Overview

Dataset statistics

Number of variables4
Number of observations191
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory32.7 B

Variable types

Text4

Dataset

Description전북특별자치도 군산시에 소재한 식품 제조가공 업체 현황에 대한 데이터로 업소명 소재지주소 전화번호 등의 항목을 제공합니다.
Author전북특별자치도 군산시
URLhttps://www.data.go.kr/data/15042642/fileData.do

Reproduction

Analysis started2024-03-14 16:16:26.615066
Analysis finished2024-03-14 16:16:27.727537
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct190
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T01:16:28.769089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length7.6439791
Min length2

Characters and Unicode

Total characters1460
Distinct characters256
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

Unique189 ?
Unique (%)99.0%

Sample

1st row동양식품
2nd row거성냉장
3rd row군산얼음(거성냉장 해망점)
4th row군산시수협비응제빙사업팀
5th row정수식품
ValueCountFrequency (%)
주식회사 14
 
5.8%
농업회사법인 8
 
3.3%
유한회사 5
 
2.1%
어업회사법인 3
 
1.2%
영어조합법인 3
 
1.2%
주)건어물타임 2
 
0.8%
부흥농산 2
 
0.8%
주 2
 
0.8%
영농조합법인 2
 
0.8%
두비주식회사 1
 
0.4%
Other values (201) 201
82.7%
2024-03-15T01:16:30.275036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 64
 
4.4%
주 53
 
3.6%
사 53
 
3.6%
회 52
 
3.6%
52
 
3.6%
) 51
 
3.5%
( 50
 
3.4%
산 49
 
3.4%
품 40
 
2.7%
농 34
 
2.3%
Other values (246) 962
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1301
89.1%
Space Separator 52
 
3.6%
Close Punctuation 51
 
3.5%
Open Punctuation 50
 
3.4%
Decimal Number 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 64
 
4.9%
주 53
 
4.1%
사 53
 
4.1%
회 52
 
4.0%
산 49
 
3.8%
품 40
 
3.1%
농 34
 
2.6%
인 34
 
2.6%
유 33
 
2.5%
법 31
 
2.4%
Other values (238) 858
65.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
T 1
33.3%
G 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1301
89.1%
Common 156
 
10.7%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 64
 
4.9%
주 53
 
4.1%
사 53
 
4.1%
회 52
 
4.0%
산 49
 
3.8%
품 40
 
3.1%
농 34
 
2.6%
인 34
 
2.6%
유 33
 
2.5%
법 31
 
2.4%
Other values (238) 858
65.9%
Common
ValueCountFrequency (%)
52
33.3%
) 51
32.7%
( 50
32.1%
2 2
 
1.3%
3 1
 
0.6%
Latin
ValueCountFrequency (%)
B 1
33.3%
T 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1301
89.1%
ASCII 159
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 64
 
4.9%
주 53
 
4.1%
사 53
 
4.1%
회 52
 
4.0%
산 49
 
3.8%
품 40
 
3.1%
농 34
 
2.6%
인 34
 
2.6%
유 33
 
2.5%
법 31
 
2.4%
Other values (238) 858
65.9%
ASCII
ValueCountFrequency (%)
52
32.7%
) 51
32.1%
( 50
31.4%
2 2
 
1.3%
B 1
 
0.6%
T 1
 
0.6%
G 1
 
0.6%
3 1
 
0.6%

소재지도로명주소
Text

Distinct190
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T01:16:30.991636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length23.759162
Min length17

Characters and Unicode

Total characters4538
Distinct characters191
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)99.0%

Sample

1st row전북특별자치도 중앙로 48 (대명동)
2nd row전북특별자치도 공항로 18 (소룡동)
3rd row전북특별자치도 내항2길 283 (해망동)
4th row전북특별자치도 비응도동 112
5th row전북특별자치도 조촌안5길 31 (경장동)
ValueCountFrequency (%)
전북특별자치도 191
 
