Overview

Dataset statistics

Number of variables5
Number of observations346
Missing cells132
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.6 KiB
Average record size in memory40.4 B

Variable types

Text4
DateTime1

Dataset

Description전라북도 정읍시에 소재한 즉석판매제고가공업소 현황중(업소명, 소재지도로명주소, 소재지지번주소, 소재지연락처) 등의 자료를 제공합니다.
Author전라북도 정읍시
URLhttps://www.data.go.kr/data/15047932/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지전화 has 132 (38.2%) missing valuesMissing

Reproduction

Analysis started2023-12-16 15:41:10.484145
Analysis finished2023-12-16 15:41:12.860202
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct342
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-16T15:41:13.782431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length6.2630058
Min length2

Characters and Unicode

Total characters2167
Distinct characters336
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

Unique338 ?
Unique (%)97.7%

Sample

1st row한일기름집
2nd row중앙기름집
3rd row우령떡방앗간
4th row태흥제분소
5th row평화제분소
ValueCountFrequency (%)
정읍점 6
 
1.4%
방앗간 5
 
1.2%
주식회사 5
 
1.2%
건강원 4
 
0.9%
농업회사법인 3
 
0.7%
식품 3
 
0.7%
떡 3
 
0.7%
영농조합법인 2
 
0.5%
로컬/하나로마트 2
 
0.5%
정읍원예농협 2
 
0.5%
Other values (386) 397
91.9%
2023-12-16T15:41:15.598729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
4.0%
원 82
 
3.8%
방 71
 
3.3%
건 66
 
3.0%
강 66
 
3.0%
간 64
 
3.0%
앗 63
 
2.9%
떡 53
 
2.4%
산 38
 
1.8%
정 37
 
1.7%
Other values (326) 1541
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2034
93.9%
Space Separator 86
 
4.0%
Open Punctuation 13
 
0.6%
Close Punctuation 13
 
0.6%
Lowercase Letter 7
 
0.3%
Decimal Number 6
 
0.3%
Other Punctuation 5
 
0.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 82
 
4.0%
방 71
 
3.5%
건 66
 
3.2%
강 66
 
3.2%
간 64
 
3.1%
앗 63
 
3.1%
떡 53
 
2.6%
산 38
 
1.9%
정 37
 
1.8%
이 29
 
1.4%
Other values (307) 1465
72.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
y 1
14.3%
a 1
14.3%
d 1
14.3%
n 1
14.3%
r 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 1
16.7%
1 1
16.7%
6 1
16.7%
4 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 2
40.0%
/ 2
40.0%
, 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
G 2
66.7%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2034
93.9%
Common 123
 
5.7%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 82
 
4.0%
방 71
 
3.5%
건 66
 
3.2%
강 66
 
3.2%
간 64
 
3.1%
앗 63
 
3.1%
떡 53
 
2.6%
산 38
 
1.9%
정 37
 
1.8%
이 29
 
1.4%
Other values (307) 1465
72.0%
Common
ValueCountFrequency (%)
86
69.9%
( 13
 
10.6%
) 13
 
10.6%
& 2
 
1.6%
/ 2
 
1.6%
2 2
 
1.6%
0 1
 
0.8%
1 1
 
0.8%
6 1
 
0.8%
4 1
 
0.8%
Latin
ValueCountFrequency (%)
e 2
20.0%
G 2
20.0%
M 1
10.0%
y 1
10.0%
a 1
10.0%
d 1
10.0%
n 1
10.0%
r 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2034
93.9%
ASCII 133
 
6.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
64.7%
( 13
 
9.8%
) 13
 
9.8%
& 2
 
1.5%
/ 2
 
1.5%
e 2
 
1.5%
2 2
 
1.5%
G 2
 
1.5%
0 1
 
0.8%
1 1
 
0.8%
Other values (9) 9
 
6.8%
Hangul
ValueCountFrequency (%)
원 82
 
4.0%
방 71
 
3.5%
건 66
 
3.2%
강 66
 
3.2%
간 64
 
3.1%
앗 63
 
3.1%
떡 53
 
2.6%
산 38
 
1.9%
정 37
 
1.8%
이 29
 
1.4%
Other values (307) 1465
72.0%

소재지(도로명)
Text

Distinct311
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-16T15:41:17.763239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length23.465318
Min length9

