Overview

Dataset statistics

Number of variables5
Number of observations1326
Missing cells477
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.9 KiB
Average record size in memory40.1 B

Variable types

Categorical1
Text4

Dataset

Description부산광역시금정구_공중위생업소현황_20230117
Author부산광역시 금정구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15006972

Alerts

소재지전화 has 477 (36.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:58:51.709746
Analysis finished2023-12-10 16:58:52.669873
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct20
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size10.5 KiB
일반미용업
334 
미용업
260 
세탁업
145 
피부미용업
132 
이용업
117 
Other values (15)
338 

Length

Max length23
Median length16
Mean length4.9758673
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
일반미용업 334
25.2%
미용업 260
19.6%
세탁업 145
10.9%
피부미용업 132
 
10.0%
이용업 117
 
8.8%
숙박업(일반) 68
 
5.1%
네일미용업 67
 
5.1%
목욕장업 48
 
3.6%
건물위생관리업 43
 
3.2%
종합미용업 18
 
1.4%
Other values (10) 94
 
7.1%

Length

2023-12-11T01:58:52.785311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 358
24.4%
미용업 321
21.9%
피부미용업 166
11.3%
세탁업 145
9.9%
이용업 117
 
8.0%
네일미용업 114
 
7.8%
숙박업(일반 68
 
4.6%
화장ㆍ분장 61
 
4.2%
목욕장업 48
 
3.3%
건물위생관리업 43
 
2.9%
Other values (2) 28
 
1.9%

업소명
Text

Distinct1263
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size10.5 KiB
2023-12-11T01:58:53.242655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length5.5143288
Min length1

Characters and Unicode

Total characters7312
Distinct characters586
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1215 ?
Unique (%)91.6%

Sample

1st row삼성여인숙
2nd row제일여인숙
3rd row마산여인숙
4th row천우장
5th row모텔 델루나
ValueCountFrequency (%)
헤어 17
 
1.1%
네일 8
 
0.5%
부산대점 8
 
0.5%
hair 7
 
0.4%
태후사랑 6
 
0.4%
nail 5
 
0.3%
salon 5
 
0.3%
제일 5
 
0.3%
에스테틱 5
 
0.3%
수 5
 
0.3%
Other values (1391) 1496
95.5%
2023-12-11T01:58:54.131652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 344
 
4.7%
헤 340
 
4.6%
249
 
3.4%
이 176
 
2.4%
스 151
 
2.1%
미 120
 
1.6%
) 117
 
1.6%
( 116
 
1.6%
일 113
 
1.5%
리 112
 
1.5%
Other values (576) 5474
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6026
82.4%
Lowercase Letter 403
 
5.5%
Uppercase Letter 314
 
4.3%
Space Separator 249
 
3.4%
Close Punctuation 117
 
1.6%
Open Punctuation 116
 
1.6%
Decimal Number 45
 
0.6%
Other Punctuation 37
 
0.5%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 344
 
5.7%
헤 340
 
5.6%
이 176
 
2.9%
스 151
 
2.5%
미 120
 
2.0%
일 113
 
1.9%
리 112
 
1.9%
네 99
 
1.6%
아 85
 
1.4%
티 66
 
1.1%
Other values (507) 4420
73.3%
Uppercase Letter
ValueCountFrequency (%)
A 29
 
9.2%
N 28
 
8.9%
O 28
 
8.9%
M 25
 
8.0%
E 21
 
6.7%
S 19
 
6.1%
L 16
 
5.1%
H 16
 
5.1%
R 16
 
5.1%
I 15
 
4.8%
Other values (14) 101
32.2%
Lowercase Letter
ValueCountFrequency (%)
o 52
12.9%
a 47
11.7%
i 44
10.9%
e 41
10.2%
n 38
9.4%
l 27
 
6.7%
r 27
 
6.7%
s 18
 
4.5%
h 18
 
4.5%
y 15
 
3.7%
Other values (13) 76
18.9%
Decimal Number
ValueCountFrequency (%)
2 15
33.3%
1 9
20.0%
5 4
 
8.9%
4 4
 
8.9%
0 3
 
6.7%
9 3
 
6.7%
3 2
 
4.4%
7 2
 
4.4%
8 2
 
4.4%
6 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
& 14
37.8%
, 9
24.3%
. 7
18.9%
' 2
 
