Overview

Dataset statistics

Number of variables5
Number of observations34
Missing cells5
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.9 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 기타식품판매업 현황입니다.
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15084137/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 5 (14.7%) missing valuesMissing
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:49:48.553537
Analysis finished2023-12-12 01:49:49.078333
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
기타식품판매업
34 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 34
100.0%

Length

2023-12-12T10:49:49.174453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:49:49.312573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 34
100.0%

업소명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T10:49:49.584883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16.5
Mean length10.529412
Min length3

Characters and Unicode

Total characters358
Distinct characters103
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row(주)지에스리테일 지에스더프레쉬 인천부개점
2nd row(주)지에스리테일 GS슈퍼 인천삼산점
3rd row지에스더프레시(GS THE FRESH) 인천마장점
4th row주식회사 두리할인마트
5th row산곡 식자재마트
ValueCountFrequency (%)
주)지에스리테일 3
 
5.7%
주식회사 3
 
5.7%
gs슈퍼 2
 
3.8%
인천삼산점 1
 
1.9%
엠패스트 1
 
1.9%
농민유통 1
 
1.9%
홈마트(산곡점 1
 
1.9%
플러스식자재마트 1
 
1.9%
부평산곡점 1
 
1.9%
m마트 1
 
1.9%
Other values (38) 38
71.7%
2023-12-12T10:49:50.105106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 23
 
6.4%
마 23
 
6.4%
19
 
5.3%
주 15
 
4.2%
) 14
 
3.9%
( 13
 
3.6%
점 13
 
3.6%
데 11
 
3.1%
롯 10
 
2.8%
식 10
 
2.8%
Other values (93) 207
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
81.8%
Space Separator 19
 
5.3%
Uppercase Letter 15
 
4.2%
Close Punctuation 14
 
3.9%
Open Punctuation 13
 
3.6%
Decimal Number 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 23
 
7.8%
마 23
 
7.8%
주 15
 
5.1%
점 13
 
4.4%
데 11
 
3.8%
롯 10
 
3.4%
식 10
 
3.4%
스 9
 
3.1%
부 8
 
2.7%
리 7
 
2.4%
Other values (79) 164
56.0%
Uppercase Letter
ValueCountFrequency (%)
S 4
26.7%
G 3
20.0%
E 2
13.3%
H 2
13.3%
R 1
 
6.7%
F 1
 
6.7%
M 1
 
6.7%
T 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
81.8%
Common 50
 
14.0%
Latin 15
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 23
 
7.8%
마 23
 
7.8%
주 15
 
5.1%
점 13
 
4.4%
데 11
 
3.8%
롯 10
 
3.4%
식 10
 
3.4%
스 9
 
3.1%
부 8
 
2.7%
리 7
 
2.4%
Other values (79) 164
56.0%
Latin
ValueCountFrequency (%)
S 4
26.7%
G 3
20.0%
E 2
13.3%
H 2
13.3%
R 1
 
6.7%
F 1
 
6.7%
M 1
 
6.7%
T 1
 
6.7%
Common
ValueCountFrequency (%)
19
38.0%
) 14
28.0%
( 13
26.0%
0 2
 
4.0%
1 1
 
2.0%
4 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
81.8%
ASCII 65
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 23
 
7.8%
마 23
 
7.8%
주 15
 
5.1%
점 13
 
4.4%
데 11
 
3.8%
롯 10
 
3.4%
식 10
 
3.4%
스 9
 
3.1%
부 8
 
2.7%
리 7
 
2.4%
Other values (79) 164
56.0%
ASCII
ValueCountFrequency (%)
19
29.2%
) 14
21.5%
( 13
20.0%
S 4
 
6.2%
G 3
 
4.6%
E 2
 
3.1%
0 2
 
3.1%
H 2
 
3.1%
R 1
 
1.5%
F 1
 
1.5%
Other values (4) 4
 
6.2%

소재지(도로명)
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T10:49:50.485513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length32.264706
Min length22

Characters and Unicode

Total characters1097
Distinct characters98
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

Unique34 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부개로 10 (부개동 1층 2층)
2nd row인천광역시 부평구 영성중로15번길 12 (삼산동 (1층))
3rd row인천광역시 부평구 마장로242번길 19 (산곡동 (101호~108호))
4th row인천광역시 부평구 부흥로 351 1층 (부평동 부일프라자)
5th row인천광역시 부평구 마장로 178 1~2층 (산곡동 형제빌딩)
ValueCountFrequency (%)
인천광역시 34
 
