Overview

Dataset statistics

Number of variables4
Number of observations1520
Missing cells671
Missing cells (%)11.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.6 KiB
Average record size in memory32.1 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 연수구의 공중위생업소 현황의 데이터로서 숙박업 미용업 등의 (업소명, 도로명 주소, 전화번호)의 항목을 제공함
Author인천광역시 연수구
URLhttps://www.data.go.kr/data/15086985/fileData.do

Alerts

소재지전화 has 671 (44.1%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:55:55.741393
Analysis finished2024-04-06 08:55:56.979073
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct22
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
일반미용업
478 
피부미용업
185 
미용업
134 
세탁업
120 
네일미용업
108 
Other values (17)
495 

Length

Max length23
Median length5
Mean length6.0059211
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 478
31.4%
피부미용업 185
 
12.2%
미용업 134
 
8.8%
세탁업 120
 
7.9%
네일미용업 108
 
7.1%
종합미용업 74
 
4.9%
이용업 66
 
4.3%
건물위생관리업 66
 
4.3%
숙박업(일반) 65
 
4.3%
화장ㆍ분장 미용업 33
 
2.2%
Other values (12) 191
 
12.6%

Length

2024-04-06T17:55:57.137987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 532
28.7%
미용업 277
14.9%
피부미용업 270
14.6%
네일미용업 203
 
11.0%
화장ㆍ분장 143
 
7.7%
세탁업 120
 
6.5%
종합미용업 74
 
4.0%
이용업 66
 
3.6%
건물위생관리업 66
 
3.6%
숙박업(일반 65
 
3.5%
Other values (2) 37
 
2.0%

업소명
Text

Distinct1481
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
2024-04-06T17:55:57.540503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length29
Mean length7.6960526
Min length1

Characters and Unicode

Total characters11698
Distinct characters612
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1444 ?
Unique (%)95.0%

Sample

1st row둥지모텔
2nd row삼미장여관
3rd row호텔뷰(VIEW)
4th row라마다송도호텔(주)
5th row여우비
ValueCountFrequency (%)
헤어 56
 
2.4%
hair 29
 
1.3%
미용실 28
 
1.2%
송도점 25
 
1.1%
네일 24
 
1.0%
이발관 20
 
0.9%
에스테틱 16
 
0.7%
주식회사 15
 
0.7%
더 14
 
0.6%
세탁 13
 
0.6%
Other values (1750) 2061
89.6%
2024-04-06T17:55:58.356960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
790
 
6.8%
어 466
 
4.0%
헤 448
 
3.8%
스 285
 
2.4%
) 260
 
2.2%
( 260
 
2.2%
이 258
 
2.2%
일 171
 
1.5%
리 166
 
1.4%
네 162
 
1.4%
Other values (602) 8432
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8471
72.4%
Lowercase Letter 916
 
7.8%
Uppercase Letter 829
 
7.1%
Space Separator 790
 
6.8%
Close Punctuation 260
 
2.2%
Open Punctuation 260
 
2.2%
Other Punctuation 82
 
0.7%
Decimal Number 77
 
0.7%
Dash Punctuation 7
 
0.1%
Connector Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 466
 
5.5%
헤 448
 
5.3%
스 285
 
3.4%
이 258
 
3.0%
일 171
 
2.0%
리 166
 
2.0%
네 162
 
1.9%
미 136
 
1.6%
아 129
 
1.5%
도 118
 
1.4%
Other values (524) 6132
72.4%
Uppercase Letter
ValueCountFrequency (%)
A 92
 
11.1%
N 67
 
8.1%
E 64
 
7.7%
L 61
 
7.4%
O 61
 
7.4%
I 56
 
6.8%
H 51
 
6.2%
B 45
 
5.4%
S 43
 
5.2%
R 40
 
4.8%
Other values (16) 249
30.0%
Lowercase Letter
ValueCountFrequency (%)
a 125
13.6%
e 95
10.4%
i 91
9.9%
o 79
 
8.6%
n 71
 
7.8%
l 67
 
7.3%
r 64
 
7.0%
h 42
 
4.6%
s 39
 
4.3%
t 36
 
3.9%
Other values (15) 207
22.6%
Other Punctuation
ValueCountFrequency (%)
& 24
29.3%
. 23
28.0%
# 12
14.6%
' 9
 