22.1%
성산면 21
 
2.4%
서수면 17
 
2.0%
1층 17
 
2.0%
1동 13
 
1.5%
옥구읍 12
 
1.4%
소룡동 12
 
1.4%
2층 11
 
1.3%
산북동 11
 
1.3%
해망동 11
 
1.3%
Other values (352) 550
63.5%
2024-03-15T01:16:32.053195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
750
 
16.5%
도 209
 
4.6%
북 208
 
4.6%
자 197
 
4.3%
치 194
 
4.3%
전 193
 
4.3%
특 191
 
4.2%
별 191
 
4.2%
1 168
 
3.7%
동 145
 
3.2%
Other values (181) 2092
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2805
61.8%
Space Separator 750
 
16.5%
Decimal Number 714
 
15.7%
Open Punctuation 101
 
2.2%
Close Punctuation 101
 
2.2%
Dash Punctuation 62
 
1.4%
Other Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 209
 
7.5%
북 208
 
7.4%
자 197
 
7.0%
치 194
 
6.9%
전 193
 
6.9%
특 191
 
6.8%
별 191
 
6.8%
동 145
 
5.2%
길 101
 
3.6%
로 88
 
3.1%
Other values (163) 1088
38.8%
Decimal Number
ValueCountFrequency (%)
1 168
23.5%
2 139
19.5%
3 93
13.0%
4 65
 
9.1%
5 47
 
6.6%
7 47
 
6.6%
6 44
 
6.2%
0 42
 
5.9%
8 39
 
5.5%
9 30
 
4.2%
Space Separator
ValueCountFrequency (%)
750
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2806
61.8%
Common 1731
38.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 209
 
7.4%
북 208
 
7.4%
자 197
 
7.0%
치 194
 
6.9%
전 193
 
6.9%
특 191
 
6.8%
별 191
 
6.8%
동 145
 
5.2%
길 101
 
3.6%
로 88
 
3.1%
Other values (164) 1089
38.8%
Common
ValueCountFrequency (%)
750
43.3%
1 168
 
9.7%
2 139
 
8.0%
( 101
 
5.8%
) 101
 
5.8%
3 93
 
5.4%
4 65
 
3.8%
- 62
 
3.6%
5 47
 
2.7%
7 47
 
2.7%
Other values (6) 158
 
9.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2805
61.8%
ASCII 1732
38.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
750
43.3%
1 168
 
9.7%
2 139
 
8.0%
( 101
 
5.8%
) 101
 
5.8%
3 93
 
5.4%
4 65
 
3.8%
- 62
 
3.6%
5 47
 
2.7%
7 47
 
2.7%
Other values (7) 159
 
9.2%
Hangul
ValueCountFrequency (%)
도 209
 
7.5%
북 208
 
7.4%
자 197
 
7.0%
치 194
 
6.9%
전 193
 
6.9%
특 191
 
6.8%
별 191
 
6.8%
동 145
 
5.2%
길 101
 
3.6%
로 88
 
3.1%
Other values (163) 1088
38.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지지번주소
Text

Distinct188
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T01:16:32.800562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length20.612565
Min length14

Characters and Unicode

Total characters3937
Distinct characters149
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)96.9%

Sample

1st row전북특별자치도대명동 385-70
2nd row전북특별자치도소룡동 921
3rd row전북특별자치도해망동 1000-132
4th row전북특별자치도비응도동 112
5th row전북특별자치도경장동 202-8
ValueCountFrequency (%)
전북특별자치도성산면 21
 
3.9%
전북특별자치도서수면 17
 
3.1%
전북특별자치도소룡동 12
 
2.2%
전북특별자치도옥구읍 12
 
2.2%
전북특별자치도해망동 11
 
2.0%
마룡리 11
 
2.0%
전북특별자치도산북동 11
 
2.0%
전북특별자치도나운동 10
 
1.8%
전북특별자치도수송동 9
 
1.7%
전북특별자치도회현면 9
 
1.7%
Other values (293) 419
77.3%
2024-03-15T01:16:34.027174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
536
 