15.5%
부평구 34
 
15.5%
1층 16
 
7.3%
산곡동 8
 
3.7%
부평동 7
 
3.2%
삼산동 5
 
2.3%
부개동 5
 
2.3%
청천동 4
 
1.8%
2층 4
 
1.8%
영성동로 3
 
1.4%
Other values (86) 99
45.2%
2023-12-12T10:49:51.033451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
214
19.5%
1 60
 
5.5%
부 58
 
5.3%
평 44
 
4.0%
동 43
 
3.9%
천 41
 
3.7%
) 38
 
3.5%
( 38
 
3.5%
인 35
 
3.2%
광 35
 
3.2%
Other values (88) 491
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 621
56.6%
Space Separator 214
 
19.5%
Decimal Number 171
 
15.6%
Close Punctuation 38
 
3.5%
Open Punctuation 38
 
3.5%
Math Symbol 6
 
0.5%
Uppercase Letter 5
 
0.5%
Dash Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 58
 
9.3%
평 44
 
7.1%
동 43
 
6.9%
천 41
 
6.6%
인 35
 
5.6%
광 35
 
5.6%
시 35
 
5.6%
로 35
 
5.6%
역 34
 
5.5%
구 34
 
5.5%
Other values (72) 227
36.6%
Decimal Number
ValueCountFrequency (%)
1 60
35.1%
2 25
14.6%
3 16
 
9.4%
5 15
 
8.8%
7 13
 
7.6%
0 10
 
5.8%
9 9
 
5.3%
4 9
 
5.3%
6 9
 
5.3%
8 5
 
2.9%
Space Separator
ValueCountFrequency (%)
214
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 621
56.6%
Common 471
42.9%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 58
 
9.3%
평 44
 
7.1%
동 43
 
6.9%
천 41
 
6.6%
인 35
 
5.6%
광 35
 
5.6%
시 35
 
5.6%
로 35
 
5.6%
역 34
 
5.5%
구 34
 
5.5%
Other values (72) 227
36.6%
Common
ValueCountFrequency (%)
214
45.4%
1 60
 
12.7%
) 38
 
8.1%
( 38
 
8.1%
2 25
 
5.3%
3 16
 
3.4%
5 15
 
3.2%
7 13
 
2.8%
0 10
 
2.1%
9 9
 
1.9%
Other values (5) 33
 
7.0%
Latin
ValueCountFrequency (%)
B 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 621
56.6%
ASCII 476
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
214
45.0%
1 60
 
12.6%
) 38
 
8.0%
( 38
 
8.0%
2 25
 
5.3%
3 16
 
3.4%
5 15
 
3.2%
7 13
 
2.7%
0 10
 
2.1%
9 9
 
1.9%
Other values (6) 38
 
8.0%
Hangul
ValueCountFrequency (%)
부 58
 
9.3%
평 44
 
7.1%
동 43
 
6.9%
천 41
 
6.6%
인 35
 
5.6%
광 35
 
5.6%
시 35
 
5.6%
로 35
 
5.6%
역 34
 
5.5%
구 34
 
5.5%
Other values (72) 227
36.6%

소재지(지번)
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T10:49:51.360339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length25.647059
Min length17

Characters and Unicode

Total characters872
Distinct characters72
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

Unique34 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부개동 501-8 1층 2층
2nd row인천광역시 부평구 삼산동 123 (1층)
3rd row인천광역시 부평구 산곡동 251-4 (101호~108호)
4th row인천광역시 부평구 부평동 126-8 부일프라자 1층
5th row인천광역시 부평구 산곡동 369-15 형제빌딩 1~2층
ValueCountFrequency (%)
인천광역시 34
18.6%
부평구 34
18.6%
1층 14
 
7.7%
산곡동 8
 
4.4%
부평동 7
 
3.8%
부개동 5
 
2.7%
삼산동 5
 
2.7%
2층 4
 
2.2%
청천동 4
 
2.2%
일부 3
 
1.6%
Other values (61) 65
35.5%
2023-12-12T10:49:51.865502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
17.7%
1 73
 
