Overview

Dataset statistics

Number of variables5
Number of observations83
Missing cells46
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory41.6 B

Variable types

Text4
Categorical1

Dataset

Description전라북도 정읍시 에 소재한 유통판매업소 현황중( 업소명, 소재지도로명주소, 소재지지번주소, 소재지연락처 )등의 자료를 제공합니다.
Author전라북도 정읍시
URLhttps://www.data.go.kr/data/15047936/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지전화 has 46 (55.4%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:09:56.745256
Analysis finished2023-12-16 15:09:59.826594
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-16T15:10:00.516977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.686747
Min length2

Characters and Unicode

Total characters638
Distinct characters180
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

Unique83 ?
Unique (%)100.0%

Sample

1st row(주)현미원
2nd row(주)코롬방제과
3rd row미래타조타운
4th row화정상회
5th row홍은농산
ValueCountFrequency (%)
농업회사법인 9
 
7.3%
유한회사 7
 
5.6%
주식회사 5
 
4.0%
영농조합법인 2
 
1.6%
동화해평농원 1
 
0.8%
새롬농원 1
 
0.8%
선물 1
 
0.8%
농부의 1
 
0.8%
거둠터 1
 
0.8%
미루네 1
 
0.8%
Other values (95) 95
76.6%
2023-12-16T15:10:03.049471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 44
 
6.9%
41
 
6.4%
회 32
 
5.0%
사 30
 
4.7%
유 20
 
3.1%
법 18
 
2.8%
인 18
 
2.8%
산 15
 
2.4%
한 14
 
2.2%
) 13
 
2.0%
Other values (170) 393
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
88.6%
Space Separator 41
 
6.4%
Close Punctuation 13
 
2.0%
Open Punctuation 11
 
1.7%
Uppercase Letter 6
 
0.9%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 44
 
7.8%
회 32
 
5.7%
사 30
 
5.3%
유 20
 
3.5%
법 18
 
3.2%
인 18
 
3.2%
산 15
 
2.7%
한 14
 
2.5%
업 13
 
2.3%
주 11
 
1.9%
Other values (161) 350
61.9%
Uppercase Letter
ValueCountFrequency (%)
F 2
33.3%
B 1
16.7%
N 1
16.7%
C 1
16.7%
S 1
16.7%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
88.6%
Common 67
 
10.5%
Latin 6
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 44
 
7.8%
회 32
 
5.7%
사 30
 
5.3%
유 20
 
3.5%
법 18
 
3.2%
인 18
 
3.2%
산 15
 
2.7%
한 14
 
2.5%
업 13
 
2.3%
주 11
 
1.9%
Other values (161) 350
61.9%
Latin
ValueCountFrequency (%)
F 2
33.3%
B 1
16.7%
N 1
16.7%
C 1
16.7%
S 1
16.7%
Common
ValueCountFrequency (%)
41
61.2%
) 13
 
19.4%
( 11
 
16.4%
& 2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
88.6%
ASCII 73
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 44
 
7.8%
회 32
 
5.7%
사 30
 
5.3%
유 20
 
3.5%
법 18
 
3.2%
인 18
 
3.2%
산 15
 
2.7%
한 14
 
2.5%
업 13
 
2.3%
주 11
 
1.9%
Other values (161) 350
61.9%
ASCII
ValueCountFrequency (%)
41
56.2%
) 13
 
17.8%
( 11
 
15.1%
& 2
 
2.7%
F 2
 
2.7%
B 1
 
1.4%
N 1
 
1.4%
C 1
 
1.4%
S 1
 
1.4%

소재지(도로명)
Text

Distinct76
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-16T15:10:04.903934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length25.698795
Min length19

Characters and Unicode

Total characters2133
Distinct characters142
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

Unique72 ?
Unique (%)86.7%

Sample

1st row전라북도 정읍시 영파길 41-8 (영파동)
2nd row전라북도 정읍시 정우면 정우남로 6
3rd row전라북도 정읍시 신태인읍 평화3길 70
4th row전라북도 정읍시 황토현로 1213-15 (농소동)
5th row전라북도 정읍시 황토현로 1213-15 (농소동)
ValueCountFrequency (%)
전라북도 83
 
18.3%
정읍시 83
 
18.3%
시기동 12
 
2.6%
황토현로 10
 
2.2%
1213-15 10
 
2.2%
농소동 9
 
2.0%
수성동 7
 
1.5%
신태인읍 6
 
1.3%
정우면 6
 
1.3%
1층 6
 
1.3%
Other values (172) 222
48.9%
2023-12-16T15:10:07.905310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
17.4%
정 105
 