5.4%
# 2
 
5.4%
: 1
 
2.7%
; 1
 
2.7%
＃ 1
 
2.7%
Space Separator
ValueCountFrequency (%)
249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6024
82.4%
Latin 717
 
9.8%
Common 569
 
7.8%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 344
 
5.7%
헤 340
 
5.6%
이 176
 
2.9%
스 151
 
2.5%
미 120
 
2.0%
일 113
 
1.9%
리 112
 
1.9%
네 99
 
1.6%
아 85
 
1.4%
티 66
 
1.1%
Other values (505) 4418
73.3%
Latin
ValueCountFrequency (%)
o 52
 
7.3%
a 47
 
6.6%
i 44
 
6.1%
e 41
 
5.7%
n 38
 
5.3%
A 29
 
4.0%
N 28
 
3.9%
O 28
 
3.9%
l 27
 
3.8%
r 27
 
3.8%
Other values (37) 356
49.7%
Common
ValueCountFrequency (%)
249
43.8%
) 117
20.6%
( 116
20.4%
2 15
 
2.6%
& 14
 
2.5%
1 9
 
1.6%
, 9
 
1.6%
. 7
 
1.2%
- 5
 
0.9%
5 4
 
0.7%
Other values (12) 24
 
4.2%
Han
ValueCountFrequency (%)
水 1
50.0%
休 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6024
82.4%
ASCII 1285
 
17.6%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 344
 
5.7%
헤 340
 
5.6%
이 176
 
2.9%
스 151
 
2.5%
미 120
 
2.0%
일 113
 
1.9%
리 112
 
1.9%
네 99
 
1.6%
아 85
 
1.4%
티 66
 
1.1%
Other values (505) 4418
73.3%
ASCII
ValueCountFrequency (%)
249
19.4%
) 117
 
9.1%
( 116
 
9.0%
o 52
 
4.0%
a 47
 
3.7%
i 44
 
3.4%
e 41
 
3.2%
n 38
 
3.0%
A 29
 
2.3%
N 28
 
2.2%
Other values (58) 524
40.8%
CJK
ValueCountFrequency (%)
水 1
50.0%
休 1
50.0%
None
ValueCountFrequency (%)
＃ 1
100.0%

영업소 주소(지번)
Text

Distinct1173
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size10.5 KiB
2023-12-11T01:58:54.786557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length38
Mean length21.470588
Min length17

Characters and Unicode

Total characters28470
Distinct characters207
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1053 ?
Unique (%)79.4%

Sample

1st row부산광역시 금정구 서동 340-21
2nd row부산광역시 금정구 서동 302-31
3rd row부산광역시 금정구 서동 302-523
4th row부산광역시 금정구 금사동 68-32
5th row부산광역시 금정구 장전동 617-12
ValueCountFrequency (%)
부산광역시 1326
23.8%
금정구 1326
23.8%
장전동 328
 
5.9%
부곡동 266
 
4.8%
구서동 250
 
4.5%
서동 245
 
4.4%
남산동 177
 
3.2%
금사동 28
 
0.5%
1층 20
 
0.4%
청룡동 20
 
0.4%
Other values (1283) 1596
28.6%
2023-12-11T01:58:55.818636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5556
19.5%
부 1610
 
5.7%
구 1590
 
5.6%
산 1518
 
5.3%
금 1366
 
4.8%
동 1362
 
4.8%
시 1339
 
4.7%
정 1337
 
4.7%
역 1332
 
4.7%
광 1327
 
4.7%
Other values (197) 10133
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15416
54.1%
Decimal Number 6199
21.8%
Space Separator 5556
 
19.5%
Dash Punctuation 1279
 
4.5%
Uppercase Letter 9
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1610
10.4%
구 1590
10.3%
산 1518
9.8%
금 1366
8.9%
동 1362
8.8%
시 1339
8.7%
정 1337
8.7%
역 1332
8.6%
광 1327
8.6%
서 504
 
3.3%
Other values (176) 2131
13.8%
Decimal Number
ValueCountFrequency (%)
1 1207
19.5%
2 1030
16.6%
3 767
12.4%
4 535
8.6%
6 506
8.2%
5 481
 
7.8%
0 457
 
7.4%
7 427
 
6.9%
9 419
 
6.8%
8 370
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
33.3%
F 2
22.2%
W 1
 
