Overview

Dataset statistics

Number of variables4
Number of observations168
Missing cells32
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory32.8 B

Variable types

Text3
Categorical1

Dataset

Description인천광역시 중구에 소재하는 중국식당에 관한 내용입니다.파일명 인천광역시 중구 중국식당 현황내용 상호, 소재지, 소재지전화번호 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15040974&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
소재지전화 has 32 (19.0%) missing valuesMissing

Reproduction

Analysis started2024-01-28 14:58:44.246568
Analysis finished2024-01-28 14:58:44.661224
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct166
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T23:58:44.870337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length33
Mean length5.6547619
Min length2

Characters and Unicode

Total characters950
Distinct characters238
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)97.6%

Sample

1st row진흥각
2nd row용화반점
3rd row혜빈장
4th row신일반점
5th row미광중화요리
ValueCountFrequency (%)
운서점 4
 
1.9%
하늘도시점 4
 
1.9%
마라탕 3
 
1.4%
공화춘 2
 
0.9%
인천공항점(여객터미널 2
 
0.9%
만다복 2
 
0.9%
주식회사 2
 
0.9%
이비가짬뽕 2
 
0.9%
교동짬뽕 2
 
0.9%
주)아워홈 2
 
0.9%
Other values (186) 189
88.3%
2024-01-28T23:58:45.247044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
4.8%
점 34
 
3.6%
라 32
 
3.4%
이 29
 
3.1%
마 27
 
2.8%
화 20
 
2.1%
탕 19
 
2.0%
뽕 18
 
1.9%
짬 16
 
1.7%
하 12
 
1.3%
Other values (228) 697
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 864
90.9%
Space Separator 46
 
4.8%
Open Punctuation 12
 
1.3%
Close Punctuation 12
 
1.3%
Other Punctuation 7
 
0.7%
Decimal Number 6
 
0.6%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 34
 
3.9%
라 32
 
3.7%
이 29
 
3.4%
마 27
 
3.1%
화 20
 
2.3%
탕 19
 
2.2%
뽕 18
 
2.1%
짬 16
 
1.9%
하 12
 
1.4%
향 12
 
1.4%
Other values (215) 645
74.7%
Decimal Number
ValueCountFrequency (%)
9 2
33.3%
0 2
33.3%
1 1
16.7%
4 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 5
71.4%
· 1
 
14.3%
, 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
I 1
33.3%
Z 1
33.3%
Space Separator
ValueCountFrequency (%)
46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 863
90.8%
Common 83
 
8.7%
Latin 3
 
0.3%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 34
 
3.9%
라 32
 
3.7%
이 29
 
3.4%
마 27
 
3.1%
화 20
 
2.3%
탕 19
 
2.2%
뽕 18
 
2.1%
짬 16
 
1.9%
하 12
 
1.4%
향 12
 
1.4%
Other values (214) 644
74.6%
Common
ValueCountFrequency (%)
46
55.4%
( 12
 
14.5%
) 12
 
14.5%
& 5
 
6.0%
9 2
 
2.4%
0 2
 
2.4%
1 1
 
1.2%
4 1
 
1.2%
· 1
 
1.2%
, 1
 
1.2%
Latin
ValueCountFrequency (%)
P 1
33.3%
I 1
33.3%
Z 1
33.3%
Han
ValueCountFrequency (%)
牛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 863
90.8%
ASCII 85
 
8.9%
CJK 1
 
0.1%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
54.1%
( 12
 
14.1%
) 12
 
14.1%
& 5
 
5.9%
9 2
 
2.4%
0 2
 
2.4%
1 1
 
1.2%
P 1
 
1.2%
I 1
 
1.2%
Z 1
 
1.2%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
점 34
 
3.9%
라 32
 
3.7%
이 29
 
3.4%
마 27
 
3.1%
화 20
 
2.3%
탕 19
 
2.2%
뽕 18
 
2.1%
짬 16
 
1.9%
하 12
 
1.4%
향 12
 
1.4%
Other values (214) 644
74.6%
CJK
ValueCountFrequency (%)
牛 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

소재지(도로명)
Text

Distinct166
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T23:58:45.505443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length34.220238
Min length13

Characters and Unicode

Total characters5749
Distinct characters190
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)97.6%

