360
 
1.1%
Other Punctuation 229
 
0.7%
Lowercase Letter 119
 
0.4%
Dash Punctuation 53
 
0.2%
Math Symbol 14
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2550
 
8.2%
원 2539
 
8.2%
고 2530
 
8.1%
스 1757
 
5.7%
텔 1594
 
5.1%
우 1021
 
3.3%
하 1019
 
3.3%
리 836
 
2.7%
빙 587
 
1.9%
빌 559
 
1.8%
Other values (579) 16055
51.7%
Uppercase Letter
ValueCountFrequency (%)
S 56
 
9.4%
I 54
 
9.0%
O 40
 
6.7%
J 36
 
6.0%
A 34
 
5.7%
H 33
 
5.5%
M 29
 
4.8%
E 29
 
4.8%
B 28
 
4.7%
K 25
 
4.2%
Other values (15) 234
39.1%
Lowercase Letter
ValueCountFrequency (%)
e 39
32.8%
i 11
 
9.2%
l 10
 
8.4%
s 9
 
7.6%
a 9
 
7.6%
o 6
 
5.0%
u 6
 
5.0%
n 5
 
4.2%
r 4
 
3.4%
t 3
 
2.5%
Other values (12) 17
14.3%
Decimal Number
ValueCountFrequency (%)
2 111
30.8%
1 69
19.2%
3 64
17.8%
4 44
 
12.2%
5 25
 
6.9%
6 12
 
3.3%
0 11
 
3.1%
9 9
 
2.5%
8 8
 
2.2%
7 7
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 172
75.1%
, 38
 
16.6%
& 11
 
4.8%
/ 4
 
1.7%
@ 2
 
0.9%
! 2
 
0.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
70.0%
Ⅰ 2
 
20.0%
Ⅲ 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
~ 11
78.6%
+ 3
 
21.4%
Space Separator
ValueCountFrequency (%)
501
100.0%
Close Punctuation
ValueCountFrequency (%)
) 471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31044
91.6%
Common 2100
 
6.2%
Latin 727
 
2.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2550
 
8.2%
원 2539
 
8.2%
고 2530
 
8.1%
스 1757
 
5.7%
텔 1594
 
5.1%
우 1021
 
3.3%
하 1019
 
3.3%
리 836
 
2.7%
빙 587
 
1.9%
빌 559
 
1.8%
Other values (576) 16052
51.7%
Latin
ValueCountFrequency (%)
S 56
 
7.7%
I 54
 
7.4%
O 40
 
5.5%
e 39
 
5.4%
J 36
 
5.0%
A 34
 
4.7%
H 33
 
4.5%
M 29
 
4.0%
E 29
 
4.0%
B 28
 
3.9%
Other values (40) 349
48.0%
Common
ValueCountFrequency (%)
501
23.9%
) 471
22.4%
( 471
22.4%
. 172
 
8.2%
2 111
 
5.3%
1 69
 
3.3%
3 64
 
3.0%
- 53
 
2.5%
4 44
 
2.1%
, 38
 
1.8%
Other values (13) 106
 
5.0%
Han
ValueCountFrequency (%)
秀 1
33.3%
家 1
33.3%
舊 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31042
91.6%
ASCII 2817
 
8.3%
Number Forms 10
 
< 0.1%
CJK 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2550
 
8.2%
원 2539
 
8.2%
고 2530
 
8.2%
스 1757
 
5.7%
텔 1594
 
5.1%
우 1021
 
3.3%
하 1019
 
3.3%
리 836
 
2.7%
빙 587
 
1.9%
빌 559
 
1.8%
Other values (574) 16050
51.7%
ASCII
ValueCountFrequency (%)
501
17.8%
) 471
16.7%
( 471
16.7%
. 172
 
6.1%
2 111
 
3.9%
1 69
 
2.4%
3 64
 
2.3%
S 56
 
2.0%
I 54
 
1.9%
- 53
 
1.9%
Other values (60) 795
28.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
70.0%
Ⅰ 2
 
20.0%
Ⅲ 1
 
10.0%
CJK
ValueCountFrequency (%)
秀 1
33.3%
家 1
33.3%
舊 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㄴ 1
50.0%
ㄱ 1
50.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
고시원업
5663 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고시원업 5663
100.0%

Length

2024-04-21T10:59:37.834092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:59:37.990124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고시원업 5663
100.0%

법정동 주소
Text

Distinct5355
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-04-21T10:59:39.034861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length19.753841
Min length14

Characters and Unicode

Total characters111866
Distinct characters196
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5088 ?
Unique (%)89.8%

Sample

1st row서울특별시 종로구 경운동 1-9
2nd row서울특별시 종로구 명륜3가 61-8
3rd row서울특별시 종로구 필운동 278-5
4th row서울특별시 종로구 창신동 283
5th row서울특별시 종로구 이화동 36-2
ValueCountFrequency (%)
서울특별시 5663
25.0%
관악구 778
 