11.1%
N 1
 
11.1%
C 1
 
11.1%
B 1
 
11.1%
Space Separator
ValueCountFrequency (%)
5556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1279
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15416
54.1%
Common 13045
45.8%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1610
10.4%
구 1590
10.3%
산 1518
9.8%
금 1366
8.9%
동 1362
8.8%
시 1339
8.7%
정 1337
8.7%
역 1332
8.6%
광 1327
8.6%
서 504
 
3.3%
Other values (176) 2131
13.8%
Common
ValueCountFrequency (%)
5556
42.6%
- 1279
 
9.8%
1 1207
 
9.3%
2 1030
 
7.9%
3 767
 
5.9%
4 535
 
4.1%
6 506
 
3.9%
5 481
 
3.7%
0 457
 
3.5%
7 427
 
3.3%
Other values (5) 800
 
6.1%
Latin
ValueCountFrequency (%)
A 3
33.3%
F 2
22.2%
W 1
 
11.1%
N 1
 
11.1%
C 1
 
11.1%
B 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15416
54.1%
ASCII 13054
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5556
42.6%
- 1279
 
9.8%
1 1207
 
9.2%
2 1030
 
7.9%
3 767
 
5.9%
4 535
 
4.1%
6 506
 
3.9%
5 481
 
3.7%
0 457
 
3.5%
7 427
 
3.3%
Other values (11) 809
 
6.2%
Hangul
ValueCountFrequency (%)
부 1610
10.4%
구 1590
10.3%
산 1518
9.8%
금 1366
8.9%
동 1362
8.8%
시 1339
8.7%
정 1337
8.7%
역 1332
8.6%
광 1327
8.6%
서 504
 
3.3%
Other values (176) 2131
13.8%

우편번호(지번)
Text

Distinct69
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size10.5 KiB
2023-12-11T01:58:56.216433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters9282
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.5%

Sample

1st row609-830
2nd row609-827
3rd row609-832
4th row609-809
5th row609-842
ValueCountFrequency (%)
609-839 135
 
10.2%
609-837 50
 
3.8%
609-814 48
 
3.6%
609-832 47
 
3.5%
609-813 45
 
3.4%
609-848 45
 
3.4%
609-842 44
 
3.3%
609-811 41
 
3.1%
609-805 40
 
3.0%
609-824 39
 
2.9%
Other values (59) 792
59.7%
2023-12-11T01:58:56.873833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1645
17.7%
9 1532
16.5%
6 1448
15.6%
8 1412
15.2%
- 1326
14.3%
3 520
 
5.6%
1 414
 
4.5%
2 347
 
3.7%
4 336
 
3.6%
5 172
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7956
85.7%
Dash Punctuation 1326
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1645
20.7%
9 1532
19.3%
6 1448
18.2%
8 1412
17.7%
3 520
 
6.5%
1 414
 
5.2%
2 347
 
4.4%
4 336
 
4.2%
5 172
 
2.2%
7 130
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1645
17.7%
9 1532
16.5%
6 1448
15.6%
8 1412
15.2%
- 1326
14.3%
3 520
 
5.6%
1 414
 
4.5%
2 347
 
3.7%
4 336
 
3.6%
5 172
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1645
17.7%
9 1532
16.5%
6 1448
15.6%
8 1412
15.2%
- 1326
14.3%
3 520
 
5.6%
1 414
 
4.5%
2 347
 
3.7%
4 336
 
3.6%
5 172
 
1.9%

소재지전화
Text

MISSING 

Distinct841
Distinct (%)99.1%
Missing477
Missing (%)36.0%
Memory size10.5 KiB
2023-12-11T01:58:57.697364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.990577
Min length12

Characters and Unicode

Total characters11878
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique833 ?
Unique (%)98.1%

Sample

1st row 051- 523-6331
2nd row 051- 523-7876
3rd row051 -529 -8230
4th row 051- 523-3826
5th row 051- 512-4718
ValueCountFrequency (%)
051 817
40.1%
515 38
 
1.9%
583 31
 
1.5%
582 27
 
1.3%
516 26
 
1.3%
512 25
 
1.2%
513 23
 
1.1%
518 20
 
1.0%
070 19
 
0.9%
517 19
 
0.9%
Other values (899) 994
48.7%
2023-12-11T01:58:58.720381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2088
17.6%
- 1698
14.3%
1667
14.0%
1 1638
13.8%
0 1277
10.8%
2 745
 