Characters and Unicode

Total characters8119
Distinct characters180
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

Unique295 ?
Unique (%)85.3%

Sample

1st row전라북도 정읍시 신태인읍 시장2길 14
2nd row전라북도 정읍시 신태인읍 시장2길 31
3rd row전라북도 정읍시 신태인읍 정신로 1258
4th row전라북도 정읍시 신태인읍 서태길 86
5th row전라북도 정읍시 신태인읍 평화3길 74
ValueCountFrequency (%)
전라북도 331
 
18.5%
정읍시 331
 
18.5%
시기동 81
 
4.5%
1층 50
 
2.8%
수성동 39
 
2.2%
연지동 33
 
1.8%
상동 30
 
1.7%
신태인읍 29
 
1.6%
초산로 22
 
1.2%
충정로 15
 
0.8%
Other values (432) 833
46.4%
2023-12-16T15:41:20.902604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1450
17.9%
시 430
 
5.3%
정 388
 
4.8%
읍 377
 
4.6%
북 354
 
4.4%
도 334
 
4.1%
전 332
 
4.1%
라 331
 
4.1%
1 291
 
3.6%
동 243
 
3.0%
Other values (170) 3589
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4736
58.3%
Space Separator 1450
 
17.9%
Decimal Number 1138
 
14.0%
Open Punctuation 225
 
2.8%
Close Punctuation 225
 
2.8%
Dash Punctuation 115
 
1.4%
Uppercase Letter 105
 
1.3%
Other Punctuation 95
 
1.2%
Math Symbol 30
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 430
 
9.1%
정 388
 
8.2%
읍 377
 
8.0%
북 354
 
7.5%
도 334
 
7.1%
전 332
 
7.0%
라 331
 
7.0%
동 243
 
5.1%
로 190
 
4.0%
길 152
 
3.2%
Other values (147) 1605
33.9%
Decimal Number
ValueCountFrequency (%)
1 291
25.6%
2 147
12.9%
3 121
10.6%
4 113
 
9.9%
6 113
 
9.9%
5 99
 
8.7%
7 67
 
5.9%
9 66
 
5.8%
0 63
 
5.5%
8 58
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
E 30
28.6%
R 15
14.3%
P 15
14.3%
L 15
14.3%
A 15
14.3%
C 15
14.3%
Math Symbol
ValueCountFrequency (%)
< 15
50.0%
> 15
50.0%
Space Separator
ValueCountFrequency (%)
1450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 225
100.0%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%
Other Punctuation
ValueCountFrequency (%)
, 95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4736
58.3%
Common 3278
40.4%
Latin 105
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 430
 
9.1%
정 388
 
8.2%
읍 377
 
8.0%
북 354
 
7.5%
도 334
 
7.1%
전 332
 
7.0%
라 331
 
7.0%
동 243
 
5.1%
로 190
 
4.0%
길 152
 
3.2%
Other values (147) 1605
33.9%
Common
ValueCountFrequency (%)
1450
44.2%
1 291
 
8.9%
( 225
 
6.9%
) 225
 
6.9%
2 147
 
4.5%
3 121
 
3.7%
- 115
 
3.5%
4 113
 
3.4%
6 113
 
3.4%
5 99
 
3.0%
Other values (7) 379
 
11.6%
Latin
ValueCountFrequency (%)
E 30
28.6%
R 15
14.3%
P 15
14.3%
L 15
14.3%
A 15
14.3%
C 15
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4736
58.3%
ASCII 3383
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1450
42.9%
1 291
 
