Overview

Dataset statistics

Number of variables5
Number of observations244
Missing cells4
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory40.5 B

Variable types

Categorical2
Text3

Dataset

Description인천광역시 미추홀구 관내의 영업 중인 중국식 식당 현황에 대한 데이터로 업종명, 업태명, 업소명, 도로명주소, 지번주소 등의 항목을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15040880/fileData.do

Alerts

업종명 has constant value ""Constant
업태명 has constant value ""Constant
소재지(도로명) has 4 (1.6%) missing valuesMissing

Reproduction

Analysis started2024-04-29 22:29:13.886016
Analysis finished2024-04-29 22:29:14.630666
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
일반음식점
244 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 244
100.0%

Length

2024-04-30T07:29:14.690072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:29:14.786892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 244
100.0%

업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
중국식
244 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중국식 244
100.0%

Length

2024-04-30T07:29:14.877606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:29:14.963324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중국식 244
100.0%

업소명
Text

Distinct235
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T07:29:15.165131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length5.6065574
Min length2

Characters and Unicode

Total characters1368
Distinct characters274
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique226 ?
Unique (%)92.6%

Sample

1st row참설렁탕
2nd row영화반점
3rd row동락반점
4th row경안각
5th row해성장
ValueCountFrequency (%)
마라탕 10
 
3.0%
주안점 6
 
1.8%
짬뽕 4
 
1.2%
탕화쿵푸 3
 
0.9%
롯데인천점 3
 
0.9%
도화점 3
 
0.9%
인천도화점 2
 
0.6%
앨리웨이 2
 
0.6%
미추홀점 2
 
0.6%
도화 2
 
0.6%
Other values (275) 293
88.8%
2024-04-30T07:29:15.525827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
6.3%
점 64
 
4.7%
라 48
 
3.5%
마 44
 
3.2%
탕 34
 
2.5%
화 33
 
2.4%
인 26
 
1.9%
이 25
 
1.8%
반 23
 
1.7%
뽕 22
 
1.6%
Other values (264) 963
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1227
89.7%
Space Separator 86
 
6.3%
Decimal Number 26
 
1.9%
Lowercase Letter 10
 
0.7%
Uppercase Letter 6
 
0.4%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 64
 
5.2%
라 48
 
3.9%
마 44
 
3.6%
탕 34
 
2.8%
화 33
 
2.7%
인 26
 
2.1%
이 25
 
2.0%
반 23
 
1.9%
뽕 22
 
1.8%
천 21
 
1.7%
Other values (240) 887
72.3%
Decimal Number
ValueCountFrequency (%)
0 10
38.5%
1 5
19.2%
9 4
 
15.4%
4 3
 
11.5%
8 2
 
7.7%
2 1
 
3.8%
5 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
30.0%
o 2
20.0%
d 1
 
10.0%
l 1
 
10.0%
n 1
 
10.0%
f 1
 
10.0%
b 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
S 1
16.7%
D 1
16.7%
F 1
16.7%
J 1
16.7%
Other Punctuation
ValueCountFrequency (%)
＆ 2
66.7%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1227
89.7%
Common 125
 
9.1%
Latin 16
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 64
 
5.2%
라 48
 
3.9%
마 44
 
3.6%
탕 34
 
2.8%
화 33
 
2.7%
인 26
 
2.1%
이 25
 
2.0%
반 23
 
1.9%
뽕 22
 
1.8%
천 21
 
1.7%
Other values (240) 887
72.3%
Common
ValueCountFrequency (%)
86
68.8%
0 10
 
8.0%
( 5
 
4.0%
1 5
 
4.0%
) 5
 
4.0%
9 4
 
3.2%
4 3
 
2.4%
8 2
 
1.6%
＆ 2
 
1.6%
2 1
 
0.8%
Other values (2) 2
 
1.6%
Latin
ValueCountFrequency (%)
e 3
18.8%
O 2
12.5%
o 2
12.5%
d 1
 
6.2%
l 1
 
6.2%
S 1
 
6.2%
n 1
 
6.2%
f 1
 
6.2%
D 1
 
6.2%
b 1
 
6.2%
Other values (2) 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1227
89.7%
ASCII 139
 