6.3%
8 635
 
5.3%
3 507
 
4.3%
7 473
 
4.0%
6 406
 
3.4%
Other values (2) 744
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8513
71.7%
Dash Punctuation 1698
 
14.3%
Space Separator 1667
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2088
24.5%
1 1638
19.2%
0 1277
15.0%
2 745
 
8.8%
8 635
 
7.5%
3 507
 
6.0%
7 473
 
5.6%
6 406
 
4.8%
4 384
 
4.5%
9 360
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 1698
100.0%
Space Separator
ValueCountFrequency (%)
1667
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11878
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2088
17.6%
- 1698
14.3%
1667
14.0%
1 1638
13.8%
0 1277
10.8%
2 745
 
6.3%
8 635
 
5.3%
3 507
 
4.3%
7 473
 
4.0%
6 406
 
3.4%
Other values (2) 744
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2088
17.6%
- 1698
14.3%
1667
14.0%
1 1638
13.8%
0 1277
10.8%
2 745
 
6.3%
8 635
 
5.3%
3 507
 
4.3%
7 473
 
4.0%
6 406
 
3.4%
Other values (2) 744
 
6.3%

Correlations

2023-12-11T01:58:58.887466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명우편번호(지번)
업종명1.0000.527
우편번호(지번)0.5271.000

Missing values

2023-12-11T01:58:52.475150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:58:52.611243image/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

업종명업소명영업소 주소(지번)우편번호(지번)소재지전화
0숙박업(일반)삼성여인숙부산광역시 금정구 서동 340-21609-830051- 523-6331
1숙박업(일반)제일여인숙부산광역시 금정구 서동 302-31609-827051- 523-7876
2숙박업(일반)마산여인숙부산광역시 금정구 서동 302-523609-832051 -529 -8230
3숙박업(일반)천우장부산광역시 금정구 금사동 68-32609-809051- 523-3826
4숙박업(일반)모텔 델루나부산광역시 금정구 장전동 617-12609-842051- 512-4718
5숙박업(일반)서동온천부산광역시 금정구 서동 338-2609-830051- 523-7788
6숙박업(일반)향림장여관부산광역시 금정구 구서동 463-5609-806051- 514-7235
7숙박업(일반)청룡여관부산광역시 금정구 청룡동 31-1609-843051- 508-6316
8숙박업(일반)유성장모텔부산광역시 금정구 청룡동 44-3609-843051- 508-5890
9숙박업(일반)에스모텔부산광역시 금정구 청룡동 39-6609-843051- 508-1172
업종명업소명영업소 주소(지번)우편번호(지번)소재지전화
1316피부미용업, 네일미용업, 화장ㆍ분장 미용업네일바다부산광역시 금정구 부곡동 63-1609-817051 -517 -4116
1317피부미용업, 네일미용업, 화장ㆍ분장 미용업살롱 드 류부산광역시 금정구 장전동 421-16609-839051 -513 -5305
1318피부미용업, 네일미용업, 화장ㆍ분장 미용업인생네일부산광역시 금정구 장전동 203-14609-837051 -583 -2977
1319피부미용업, 네일미용업, 화장ㆍ분장 미용업살롱드현지부산광역시 금정구 부곡동 242-22609-852<NA>
1320피부미용업, 네일미용업, 화장ㆍ분장 미용업엠에스뷰티부산광역시 금정구 구서동 252-17609-847<NA>
1321피부미용업, 네일미용업, 화장ㆍ분장 미용업아소시에 네일(Associe nail)부산광역시 금정구 부곡동 386-1 신동아아파트609-824<NA>
1322피부미용업, 네일미용업, 화장ㆍ분장 미용업뷰티싸롱미미부산광역시 금정구 장전동 412-10609-838051 -518 -8815
1323피부미용업, 네일미용업, 화장ㆍ분장 미용업블랑드뷰티부산광역시 금정구 장전동 423-52609-839<NA>
1324피부미용업, 네일미용업, 화장ㆍ분장 미용업까모르살롱 네일왁싱부산광역시 금정구 장전동 414-2609-839<NA>
1325피부미용업, 네일미용업, 화장ㆍ분장 미용업마셀왁싱앤뷰티부산광역시 금정구 장전동 293-175609-839<NA>