Sample

1st row인천광역시 중구 신포로23번길 20, 1,2,3층 (중앙동4가)
2nd row인천광역시 중구 경동 4
3rd row인천광역시 중구 참외전로13번길 21 (송월동2가)
4th row인천광역시 중구 서해대로 460-1 (신흥동2가, 3)
5th row인천광역시 중구 참외전로13번길 15-4 (송월동2가)
ValueCountFrequency (%)
인천광역시 168
 
15.2%
중구 168
 
15.2%
1층 69
 
6.2%
운서동 50
 
4.5%
중산동 27
 
2.4%
차이나타운로 23
 
2.1%
북성동2가 16
 
1.4%
2층 15
 
1.4%
1,2층 10
 
0.9%
선린동 10
 
0.9%
Other values (329) 548
49.6%
2024-01-28T23:58:45.878456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
937
 
16.3%
1 301
 
5.2%
중 214
 
3.7%
2 208
 
3.6%
, 202
 
3.5%
동 185
 
3.2%
시 184
 
3.2%
인 182
 
3.2%
천 176
 
3.1%
역 170
 
3.0%
Other values (180) 2990
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3191
55.5%
Decimal Number 1024
 
17.8%
Space Separator 937
 
16.3%
Other Punctuation 202
 
3.5%
Close Punctuation 168
 
2.9%
Open Punctuation 168
 
2.9%
Dash Punctuation 42
 
0.7%
Uppercase Letter 11
 
0.2%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 214
 
6.7%
동 185
 
5.8%
시 184
 
5.8%
인 182
 
5.7%
천 176
 
5.5%
역 170
 
5.3%
광 169
 
5.3%
구 168
 
5.3%
로 165
 
5.2%
층 123
 
3.9%
Other values (160) 1455
45.6%
Decimal Number
ValueCountFrequency (%)
1 301
29.4%
2 208
20.3%
4 107
 
10.4%
3 104
 
10.2%
0 85
 
8.3%
5 56
 
5.5%
6 52
 
5.1%
7 43
 
4.2%
9 36
 
3.5%
8 32
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
I 6
54.5%
C 2
 
18.2%
B 2
 
18.2%
F 1
 
9.1%
Space Separator
ValueCountFrequency (%)
937
100.0%
Other Punctuation
ValueCountFrequency (%)
, 202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3191
55.5%
Common 2547
44.3%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 214
 
6.7%
동 185
 
5.8%
시 184
 
5.8%
인 182
 
5.7%
천 176
 
5.5%
역 170
 
5.3%
광 169
 
5.3%
구 168
 
5.3%
로 165
 
5.2%
층 123
 
3.9%
Other values (160) 1455
45.6%
Common
ValueCountFrequency (%)
937
36.8%
1 301
 
11.8%
2 208
 
8.2%
, 202
 
7.9%
) 168
 
6.6%
( 168
 
6.6%
4 107
 
4.2%
3 104
 
4.1%
0 85
 
3.3%
5 56
 
2.2%
Other values (6) 211
 
8.3%
Latin
ValueCountFrequency (%)
I 6
54.5%
C 2
 
18.2%
B 2
 
18.2%
F 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3191
55.5%
ASCII 2558
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
937
36.6%
1 301
 
11.8%
2 208
 
8.1%
, 202
 
7.9%
) 168
 
6.6%
( 168
 
6.6%
4 107
 
4.2%
3 104
 
4.1%
0 85
 
3.3%
5 56
 
2.2%
Other values (10) 222
 
8.7%
Hangul
ValueCountFrequency (%)
중 214
 
6.7%
동 185
 
5.8%
시 184
 
5.8%
인 182
 
5.7%
천 176
 
5.5%
역 170
 
5.3%
광 169
 
5.3%
구 168
 
5.3%
로 165
 
5.2%
층 123
 
3.9%
Other values (160) 1455
45.6%

소재지전화
Text

MISSING 

Distinct135
Distinct (%)99.3%
Missing32
Missing (%)19.0%
Memory size1.4 KiB
2024-01-28T23:58:46.087576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1632
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

Unique134 ?
Unique (%)98.5%

Sample

1st row032-772-3058
2nd row032-773-5970
3rd row032-772-1928
4th row032-882-1812
5th row032-772-5595
ValueCountFrequency (%)
032-743-6250 2
 