8.4%
부 51
 
5.8%
평 41
 
4.7%
천 38
 
4.4%
동 38
 
4.4%
시 35
 
4.0%
구 34
 
3.9%
인 34
 
3.9%
광 34
 
3.9%
Other values (62) 340
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
54.1%
Decimal Number 198
22.7%
Space Separator 154
 
17.7%
Dash Punctuation 28
 
3.2%
Close Punctuation 5
 
0.6%
Math Symbol 5
 
0.6%
Open Punctuation 5
 
0.6%
Uppercase Letter 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 51
10.8%
평 41
 
8.7%
천 38
 
8.1%
동 38
 
8.1%
시 35
 
7.4%
구 34
 
7.2%
인 34
 
7.2%
광 34
 
7.2%
역 34
 
7.2%
층 21
 
4.4%
Other values (46) 112
23.7%
Decimal Number
ValueCountFrequency (%)
1 73
36.9%
2 24
 
12.1%
0 18
 
9.1%
3 16
 
8.1%
5 15
 
7.6%
7 12
 
6.1%
8 11
 
5.6%
9 11
 
5.6%
4 10
 
5.1%
6 8
 
4.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
54.1%
Common 395
45.3%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 51
10.8%
평 41
 
8.7%
천 38
 
8.1%
동 38
 
8.1%
시 35
 
7.4%
구 34
 
7.2%
인 34
 
7.2%
광 34
 
7.2%
역 34
 
7.2%
층 21
 
4.4%
Other values (46) 112
23.7%
Common
ValueCountFrequency (%)
154
39.0%
1 73
18.5%
- 28
 
7.1%
2 24
 
6.1%
0 18
 
4.6%
3 16
 
4.1%
5 15
 
3.8%
7 12
 
3.0%
8 11
 
2.8%
9 11
 
2.8%
Other values (5) 33
 
8.4%
Latin
ValueCountFrequency (%)
B 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
54.1%
ASCII 400
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
38.5%
1 73
18.2%
- 28
 
7.0%
2 24
 
6.0%
0 18
 
4.5%
3 16
 
4.0%
5 15
 
3.8%
7 12
 
3.0%
8 11
 
2.8%
9 11
 
2.8%
Other values (6) 38
 
9.5%
Hangul
ValueCountFrequency (%)
부 51
10.8%
평 41
 
8.7%
천 38
 
8.1%
동 38
 
8.1%
시 35
 
7.4%
구 34
 
7.2%
인 34
 
7.2%
광 34
 
7.2%
역 34
 
7.2%
층 21
 
4.4%
Other values (46) 112
23.7%

소재지전화
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing5
Missing (%)14.7%
Memory size404.0 B
2023-12-12T10:49:52.157772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row032-506-2004
2nd row032-330-3230
3rd row032-505-8225
4th row032-546-1234
5th row032-512-5945
ValueCountFrequency (%)
032-506-2004 1
 
3.4%
032-573-2001 1
 
3.4%
032-527-8833 1
 
3.4%
032-502-4771 1
 
3.4%
032-361-8860 1
 
3.4%
032-503-3230 1
 
3.4%
032-509-2500 1
 
3.4%
032-330-1113 1
 
3.4%
032-507-2345 1
 
3.4%
032-452-2000 1
 
3.4%
Other values (19) 19
65.5%
2023-12-12T10:49:52.654558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
17.5%
2 58
16.7%
- 58
16.7%
3 53
15.2%
5 41
11.8%
1 19
 
5.5%
4 18
 
5.2%
8 14
 
4.0%
6 11
 
3.2%
7 10
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
21.0%
2 58
20.0%
3 53
18.3%
5 41
14.1%
1 19
 
6.6%
4 18
 
6.2%
8 14
 
4.8%
6 11
 
3.8%
7 10
 
3.4%
9 5
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
17.5%
2 58
16.7%
- 58
16.7%
3 53
15.2%
5 41
11.8%
1 19
 
5.5%
4 18
 
5.2%
8 14
 
4.0%
6 11
 
3.2%
7 10
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
17.5%
2 58
16.7%
- 58
16.7%
3 53
15.2%
5 41
11.8%
1 19
 
5.5%
4 18
 
5.2%
8 14
 
4.0%
6 11
 
3.2%
7 10
 
2.9%

Correlations

2023-12-12T10:49:52.807544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지(지번)소재지전화
업소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-12T10:49:48.882647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:49:49.036305image/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