3.4%
신림동 582
 
2.6%
동작구 485
 
2.1%
강남구 415
 
1.8%
동대문구 339
 
1.5%
영등포구 323
 
1.4%
성북구 308
 
1.4%
서대문구 243
 
1.1%
송파구 242
 
1.1%
Other values (5269) 13274
58.6%
2024-04-21T10:59:40.363224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16989
15.2%
동 6771
 
6.1%
서 6427
 
5.7%
구 5981
 
5.3%
시 5680
 
5.1%
특 5663
 
5.1%
별 5663
 
5.1%
울 5663
 
5.1%
1 5394
 
4.8%
- 5240
 
4.7%
Other values (186) 42395
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63892
57.1%
Decimal Number 25745
23.0%
Space Separator 16989
 
15.2%
Dash Punctuation 5240
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6771
 
10.6%
서 6427
 
10.1%
구 5981
 
9.4%
시 5680
 
8.9%
특 5663
 
8.9%
별 5663
 
8.9%
울 5663
 
8.9%
강 890
 
1.4%
신 853
 
1.3%
관 814
 
1.3%
Other values (174) 19487
30.5%
Decimal Number
ValueCountFrequency (%)
1 5394
21.0%
2 3642
14.1%
3 3002
11.7%
4 2517
9.8%
5 2419
9.4%
6 2182
8.5%
0 1717
 
6.7%
7 1712
 
6.6%
9 1603
 
6.2%
8 1557
 
6.0%
Space Separator
ValueCountFrequency (%)
16989
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63892
57.1%
Common 47974
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6771
 
10.6%
서 6427
 
10.1%
구 5981
 
9.4%
시 5680
 
8.9%
특 5663
 
8.9%
별 5663
 
8.9%
울 5663
 
8.9%
강 890
 
1.4%
신 853
 
1.3%
관 814
 
1.3%
Other values (174) 19487
30.5%
Common
ValueCountFrequency (%)
16989
35.4%
1 5394
 
11.2%
- 5240
 
10.9%
2 3642
 
7.6%
3 3002
 
6.3%
4 2517
 
5.2%
5 2419
 
5.0%
6 2182
 
4.5%
0 1717
 
3.6%
7 1712
 
3.6%
Other values (2) 3160
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63892
57.1%
ASCII 47974
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16989
35.4%
1 5394
 
11.2%
- 5240
 
10.9%
2 3642
 
7.6%
3 3002
 
6.3%
4 2517
 
5.2%
5 2419
 
5.0%
6 2182
 
4.5%
0 1717
 
3.6%
7 1712
 
3.6%
Other values (2) 3160
 
6.6%
Hangul
ValueCountFrequency (%)
동 6771
 
10.6%
서 6427
 
10.1%
구 5981
 
9.4%
시 5680
 
8.9%
특 5663
 
8.9%
별 5663
 
8.9%
울 5663
 
8.9%
강 890
 
1.4%
신 853
 
1.3%
관 814
 
1.3%
Other values (174) 19487
30.5%

Interactions

2024-04-21T10:59:34.382974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-21T10:59:34.582734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:59:34.728710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번상호업종법정동 주소
01운현고시원고시원업서울특별시 종로구 경운동 1-9
12주식회사 에스에스디에이고시원업서울특별시 종로구 명륜3가 61-8
23원룸텔경복궁굿스테이고시원업서울특별시 종로구 필운동 278-5
34영하호고시원업서울특별시 종로구 창신동 283
45대보빌딩(코쿤하우스)고시원업서울특별시 종로구 이화동 36-2
56비엔하우스고시원업서울특별시 종로구 이화동 125
67동대문고시원고시원업서울특별시 종로구 창신동 651-16
7821세기고시원고시원업서울특별시 종로구 창신동 330-2
89밀레니엄 고시원고시원업서울특별시 종로구 창신동 463-1
910굿스테이원룸텔고시원업서울특별시 종로구 명륜1가 16-21
연번상호업종법정동 주소
56535654신동양고시원업서울특별시 관악구 신림동 1666-44
56545655신도시형 롯데원룸텔고시원업서울특별시 관악구 봉천동 972-29
56555656학운원룸고시원업서울특별시 관악구 신림동 231-39
56565657윤초고시원고시원업서울특별시 관악구 신림동 1554-21
56575658서전고시원업서울특별시 관악구 신림동 1532-20
56585659골든고시원고시원업서울특별시 관악구 신림동 1432-140
56595660삼원고시원고시원업서울특별시 관악구 봉천동 1666-48
56605661상록수고시텔고시원업서울특별시 관악구 신림동 112-37
56615662모렉스빌고시원고시원업서울특별시 관악구 신림동 570-36
56625663씨티빌고시원고시원업서울특별시 관악구 신림동 1568-12