13.6%
도 206
 
5.2%
북 204
 
5.2%
치 192
 
4.9%
전 192
 
4.9%
자 191
 
4.9%
별 191
 
4.9%
특 191
 
4.9%
1 190
 
4.8%
- 162
 
4.1%
Other values (139) 1682
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2385
60.6%
Decimal Number 847
 
21.5%
Space Separator 536
 
13.6%
Dash Punctuation 162
 
4.1%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 206
 
8.6%
북 204
 
8.6%
치 192
 
8.1%
전 192
 
8.1%
자 191
 
8.0%
별 191
 
8.0%
특 191
 
8.0%
동 127
 
5.3%
리 89
 
3.7%
면 80
 
3.4%
Other values (124) 722
30.3%
Decimal Number
ValueCountFrequency (%)
1 190
22.4%
2 107
12.6%
3 89
10.5%
9 80
9.4%
4 73
 
8.6%
5 71
 
8.4%
7 62
 
7.3%
0 59
 
7.0%
6 58
 
6.8%
8 58
 
6.8%
Space Separator
ValueCountFrequency (%)
536
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2385
60.6%
Common 1551
39.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 206
 
8.6%
북 204
 
8.6%
치 192
 
8.1%
전 192
 
8.1%
자 191
 
8.0%
별 191
 
8.0%
특 191
 
8.0%
동 127
 
5.3%
리 89
 
3.7%
면 80
 
3.4%
Other values (124) 722
30.3%
Common
ValueCountFrequency (%)
536
34.6%
1 190
 
12.3%
- 162
 
10.4%
2 107
 
6.9%
3 89
 
5.7%
9 80
 
5.2%
4 73
 
4.7%
5 71
 
4.6%
7 62
 
4.0%
0 59
 
3.8%
Other values (4) 122
 
7.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2385
60.6%
ASCII 1552
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
536
34.5%
1 190
 
12.2%
- 162
 
10.4%
2 107
 
6.9%
3 89
 
5.7%
9 80
 
5.2%
4 73
 
4.7%
5 71
 
4.6%
7 62
 
4.0%
0 59
 
3.8%
Other values (5) 123
 
7.9%
Hangul
ValueCountFrequency (%)
도 206
 
8.6%
북 204
 
8.6%
치 192
 
8.1%
전 192
 
8.1%
자 191
 
8.0%
별 191
 
8.0%
특 191
 
8.0%
동 127
 
5.3%
리 89
 
3.7%
면 80
 
3.4%
Other values (124) 722
30.3%

소재지전화
Text

Distinct126
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T01:16:35.592159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.026178
Min length6

Characters and Unicode

Total characters2106
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)65.4%

Sample

1st row063-445-9364
2nd row063-467-7301
3rd row063 -467 -0008
4th row063- 462-0157
5th row063- 452-5891
ValueCountFrequency (%)
063 105
27.7%
데이터미집계 66
17.4%
466 10
 
2.6%
453 10
 
2.6%
467 6
 
1.6%
451 6
 
1.6%
446 6
 
1.6%
464 4
 
1.1%
445 4
 
1.1%
443 4
 
1.1%
Other values (147) 158
41.7%
2024-03-15T01:16:38.057264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 250
11.9%
6 234
11.1%
208
9.9%
3 203
9.6%
0 196
 
9.3%
4 187
 
8.9%
5 109
 
5.2%
1 85
 
4.0%
2 72
 
3.4%
7 66
 
3.1%
Other values (8) 496
23.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1252
59.4%
Other Letter 396
 
18.8%
Dash Punctuation 250
 
11.9%
Space Separator 208
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 234
18.7%
3 203
16.2%
0 196
15.7%
4 187
14.9%
5 109
8.7%
1 85
 
6.8%
2 72
 
5.8%
7 66
 
5.3%
8 63
 
5.0%
9 37
 
3.0%
Other Letter
ValueCountFrequency (%)
데 66
16.7%
이 66
16.7%
계 66
16.7%
집 66
16.7%
미 66
16.7%
터 66
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1710
81.2%
Hangul 396
 