1.5%
032-746-7222 1
 
0.7%
032-772-3058 1
 
0.7%
032-278-5780 1
 
0.7%
032-729-2227 1
 
0.7%
032-751-8132 1
 
0.7%
032-752-3360 1
 
0.7%
032-743-6280 1
 
0.7%
032-743-6260 1
 
0.7%
032-746-8132 1
 
0.7%
Other values (125) 125
91.9%
2024-01-28T23:58:46.398012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 272
16.7%
2 247
15.1%
7 210
12.9%
3 207
12.7%
0 192
11.8%
8 123
7.5%
6 117
7.2%
5 94
 
5.8%
1 73
 
4.5%
4 57
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1360
83.3%
Dash Punctuation 272
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 247
18.2%
7 210
15.4%
3 207
15.2%
0 192
14.1%
8 123
9.0%
6 117
8.6%
5 94
 
6.9%
1 73
 
5.4%
4 57
 
4.2%
9 40
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1632
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 272
16.7%
2 247
15.1%
7 210
12.9%
3 207
12.7%
0 192
11.8%
8 123
7.5%
6 117
7.2%
5 94
 
5.8%
1 73
 
4.5%
4 57
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 272
16.7%
2 247
15.1%
7 210
12.9%
3 207
12.7%
0 192
11.8%
8 123
7.5%
6 117
7.2%
5 94
 
5.8%
1 73
 
4.5%
4 57
 
3.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-07-05
168 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-05
2nd row2023-07-05
3rd row2023-07-05
4th row2023-07-05
5th row2023-07-05

Common Values

ValueCountFrequency (%)
2023-07-05 168
100.0%

Length

2024-01-28T23:58:46.510294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:58:46.594399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-05 168
100.0%

Missing values

2024-01-28T23:58:44.531811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T23:58:44.626590image/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

업소명소재지(도로명)소재지전화데이터기준일자
0진흥각인천광역시 중구 신포로23번길 20, 1,2,3층 (중앙동4가)032-772-30582023-07-05
1용화반점인천광역시 중구 경동 4032-773-59702023-07-05
2혜빈장인천광역시 중구 참외전로13번길 21 (송월동2가)032-772-19282023-07-05
3신일반점인천광역시 중구 서해대로 460-1 (신흥동2가, 3)032-882-18122023-07-05
4미광중화요리인천광역시 중구 참외전로13번길 15-4 (송월동2가)032-772-55952023-07-05
5중화원인천광역시 중구 차이나타운로44번길 20 (북성동2가)032-777-86302023-07-05
6풍미인천광역시 중구 차이나타운로 56 (선린동, 1층,2층)032-772-26802023-07-05
7원정루인천광역시 중구 서해대로 220 (신흥동3가)032-882-42522023-07-05
8중화루인천광역시 중구 홍예문로 12 (중앙동4가, 7-1,2(1,2,3층))032-762-02312023-07-05
9퓨어쉐프인천광역시 중구 서해대로449번길 6-7 (신흥동2가)032-766-37552023-07-05
업소명소재지(도로명)소재지전화데이터기준일자
158별미여의인천광역시 중구 우현로35번길 12, 1층 (신포동)032-772-62662023-07-05
159라오샹하이인천광역시 중구 햇내로안길 58-2, 1층 (운서동)032-299-82922023-07-05
160뽕가네&덮밥ZIP 운서점인천광역시 중구 화랑목로 70-4, 1층 102,103호 (운서동)<NA>2023-07-05
161육짬뽕인천광역시 중구 모랫말로 6-8, 1층 일부 (운서동)0327-5266-602023-07-05
162천향오마라탕 운서역점인천광역시 중구 영종대로162번길 26, 삼성홈큐브 1층 108호 (운서동)032-751-57892023-07-05
163주태백이인천광역시 중구 영종대로196번길 15-25, 114동 1층 131호 (운서동, 운서역 반도유보라 퍼스티지)032-747-22582023-07-05
164牛우육면관인천광역시 중구 하늘중앙로 193, 1층 123호 (중산동)032-721-98982023-07-05
165취화선인천광역시 중구 햇내로안길 7, 1층 104호 (운서동)032-746-65132023-07-05
166불간짬뽕인천광역시 중구 하늘중앙로225번길 20, 스카이에비뉴2 2층 211,212,213호 (중산동)032-212-57572023-07-05
167대박각인천광역시 중구 우현로72번길 18, 1층 (용동)<NA>2023-07-05