8.6%
( 225
 
6.7%
) 225
 
6.7%
2 147
 
4.3%
3 121
 
3.6%
- 115
 
3.4%
4 113
 
3.3%
6 113
 
3.3%
5 99
 
2.9%
Other values (13) 484
 
14.3%
Hangul
ValueCountFrequency (%)
시 430
 
9.1%
정 388
 
8.2%
읍 377
 
8.0%
북 354
 
7.5%
도 334
 
7.1%
전 332
 
7.0%
라 331
 
7.0%
동 243
 
5.1%
로 190
 
4.0%
길 152
 
3.2%
Other values (147) 1605
33.9%

소재지(지번)
Text

Distinct316
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-16T15:41:22.443133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length34
Mean length21.395954
Min length15

Characters and Unicode

Total characters7403
Distinct characters167
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)85.5%

Sample

1st row전라북도 정읍시 신태인읍 신태인리 152-8
2nd row전라북도 정읍시 신태인읍 신태인리 150
3rd row전라북도 정읍시 신태인읍 우령리 476-1
4th row전라북도 정읍시 신태인읍 신태인리 406-1
5th row전라북도 정읍시 신태인읍 신태인리 572-6
ValueCountFrequency (%)
전라북도 346
21.9%
정읍시 346
21.9%
시기동 89
 
5.6%
수성동 40
 
2.5%
연지동 34
 
2.2%
신태인읍 31
 
2.0%
상동 30
 
1.9%
신태인리 27
 
1.7%
칠보면 14
 
0.9%
농소동 12
 
0.8%
Other values (425) 611
38.7%
2023-12-16T15:41:24.570101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1576
21.3%
시 444
 
6.0%
읍 378
 
5.1%
정 357
 
4.8%
북 356
 
4.8%
전 349
 
4.7%
라 347
 
4.7%
도 346
 
4.7%
- 296
 
4.0%
1 275
 
3.7%
Other values (157) 2679
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4083
55.2%
Space Separator 1576
 
21.3%
Decimal Number 1437
 
19.4%
Dash Punctuation 296
 
4.0%
Other Punctuation 6
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 444
10.9%
읍 378
 
9.3%
정 357
 
8.7%
북 356
 
8.7%
전 349
 
8.5%
라 347
 
8.5%
도 346
 
8.5%
동 240
 
5.9%
리 118
 
2.9%
기 90
 
2.2%
Other values (141) 1058
25.9%
Decimal Number
ValueCountFrequency (%)
1 275
19.1%
4 181
12.6%
2 164
11.4%
3 156
10.9%
5 143
10.0%
6 125
8.7%
9 110
 
7.7%
0 106
 
7.4%
7 91
 
6.3%
8 86
 
6.0%
Space Separator
ValueCountFrequency (%)
1576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4083
55.2%
Common 3320
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 444
10.9%
읍 378
 
9.3%
정 357
 
8.7%
북 356
 
8.7%
전 349
 
8.5%
라 347
 
8.5%
도 346
 
8.5%
동 240
 
5.9%
리 118
 
2.9%
기 90
 
2.2%
Other values (141) 1058
25.9%
Common
ValueCountFrequency (%)
1576
47.5%
- 296
 
8.9%
1 275
 
8.3%
4 181
 
5.5%
2 164
 
4.9%
3 156
 
4.7%
5 143
 
4.3%
6 125
 
3.8%
9 110
 
3.3%
0 106
 
3.2%
Other values (6) 188
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4083
55.2%
ASCII 3320
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1576
47.5%
- 296
 
8.9%
1 275
 
8.3%
4 181
 
5.5%
2 164
 
4.9%
3 156
 
4.7%
5 143
 
4.3%
6 125
 
3.8%
9 110
 
3.3%
0 106
 
3.2%
Other values (6) 188
 
5.7%
Hangul
ValueCountFrequency (%)
시 444
10.9%
읍 378
 
9.3%
정 357
 
8.7%
북 356
 
8.7%
전 349
 
8.5%
라 347
 
8.5%
도 346
 
8.5%
동 240
 
5.9%
리 118
 
2.9%
기 90
 
2.2%
Other values (141) 1058
25.9%

소재지전화
Text

MISSING 

Distinct213
Distinct (%)99.5%
Missing132
Missing (%)38.2%
Memory size2.8 KiB
2023-12-16T15:41:25.704235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.009346
Min length12