11.0%
: 8
 
9.8%
＃ 2
 
2.4%
; 1
 
1.2%
： 1
 
1.2%
/ 1
 
1.2%
· 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 18
23.4%
1 15
19.5%
3 11
14.3%
6 7
 
9.1%
5 7
 
9.1%
4 6
 
7.8%
0 6
 
7.8%
9 3
 
3.9%
8 2
 
2.6%
7 2
 
2.6%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
790
100.0%
Close Punctuation
ValueCountFrequency (%)
) 260
100.0%
Open Punctuation
ValueCountFrequency (%)
( 260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8467
72.4%
Latin 1745
 
14.9%
Common 1482
 
12.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 466
 
5.5%
헤 448
 
5.3%
스 285
 
3.4%
이 258
 
3.0%
일 171
 
2.0%
리 166
 
2.0%
네 162
 
1.9%
미 136
 
1.6%
아 129
 
1.5%
도 118
 
1.4%
Other values (520) 6128
72.4%
Latin
ValueCountFrequency (%)
a 125
 
7.2%
e 95
 
5.4%
A 92
 
5.3%
i 91
 
5.2%
o 79
 
4.5%
n 71
 
4.1%
l 67
 
3.8%
N 67
 
3.8%
E 64
 
3.7%
r 64
 
3.7%
Other values (41) 930
53.3%
Common
ValueCountFrequency (%)
790
53.3%
) 260
 
17.5%
( 260
 
17.5%
& 24
 
1.6%
. 23
 
1.6%
2 18
 
1.2%
1 15
 
1.0%
# 12
 
0.8%
3 11
 
0.7%
' 9
 
0.6%
Other values (17) 60
 
4.0%
Han
ValueCountFrequency (%)
美 1
25.0%
后 1
25.0%
秀 1
25.0%
休 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8467
72.4%
ASCII 3223
 
27.6%
None 4
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
790
24.5%
) 260
 
8.1%
( 260
 
8.1%
a 125
 
3.9%
e 95
 
2.9%
A 92
 
2.9%
i 91
 
2.8%
o 79
 
2.5%
n 71
 
2.2%
l 67
 
2.1%
Other values (65) 1293
40.1%
Hangul
ValueCountFrequency (%)
어 466
 
5.5%
헤 448
 
5.3%
스 285
 
3.4%
이 258
 
3.0%
일 171
 
2.0%
리 166
 
2.0%
네 162
 
1.9%
미 136
 
1.6%
아 129
 
1.5%
도 118
 
1.4%
Other values (520) 6128
72.4%
None
ValueCountFrequency (%)
＃ 2
50.0%
： 1
25.0%
· 1
25.0%
CJK
ValueCountFrequency (%)
美 1
25.0%
后 1
25.0%
秀 1
25.0%
休 1
25.0%

영업소주소(도로명)
Text

Distinct1495
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
2024-04-06T17:55:58.844311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length56
Mean length41.877632
Min length21

Characters and Unicode

Total characters63654
Distinct characters351
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1473 ?
Unique (%)96.9%

Sample

1st row인천광역시 연수구 능허대로 175 (옥련동)
2nd row인천광역시 연수구 능허대로167번길 6 (옥련동)
3rd row인천광역시 연수구 대암로 8 (옥련동)
4th row인천광역시 연수구 능허대로267번길 29 (동춘동)
5th row인천광역시 연수구 능허대로191번길 11 (옥련동)
ValueCountFrequency (%)
인천광역시 1520
 
12.7%
연수구 1520
 
12.7%
송도동 661
 
5.5%
1층 304
 
2.5%
연수동 276
 
2.3%
옥련동 197
 
1.7%
동춘동 188
 
1.6%
2층 165
 
1.4%
송도 156
 
1.3%
일부호 143
 
1.2%
Other values (1727) 6804
57.0%
2024-04-06T17:55:59.678236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12322
 
19.4%
1 3040
 
4.8%
동 2347
 
3.7%
연 1868
 
2.9%
수 1866
 
2.9%
2 1846
 
2.9%
인 1746
 
2.7%
시 1738
 
2.7%
) 1647
 
2.6%
( 1647
 
2.6%
Other values (341) 33587
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36653
57.6%
Space Separator 12322
 
19.4%
Decimal Number 10570
 
16.6%
Close Punctuation 1647
 
2.6%
Open Punctuation 1647
 
2.6%
Uppercase Letter 468
 
0.7%
Dash Punctuation 229
 
0.4%
Math Symbol 38
 
0.1%
Other Punctuation 36
 
0.1%
Lowercase Letter 36
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2347
 