10.2%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
61.9%
0 10
 
7.2%
( 5
 
3.6%
1 5
 
3.6%
) 5
 
3.6%
9 4
 
2.9%
4 3
 
2.2%
e 3
 
2.2%
8 2
 
1.4%
O 2
 
1.4%
Other values (13) 14
 
10.1%
Hangul
ValueCountFrequency (%)
점 64
 
5.2%
라 48
 
3.9%
마 44
 
3.6%
탕 34
 
2.8%
화 33
 
2.7%
인 26
 
2.1%
이 25
 
2.0%
반 23
 
1.9%
뽕 22
 
1.8%
천 21
 
1.7%
Other values (240) 887
72.3%
None
ValueCountFrequency (%)
＆ 2
100.0%

소재지(도로명)
Text

MISSING 

Distinct239
Distinct (%)99.6%
Missing4
Missing (%)1.6%
Memory size2.0 KiB
2024-04-30T07:29:15.747513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length32.275
Min length23

Characters and Unicode

Total characters7746
Distinct characters191
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)99.2%

Sample

1st row인천광역시 미추홀구 인하로 274-30 (주안동,남부상가3동9호)
2nd row인천광역시 미추홀구 인중로 18, 1층 (숭의동)
3rd row인천광역시 미추홀구 독배로 473 (숭의동)
4th row인천광역시 미추홀구 경인로 182-1 (도화동)
5th row인천광역시 미추홀구 소성로 85 (학익동)
ValueCountFrequency (%)
인천광역시 240
 
16.2%
미추홀구 240
 
16.2%
주안동 79
 
5.3%
용현동 68
 
4.6%
1층 63
 
4.3%
2층 31
 
2.1%
도화동 28
 
1.9%
숭의동 20
 
1.4%
학익동 18
 
1.2%
인하로 14
 
0.9%
Other values (407) 680
45.9%
2024-04-30T07:29:16.109646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1242
 
16.0%
인 320
 
4.1%
1 291
 
3.8%
미 264
 
3.4%
홀 263
 
3.4%
동 258
 
3.3%
추 257
 
3.3%
천 251
 
3.2%
역 246
 
3.2%
) 246
 
3.2%
Other values (181) 4108
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4570
59.0%
Space Separator 1242
 
16.0%
Decimal Number 1200
 
15.5%
Close Punctuation 246
 
3.2%
Open Punctuation 246
 
3.2%
Other Punctuation 189
 
2.4%
Dash Punctuation 39
 
0.5%
Uppercase Letter 8
 
0.1%
Lowercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 320
 
7.0%
미 264
 
5.8%
홀 263
 
5.8%
동 258
 
5.6%
추 257
 
5.6%
천 251
 
5.5%
역 246
 
5.4%
시 241
 
5.3%
구 241
 
5.3%
광 241
 
5.3%
Other values (156) 1988
43.5%
Decimal Number
ValueCountFrequency (%)
1 291
24.2%
2 188
15.7%
3 145
12.1%
0 119
9.9%
4 105
 
8.8%
5 80
 
6.7%
6 78
 
6.5%
8 75
 
6.2%
7 71
 
5.9%
9 48
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
50.0%
K 1
 
12.5%
A 1
 
12.5%
J 1
 
12.5%
T 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
w 1
25.0%
e 1
25.0%
r 1
25.0%
Space Separator
ValueCountFrequency (%)
1242
100.0%
Close Punctuation
ValueCountFrequency (%)
) 246
100.0%
Open Punctuation
ValueCountFrequency (%)
( 246
100.0%
Other Punctuation
ValueCountFrequency (%)
, 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4570
59.0%
Common 3164
40.8%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 320
 
7.0%
미 264
 
5.8%
홀 263
 
5.8%
동 258
 
5.6%
추 257
 
5.6%
천 251
 
5.5%
역 246
 
5.4%
시 241
 
5.3%
구 241
 
5.3%
광 241
 
5.3%
Other values (156) 1988
43.5%
Common
ValueCountFrequency (%)
1242
39.3%
1 291
 
9.2%
) 246
 
7.8%
( 246
 
7.8%
, 189
 
6.0%
2 188
 
5.9%
3 145
 
4.6%
0 119
 
3.8%
4 105
 
3.3%
5 80
 
2.5%
Other values (6) 313
 
9.9%
Latin
ValueCountFrequency (%)
B 4
33.3%
K 1
 
8.3%
A 1
 
8.3%
J 1
 
8.3%
T 1
 
8.3%
o 1
 
8.3%
w 1
 
8.3%
e 1
 
8.3%
r 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4570
59.0%
ASCII 3176
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1242
39.1%
1 291
 