Characters and Unicode

Total characters2570
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

Unique212 ?
Unique (%)99.1%

Sample

1st row063-571-2756
2nd row063-571-2776
3rd row063-571-1582
4th row063-571-7881
5th row063-571-6947
ValueCountFrequency (%)
063-537-0460 2
 
0.9%
063-538-3004 1
 
0.5%
063-538-1325 1
 
0.5%
063-535-4457 1
 
0.5%
063-532-9696 1
 
0.5%
063-534-3376 1
 
0.5%
063-538-8300 1
 
0.5%
063-533-7885 1
 
0.5%
063-532-7571 1
 
0.5%
063-533-8592 1
 
0.5%
Other values (203) 203
94.9%
2023-12-16T15:41:27.374841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 514
20.0%
- 428
16.7%
5 341
13.3%
0 323
12.6%
6 320
12.5%
1 129
 
5.0%
7 123
 
4.8%
4 105
 
4.1%
2 104
 
4.0%
8 103
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2142
83.3%
Dash Punctuation 428
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 514
24.0%
5 341
15.9%
0 323
15.1%
6 320
14.9%
1 129
 
6.0%
7 123
 
5.7%
4 105
 
4.9%
2 104
 
4.9%
8 103
 
4.8%
9 80
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 514
20.0%
- 428
16.7%
5 341
13.3%
0 323
12.6%
6 320
12.5%
1 129
 
5.0%
7 123
 
4.8%
4 105
 
4.1%
2 104
 
4.0%
8 103
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 514
20.0%
- 428
16.7%
5 341
13.3%
0 323
12.6%
6 320
12.5%
1 129
 
5.0%
7 123
 
4.8%
4 105
 
4.1%
2 104
 
4.0%
8 103
 
4.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-16T15:41:27.980439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:41:28.354518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-16T15:41:12.004152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:41:12.617836image/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)소재지(지번)소재지전화데이터기준일자
0한일기름집전라북도 정읍시 신태인읍 시장2길 14전라북도 정읍시 신태인읍 신태인리 152-8063-571-27562023-12-13
1중앙기름집전라북도 정읍시 신태인읍 시장2길 31전라북도 정읍시 신태인읍 신태인리 150063-571-27762023-12-13
2우령떡방앗간전라북도 정읍시 신태인읍 정신로 1258전라북도 정읍시 신태인읍 우령리 476-1063-571-15822023-12-13
3태흥제분소전라북도 정읍시 신태인읍 서태길 86전라북도 정읍시 신태인읍 신태인리 406-1063-571-78812023-12-13
4평화제분소전라북도 정읍시 신태인읍 평화3길 74전라북도 정읍시 신태인읍 신태인리 572-6063-571-69472023-12-13
5동부떡방앗간전라북도 정읍시 입암면 동부길 26-3전라북도 정읍시 입암면 천원리 128-2063-534-24132023-12-13
6칠정떡방앗간전라북도 정읍시 고부면 관청길 65-4전라북도 정읍시 고부면 관청리 529063-536-00832023-12-13
7백양떡집건강원전라북도 정읍시 영원면 청량길 2전라북도 정읍시 영원면 장재리 1393063-536-75082023-12-13
8소송떡방앗간전라북도 정읍시 이평면 소송길 23전라북도 정읍시 이평면 창동리 81-1063-534-18102023-12-13
9태인방앗간전라북도 정읍시 태인면 향교1길 3전라북도 정읍시 태인면 태성리 561-1063-534-41722023-12-13
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344대찬수산전라북도 정읍시 명덕로 25, 농협하나로마트 1층 (연지동)전라북도 정읍시 연지동 341-9 농협하나로마트<NA>2023-12-13
345주식회사 제이수산전라북도 정읍시 벚꽃로 85, 롯데마트 (농소동)전라북도 정읍시 농소동 446-1 롯데마트<NA>2023-12-13