6.4%
연 1868
 
5.1%
수 1866
 
5.1%
인 1746
 
4.8%
시 1738
 
4.7%
천 1612
 
4.4%
로 1594
 
4.3%
광 1527
 
4.2%
구 1523
 
4.2%
역 1520
 
4.1%
Other values (291) 19312
52.7%
Uppercase Letter
ValueCountFrequency (%)
A 105
22.4%
B 77
16.5%
C 49
10.5%
D 38
 
8.1%
E 23
 
4.9%
T 22
 
4.7%
S 21
 
4.5%
U 15
 
3.2%
M 15
 
3.2%
G 14
 
3.0%
Other values (13) 89
19.0%
Decimal Number
ValueCountFrequency (%)
1 3040
28.8%
2 1846
17.5%
0 1339
12.7%
3 947
 
9.0%
4 698
 
6.6%
5 650
 
6.1%
8 610
 
5.8%
6 557
 
5.3%
7 485
 
4.6%
9 398
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
s 10
27.8%
e 10
27.8%
t 8
22.2%
a 4
 
11.1%
m 2
 
5.6%
i 1
 
2.8%
c 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
@ 29
80.6%
& 3
 
8.3%
. 3
 
8.3%
/ 1
 
2.8%
Space Separator
ValueCountFrequency (%)
12322
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1647
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1647
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 229
100.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36653
57.6%
Common 26489
41.6%
Latin 512
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2347
 
6.4%
연 1868
 
5.1%
수 1866
 
5.1%
인 1746
 
4.8%
시 1738
 
4.7%
천 1612
 
4.4%
로 1594
 
4.3%
광 1527
 
4.2%
구 1523
 
4.2%
역 1520
 
4.1%
Other values (291) 19312
52.7%
Latin
ValueCountFrequency (%)
A 105
20.5%
B 77
15.0%
C 49
 
9.6%
D 38
 
7.4%
E 23
 
4.5%
T 22
 
4.3%
S 21
 
4.1%
U 15
 
2.9%
M 15
 
2.9%
G 14
 
2.7%
Other values (21) 133
26.0%
Common
ValueCountFrequency (%)
12322
46.5%
1 3040
 
11.5%
2 1846
 
7.0%
) 1647
 
6.2%
( 1647
 
6.2%
0 1339
 
5.1%
3 947
 
3.6%
4 698
 
2.6%
5 650
 
2.5%
8 610
 
2.3%
Other values (9) 1743
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36653
57.6%
ASCII 26993
42.4%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12322
45.6%
1 3040
 
11.3%
2 1846
 
6.8%
) 1647
 
6.1%
( 1647
 
6.1%
0 1339
 
5.0%
3 947
 
3.5%
4 698
 
2.6%
5 650
 
2.4%
8 610
 
2.3%
Other values (39) 2247
 
8.3%
Hangul
ValueCountFrequency (%)
동 2347
 
6.4%
연 1868
 
5.1%
수 1866
 
5.1%
인 1746
 
4.8%
시 1738
 
4.7%
천 1612
 
4.4%
로 1594
 
4.3%
광 1527
 
4.2%
구 1523
 
4.2%
역 1520
 
4.1%
Other values (291) 19312
52.7%
Number Forms
ValueCountFrequency (%)
Ⅲ 8
100.0%

소재지전화
Text

MISSING 

Distinct841
Distinct (%)99.1%
Missing671
Missing (%)44.1%
Memory size12.0 KiB
2024-04-06T17:56:00.181847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.040047
Min length5

Characters and Unicode

Total characters10222
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

Unique833 ?
Unique (%)98.1%

Sample

1st row032-833-6222
2nd row032-832-1525
3rd row032-832-1500
4th row032-832-1311
5th row032-832-9700
ValueCountFrequency (%)
032-710-5002 2
 
0.2%
032-835-1000 2
 
0.2%
032-818-2601 2
 
0.2%
032-851-6900 2
 
0.2%
032-851-8899 2
 
0.2%
032-831-3120 2
 
0.2%
032-813-4646 2
 
0.2%
032-821-6677 2
 
0.2%
032-822-2033 1
 
0.1%
032-814-1600 1
 
0.1%
Other values (831) 831
97.9%
2024-04-06T17:56:00.849130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1697
16.6%
3 1546
15.1%
2 1442
14.1%
0 1363
13.3%
8 1163
11.4%
1 910
8.9%
5 490
 