4.9%
시 102
 
4.8%
1 101
 
4.7%
읍 98
 
4.6%
북 95
 
4.5%
도 87
 
4.1%
전 86
 
4.0%
라 83
 
3.9%
동 59
 
2.8%
Other values (132) 946
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1242
58.2%
Space Separator 371
 
17.4%
Decimal Number 343
 
16.1%
Close Punctuation 52
 
2.4%
Open Punctuation 52
 
2.4%
Dash Punctuation 47
 
2.2%
Other Punctuation 24
 
1.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 105
 
8.5%
시 102
 
8.2%
읍 98
 
7.9%
북 95
 
7.6%
도 87
 
7.0%
전 86
 
6.9%
라 83
 
6.7%
동 59
 
4.8%
로 44
 
3.5%
길 39
 
3.1%
Other values (115) 444
35.7%
Decimal Number
ValueCountFrequency (%)
1 101
29.4%
2 52
15.2%
3 44
12.8%
5 36
 
10.5%
4 28
 
8.2%
6 23
 
6.7%
7 16
 
4.7%
9 15
 
4.4%
8 15
 
4.4%
0 13
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1242
58.2%
Common 889
41.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 105
 
8.5%
시 102
 
8.2%
읍 98
 
7.9%
북 95
 
7.6%
도 87
 
7.0%
전 86
 
6.9%
라 83
 
6.7%
동 59
 
4.8%
로 44
 
3.5%
길 39
 
3.1%
Other values (115) 444
35.7%
Common
ValueCountFrequency (%)
371
41.7%
1 101
 
11.4%
) 52
 
5.8%
( 52
 
5.8%
2 52
 
5.8%
- 47
 
5.3%
3 44
 
4.9%
5 36
 
4.0%
4 28
 
3.1%
, 24
 
2.7%
Other values (5) 82
 
9.2%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1242
58.2%
ASCII 891
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
41.6%
1 101
 
11.3%
) 52
 
5.8%
( 52
 
5.8%
2 52
 
5.8%
- 47
 
5.3%
3 44
 
4.9%
5 36
 
4.0%
4 28
 
3.1%
, 24
 
2.7%
Other values (7) 84
 
9.4%
Hangul
ValueCountFrequency (%)
정 105
 
8.5%
시 102
 
8.2%
읍 98
 
7.9%
북 95
 
7.6%
도 87
 
7.0%
전 86
 
6.9%
라 83
 
6.7%
동 59
 
4.8%
로 44
 
3.5%
길 39
 
3.1%
Other values (115) 444
35.7%

소재지(지번)
Text

Distinct74
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-16T15:10:09.725855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length22.506024
Min length17

Characters and Unicode

Total characters1868
Distinct characters120
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

Unique69 ?
Unique (%)83.1%

Sample

1st row전라북도 정읍시 영파동 500-17
2nd row전라북도 정읍시 정우면 우산리 519-2
3rd row전라북도 정읍시 신태인읍 신태인리 572-1
4th row전라북도 정읍시 농소동 45-15
5th row전라북도 정읍시 농소동 45-15
ValueCountFrequency (%)
전라북도 83
20.7%
정읍시 83
20.7%
농소동 12
 
3.0%
시기동 12
 
3.0%
45-15 10
 
2.5%
수성동 7
 
1.7%
신태인읍 6
 
1.5%
정우면 6
 
1.5%
입암면 5
 
1.2%
연지동 5
 
1.2%
Other values (134) 172
42.9%
2023-12-16T15:10:11.824338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
398
21.3%
시 100
 
5.4%
정 91
 
4.9%
북 90
 
4.8%
읍 90
 
4.8%
도 87
 
4.7%
전 86
 
4.6%
1 86
 
4.6%
라 83
 
4.4%
- 64
 
3.4%
Other values (110) 693
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1058
56.6%
Space Separator 398
 
21.3%
Decimal Number 340
 
18.2%
Dash Punctuation 64
 
3.4%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 100
 
9.5%
정 91
 
8.6%
북 90
 
8.5%
읍 90
 
8.5%
도 87
 
8.2%
전 86
 
8.1%
라 83
 
7.8%
동 54
 
5.1%
리 36
 
3.4%
면 30
 
2.8%
Other values (94) 311
29.4%
Decimal Number
ValueCountFrequency (%)
1 86
25.3%
4 46
13.5%
2 45
13.2%
5 43
12.6%
7 28
 