9.2%
) 246
 
7.7%
( 246
 
7.7%
, 189
 
6.0%
2 188
 
5.9%
3 145
 
4.6%
0 119
 
3.7%
4 105
 
3.3%
5 80
 
2.5%
Other values (15) 325
 
10.2%
Hangul
ValueCountFrequency (%)
인 320
 
7.0%
미 264
 
5.8%
홀 263
 
5.8%
동 258
 
5.6%
추 257
 
5.6%
천 251
 
5.5%
역 246
 
5.4%
시 241
 
5.3%
구 241
 
5.3%
광 241
 
5.3%
Other values (156) 1988
43.5%

소재지(지번)
Text

Distinct233
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T07:29:16.450118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length45
Mean length24.418033
Min length19

Characters and Unicode

Total characters5958
Distinct characters139
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

Unique227 ?
Unique (%)93.0%

Sample

1st row인천광역시 미추홀구 주안동 1315-19 남부상가3동9호
2nd row인천광역시 미추홀구 숭의동 408-8
3rd row인천광역시 미추홀구 숭의동 301-73
4th row인천광역시 미추홀구 도화동 634-17
5th row인천광역시 미추홀구 주안동 292
ValueCountFrequency (%)
인천광역시 244
21.4%
미추홀구 244
21.4%
주안동 88
 
7.7%
용현동 72
 
6.3%
도화동 28
 
2.5%
학익동 21
 
1.8%
숭의동 20
 
1.8%
1층 14
 
1.2%
2층 10
 
0.9%
관교동 8
 
0.7%
Other values (315) 390
34.2%
2024-04-30T07:29:16.977191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1111
18.6%
1 301
 
5.1%
인 257
 
4.3%
미 256
 
4.3%
천 252
 
4.2%
홀 251
 
4.2%
역 250
 
4.2%
추 250
 
4.2%
동 250
 
4.2%
광 245
 
4.1%
Other values (129) 2535
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3371
56.6%
Decimal Number 1213
 
20.4%
Space Separator 1111
 
18.6%
Dash Punctuation 223
 
3.7%
Other Punctuation 21
 
0.4%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Uppercase Letter 5
 
0.1%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 257
 
7.6%
미 256
 
7.6%
천 252
 
7.5%
홀 251
 
7.4%
역 250
 
7.4%
추 250
 
7.4%
동 250
 
7.4%
광 245
 
7.3%
시 245
 
7.3%
구 244
 
7.2%
Other values (106) 871
25.8%
Decimal Number
ValueCountFrequency (%)
1 301
24.8%
2 149
12.3%
4 115
 
9.5%
3 113
 
9.3%
6 102
 
8.4%
5 100
 
8.2%
0 91
 
7.5%
8 87
 
7.2%
9 86
 
7.1%
7 69
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
K 1
20.0%
J 1
20.0%
T 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
25.0%
o 1
25.0%
e 1
25.0%
r 1
25.0%
Space Separator
ValueCountFrequency (%)
1111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 223
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3371
56.6%
Common 2578
43.3%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 257
 
7.6%
미 256
 
7.6%
천 252
 
7.5%
홀 251
 
7.4%
역 250
 
7.4%
추 250
 
7.4%
동 250
 
7.4%
광 245
 
7.3%
시 245
 
7.3%
구 244
 
7.2%
Other values (106) 871
25.8%
Common
ValueCountFrequency (%)
1111
43.1%
1 301
 
11.7%
- 223
 
8.7%
2 149
 
5.8%
4 115
 
4.5%
3 113
 
4.4%
6 102
 
4.0%
5 100
 
3.9%
0 91
 
3.5%
8 87
 
3.4%
Other values (5) 186
 
7.2%
Latin
ValueCountFrequency (%)
B 2
22.2%
K 1
11.1%
w 1
11.1%
J 1
11.1%
T 1
11.1%
o 1
11.1%
e 1
11.1%
r 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3371
56.6%
ASCII 2587
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1111
42.9%
1 301
 