업종명업소명소재지(도로명)소재지(지번)소재지전화
0기타식품판매업(주)지에스리테일 지에스더프레쉬 인천부개점인천광역시 부평구 부개로 10 (부개동 1층 2층)인천광역시 부평구 부개동 501-8 1층 2층032-506-2004
1기타식품판매업(주)지에스리테일 GS슈퍼 인천삼산점인천광역시 부평구 영성중로15번길 12 (삼산동 (1층))인천광역시 부평구 삼산동 123 (1층)<NA>
2기타식품판매업지에스더프레시(GS THE FRESH) 인천마장점인천광역시 부평구 마장로242번길 19 (산곡동 (101호~108호))인천광역시 부평구 산곡동 251-4 (101호~108호)032-330-3230
3기타식품판매업주식회사 두리할인마트인천광역시 부평구 부흥로 351 1층 (부평동 부일프라자)인천광역시 부평구 부평동 126-8 부일프라자 1층032-505-8225
4기타식품판매업산곡 식자재마트인천광역시 부평구 마장로 178 1~2층 (산곡동 형제빌딩)인천광역시 부평구 산곡동 369-15 형제빌딩 1~2층032-546-1234
5기타식품판매업하모니마트인천광역시 부평구 부흥북로5번길 9 가동 1층 (부평동)인천광역시 부평구 부평동 431-48 1층 가동<NA>
6기타식품판매업하이웨이클럽 청천점인천광역시 부평구 세월천로 9 1층 일부 2층 일부호 (청천동)인천광역시 부평구 청천동 191-9 1층 일부 2층 일부032-512-5945
7기타식품판매업푸르지오우리마트인천광역시 부평구 세월천로 16 (청천동 대우2차상가 B101호)인천광역시 부평구 청천동 176 대우2차상가 B101호032-525-3112
8기타식품판매업주)세진식자재인천광역시 부평구 영성동로 36-23 (삼산동 1층)인천광역시 부평구 삼산동 508-1 외1필지 1층032-567-0602
9기타식품판매업현대그린마트인천광역시 부평구 백범로422번길 57 (십정동 B동 1층)인천광역시 부평구 십정동 520-15 B동 1층032-429-4411
업종명업소명소재지(도로명)소재지(지번)소재지전화
24기타식품판매업부평식자재마트인천광역시 부평구 신트리로8번길 30 1층 (부평동)인천광역시 부평구 부평동 417-6 1층032-507-2345
25기타식품판매업(주)윈플러스마트남부 부개점인천광역시 부평구 수변로57번길 9 1 2층 (부개동)인천광역시 부평구 부개동 513 1 2층032-330-1113
26기타식품판매업롯데쇼핑(주) 롯데마트부평점인천광역시 부평구 마장로 296 (산곡동)인천광역시 부평구 산곡동 159-52032-509-2500
27기타식품판매업즐거운마트인천광역시 부평구 길주로494번길 59 1층 (부평동)인천광역시 부평구 부평동 799 1층032-503-3230
28기타식품판매업(주)제일식자재마트인천광역시 부평구 동수로 153 1~2층 (부개동 부개동판매시설 주건축물제1동)인천광역시 부평구 부개동 260-4 외 5필지 부개동판매시설 주건축물제1동 1~2층032-361-8860
29기타식품판매업M마트인천광역시 부평구 길주남로 135 (부개동 (1층))인천광역시 부평구 부개동 12-171 (1층)032-502-4771
30기타식품판매업(주)지에스리테일 GS슈퍼 부평산곡점인천광역시 부평구 원적로432번길 10 (산곡동)인천광역시 부평구 산곡동 137-1032-527-8833
31기타식품판매업플러스식자재마트인천광역시 부평구 주부토로 116 1층 (부평동)인천광역시 부평구 부평동 890-1032-521-3256
32기타식품판매업홈마트(산곡점)인천광역시 부평구 부흥로173번길 55 1층 (산곡동)인천광역시 부평구 산곡동 284-20<NA>
33기타식품판매업에이스마트인천광역시 부평구 백운로 53 1층 101~107호 (십정동 파크타운1차)인천광역시 부평구 십정동 182-19 파크타운1차 1층 101~107호<NA>