18.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 250
14.6%
6 234
13.7%
208
12.2%
3 203
11.9%
0 196
11.5%
4 187
10.9%
5 109
6.4%
1 85
 
5.0%
2 72
 
4.2%
7 66
 
3.9%
Other values (2) 100
 
5.8%
Hangul
ValueCountFrequency (%)
데 66
16.7%
이 66
16.7%
계 66
16.7%
집 66
16.7%
미 66
16.7%
터 66
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1710
81.2%
Hangul 396
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 250
14.6%
6 234
13.7%
208
12.2%
3 203
11.9%
0 196
11.5%
4 187
10.9%
5 109
6.4%
1 85
 
5.0%
2 72
 
4.2%
7 66
 
3.9%
Other values (2) 100
 
5.8%
Hangul
ValueCountFrequency (%)
데 66
16.7%
이 66
16.7%
계 66
16.7%
집 66
16.7%
미 66
16.7%
터 66
16.7%

Missing values

2024-03-15T01:16:27.310999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:16:27.651160image/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

업소명소재지도로명주소소재지지번주소소재지전화
0동양식품전북특별자치도 중앙로 48 (대명동)전북특별자치도대명동 385-70063-445-9364
1거성냉장전북특별자치도 공항로 18 (소룡동)전북특별자치도소룡동 921063-467-7301
2군산얼음(거성냉장 해망점)전북특별자치도 내항2길 283 (해망동)전북특별자치도해망동 1000-132063 -467 -0008
3군산시수협비응제빙사업팀전북특별자치도 비응도동 112전북특별자치도비응도동 112063- 462-0157
4정수식품전북특별자치도 조촌안5길 31 (경장동)전북특별자치도경장동 202-8063- 452-5891
5군산이화식품전북특별자치도 중앙로 65-6 1층 2층 (장재동)전북특별자치도장재동 209-2 1층 2층063-446 -8228
6대영식품전북특별자치도 하신2길 12-6 (나운동)전북특별자치도나운동 823-2063-462-3620
7삼학식품전북특별자치도 성산면 동군산로 13전북특별자치도성산면 고봉리 372-5063- 453-6666
8태정식품전북특별자치도 금암2길 13 (금암동)전북특별자치도금암동 73-122063 -443 -1188
9(주) 대두식품전북특별자치도 서수면 상장곤윗길 23전북특별자치도서수면 마룡리 93-19063 -450 -3500
업소명소재지도로명주소소재지지번주소소재지전화
181선장의식탁전북특별자치도 대학로 226 2동 (나운동)전북특별자치도나운동 669-2 2동데이터미집계
182영농조합법인 늘처음처럼전북특별자치도 서수면 용천로 334-17전북특별자치도서수면 마룡리 93-6063 -453 -9755
183(유)에이원시스템 군산지사전북특별자치도 나운안길 34 나동 101호 (나운동)전북특별자치도나운동 103-13 나동 101호063 -467 -1314
184골든글로리전북특별자치도 토성길 16-7 (사정동)전북특별자치도사정동 525063 -451 -6565
185태화수산전북특별자치도 옥구읍 척동길 71 1동전북특별자치도옥구읍 옥정리 138-4063 -466 -0591
186주식회사 비그룹전북특별자치도 해망로 558 2동 1층 (소룡동)전북특별자치도소룡동 679-3 2동 1층063 -442 -7616
187서우엠에스(주)전북특별자치도 서수면 서라로 185 서우엠에스(주)전북특별자치도서수면 마룡리 865 서우엠에스(주)063 -211 -4522
188(주)브이시티전북특별자치도 서수면 탑천로 621전북특별자치도서수면 서수리 373-1데이터미집계
189(주)카페창업비지니스지원센터전북특별자치도 월명로 209 203호 (수송동)전북특별자치도수송동 820-7 203호063 -468 -9585
190저스트커피로스터즈전북특별자치도 축동2길 40-2 102호 (수송동)전북특별자치도수송동 805 102호063 -467 -2449