11.6%
- 223
 
8.6%
2 149
 
5.8%
4 115
 
4.4%
3 113
 
4.4%
6 102
 
3.9%
5 100
 
3.9%
0 91
 
3.5%
8 87
 
3.4%
Other values (13) 195
 
7.5%
Hangul
ValueCountFrequency (%)
인 257
 
7.6%
미 256
 
7.6%
천 252
 
7.5%
홀 251
 
7.4%
역 250
 
7.4%
추 250
 
7.4%
동 250
 
7.4%
광 245
 
7.3%
시 245
 
7.3%
구 244
 
7.2%
Other values (106) 871
25.8%

Missing values

2024-04-30T07:29:14.510295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:29:14.594755image/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

업종명업태명업소명소재지(도로명)소재지(지번)
0일반음식점중국식참설렁탕인천광역시 미추홀구 인하로 274-30 (주안동,남부상가3동9호)인천광역시 미추홀구 주안동 1315-19 남부상가3동9호
1일반음식점중국식영화반점인천광역시 미추홀구 인중로 18, 1층 (숭의동)인천광역시 미추홀구 숭의동 408-8
2일반음식점중국식동락반점인천광역시 미추홀구 독배로 473 (숭의동)인천광역시 미추홀구 숭의동 301-73
3일반음식점중국식경안각인천광역시 미추홀구 경인로 182-1 (도화동)인천광역시 미추홀구 도화동 634-17
4일반음식점중국식해성장<NA>인천광역시 미추홀구 주안동 292
5일반음식점중국식보화장인천광역시 미추홀구 소성로 85 (학익동)인천광역시 미추홀구 학익동 330-11
6일반음식점중국식야래향인천광역시 미추홀구 경원대로858번길 6 (주안동)인천광역시 미추홀구 주안동 951-9
7일반음식점중국식진성각<NA>인천광역시 미추홀구 주안동 583-1584
8일반음식점중국식용운반점인천광역시 미추홀구 경인북길 37-28 (용현동)인천광역시 미추홀구 용현동 211-5
9일반음식점중국식진미식당인천광역시 미추홀구 아암대로253번길 31 (학익동,,69)인천광역시 미추홀구 학익동 587-68 ,69
업종명업태명업소명소재지(도로명)소재지(지번)
234일반음식점중국식공룡인천광역시 미추홀구 경인남길30번길 50, 1층 일부호 (용현동)인천광역시 미추홀구 용현동 191-90
235일반음식점중국식우육미엔 롯데인천점인천광역시 미추홀구 연남로 35, 인천종합터미널,롯데백화점 지하1층 식품관호 (관교동)인천광역시 미추홀구 관교동 15 인천종합터미널,롯데백화점
236일반음식점중국식호우섬 롯데인천점인천광역시 미추홀구 연남로 35, 인천종합터미널,롯데백화점(식품관) 지하1층 (관교동)인천광역시 미추홀구 관교동 15 인천종합터미널,롯데백화점
237일반음식점중국식소복관인천광역시 미추홀구 경인로 372, 201동 지하2층 B2030호 (주안동, 포레나 미추홀)인천광역시 미추홀구 주안동 0 포레나 미추홀
238일반음식점중국식마라혁명인천광역시 미추홀구 한나루로501번길 26, 용남 프라자 1층 동쪽 첫번째칸 103호 (용현동)인천광역시 미추홀구 용현동 3-29 용남 프라자
239일반음식점중국식마라홍마라탕인천광역시 미추홀구 숙골로 104, 와이지프라자 103호 (도화동)인천광역시 미추홀구 도화동 1006-2 와이지프라자
240일반음식점중국식가오씽인천광역시 미추홀구 경인로 372, 지2층 2122호,2123호 (주안동, 포레나 미추홀)인천광역시 미추홀구 주안동 0 포레나 미추홀
241일반음식점중국식다미향 마라탕인천광역시 미추홀구 경원대로670번길 22, 1층 101호 (관교동)인천광역시 미추홀구 관교동 487-16
242일반음식점중국식홍란 인천용현점인천광역시 미추홀구 낙섬중로 112, 씨티맥 1층 우측호 (용현동)인천광역시 미추홀구 용현동 558-36 씨티맥
243일반음식점중국식니루숯불구이인천광역시 미추홀구 주안로 136, 1층 101호 (주안동)인천광역시 미추홀구 주안동 113-1