4.8%
7 474
 
4.6%
4 394
 
3.9%
6 379
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8525
83.4%
Dash Punctuation 1697
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1546
18.1%
2 1442
16.9%
0 1363
16.0%
8 1163
13.6%
1 910
10.7%
5 490
 
5.7%
7 474
 
5.6%
4 394
 
4.6%
6 379
 
4.4%
9 364
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 1697
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10222
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1697
16.6%
3 1546
15.1%
2 1442
14.1%
0 1363
13.3%
8 1163
11.4%
1 910
8.9%
5 490
 
4.8%
7 474
 
4.6%
4 394
 
3.9%
6 379
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1697
16.6%
3 1546
15.1%
2 1442
14.1%
0 1363
13.3%
8 1163
11.4%
1 910
8.9%
5 490
 
4.8%
7 474
 
4.6%
4 394
 
3.9%
6 379
 
3.7%

Missing values

2024-04-06T17:55:56.708992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:55:56.904723image/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

업종명업소명영업소주소(도로명)소재지전화
0숙박업(일반)둥지모텔인천광역시 연수구 능허대로 175 (옥련동)032-833-6222
1숙박업(일반)삼미장여관인천광역시 연수구 능허대로167번길 6 (옥련동)032-832-1525
2숙박업(일반)호텔뷰(VIEW)인천광역시 연수구 대암로 8 (옥련동)032-832-1500
3숙박업(일반)라마다송도호텔(주)인천광역시 연수구 능허대로267번길 29 (동춘동)032-832-1311
4숙박업(일반)여우비인천광역시 연수구 능허대로191번길 11 (옥련동)032-832-9700
5숙박업(일반)필드모텔인천광역시 연수구 대암로 4 (옥련동)032-0832-1239
6숙박업(일반)가빈인천광역시 연수구 인권로 17 (옥련동)032-832-3561
7숙박업(일반)호텔메이인천광역시 연수구 인권로9번길 10 (옥련동)032-834-5505
8숙박업(일반)큐(Q)모텔인천광역시 연수구 대암로8번길 14 (옥련동)032-831-9488
9숙박업(일반)노리터모텔인천광역시 연수구 인권로 15 (옥련동)032-858-8664
업종명업소명영업소주소(도로명)소재지전화
1510피부미용업 네일미용업 화장ㆍ분장 미용업네일 민(Nail Min)인천광역시 연수구 컨벤시아대로 116 1층 125호 (송도동 푸르지오월드마크)<NA>
1511피부미용업 네일미용업 화장ㆍ분장 미용업네일은 예쁘게인천광역시 연수구 컨벤시아대로 50 1층 118호 (송도동 푸르지오월드마크)<NA>
1512피부미용업 네일미용업 화장ㆍ분장 미용업네일해피(nail happy)인천광역시 연수구 신송로6번길 7 상가동 201호 (송도동 송도 성지리벨루스)<NA>
1513피부미용업 네일미용업 화장ㆍ분장 미용업바닐라뷰티크인천광역시 연수구 하모니로 158 송도타임스페이스 C동 215호 (송도동)<NA>
1514피부미용업 네일미용업 화장ㆍ분장 미용업소담살롱인천광역시 연수구 하모니로 158 송도타임스페이스 D동 2층 222호 (송도동)<NA>
1515피부미용업 네일미용업 화장ㆍ분장 미용업365왁싱인천광역시 연수구 앵고개로 260 맘모스빌딩 2층 208호 (동춘동)<NA>
1516피부미용업 네일미용업 화장ㆍ분장 미용업네일을 부탁해인천광역시 연수구 계림로112번길 9 삼성주택 1층 일부호 (청학동)032-819-7715
1517피부미용업 네일미용업 화장ㆍ분장 미용업나다운네일인천광역시 연수구 하모니로178번길 22 3층 315일부호 (송도동)<NA>
1518피부미용업 네일미용업 화장ㆍ분장 미용업네일젤이뻐인천광역시 연수구 먼우금로222번길 37 이레하이니스 101동 101호 (연수동)<NA>
1519피부미용업 네일미용업 화장ㆍ분장 미용업숲래쉬 속눈썹&펌인천광역시 연수구 하모니로178번길 22 송도 GTX 센트럴 129-1호 일부호 (송도동)<NA>