8.2%
9 25
 
7.4%
3 21
 
6.2%
8 16
 
4.7%
0 15
 
4.4%
6 15
 
4.4%
Space Separator
ValueCountFrequency (%)
398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1058
56.6%
Common 809
43.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 100
 
9.5%
정 91
 
8.6%
북 90
 
8.5%
읍 90
 
8.5%
도 87
 
8.2%
전 86
 
8.1%
라 83
 
7.8%
동 54
 
5.1%
리 36
 
3.4%
면 30
 
2.8%
Other values (94) 311
29.4%
Common
ValueCountFrequency (%)
398
49.2%
1 86
 
10.6%
- 64
 
7.9%
4 46
 
5.7%
2 45
 
5.6%
5 43
 
5.3%
7 28
 
3.5%
9 25
 
3.1%
3 21
 
2.6%
8 16
 
2.0%
Other values (5) 37
 
4.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1058
56.6%
ASCII 810
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
398
49.1%
1 86
 
10.6%
- 64
 
7.9%
4 46
 
5.7%
2 45
 
5.6%
5 43
 
5.3%
7 28
 
3.5%
9 25
 
3.1%
3 21
 
2.6%
8 16
 
2.0%
Other values (6) 38
 
4.7%
Hangul
ValueCountFrequency (%)
시 100
 
9.5%
정 91
 
8.6%
북 90
 
8.5%
읍 90
 
8.5%
도 87
 
8.2%
전 86
 
8.1%
라 83
 
7.8%
동 54
 
5.1%
리 36
 
3.4%
면 30
 
2.8%
Other values (94) 311
29.4%

소재지전화
Text

MISSING 

Distinct36
Distinct (%)97.3%
Missing46
Missing (%)55.4%
Memory size796.0 B
2023-12-16T15:10:13.033800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027027
Min length12

Characters and Unicode

Total characters445
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

Unique35 ?
Unique (%)94.6%

Sample

1st row063-531-1131
2nd row063-537-9911
3rd row063-543-5966
4th row063-535-6248
5th row063-532-2353
ValueCountFrequency (%)
063-538-9594 2
 
5.4%
063-537-3303 1
 
2.7%
063-536-7600 1
 
2.7%
063-531-1131 1
 
2.7%
063-571-6700 1
 
2.7%
063-535-0070 1
 
2.7%
063-535-8083 1
 
2.7%
063-534-3033 1
 
2.7%
063-535-0108 1
 
2.7%
063-536-2992 1
 
2.7%
Other values (26) 26
70.3%
2023-12-16T15:10:14.916200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 90
20.2%
- 74
16.6%
0 65
14.6%
5 60
13.5%
6 50
11.2%
7 22
 
4.9%
1 20
 
4.5%
8 18
 
4.0%
9 16
 
3.6%
2 16
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 371
83.4%
Dash Punctuation 74
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 90
24.3%
0 65
17.5%
5 60
16.2%
6 50
13.5%
7 22
 
5.9%
1 20
 
5.4%
8 18
 
4.9%
9 16
 
4.3%
2 16
 
4.3%
4 14
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 445
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 90
20.2%
- 74
16.6%
0 65
14.6%
5 60
13.5%
6 50
11.2%
7 22
 
4.9%
1 20
 
4.5%
8 18
 
4.0%
9 16
 
3.6%
2 16
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 90
20.2%
- 74
16.6%
0 65
14.6%
5 60
13.5%
6 50
11.2%
7 22
 
4.9%
1 20
 
4.5%
8 18
 
4.0%
9 16
 
3.6%
2 16
 
3.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13
83 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-13
2nd row2023-12-13
3rd row2023-12-13
4th row2023-12-13
5th row2023-12-13

Common Values

ValueCountFrequency (%)
2023-12-13 83
100.0%

Length

2023-12-16T15:10:15.794455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:10:16.349146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-13 83
100.0%

Correlations

2023-12-16T15:10:16.787701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지(지번)소재지전화
업소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0000.978
소재지(지번)1.0001.0001.0000.978
소재지전화1.0000.9780.9781.000

Missing values

2023-12-16T15:09:59.045943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:09:59.668978image/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
0(주)현미원전라북도 정읍시 영파길 41-8 (영파동)전라북도 정읍시 영파동 500-17063-531-11312023-12-13
1(주)코롬방제과전라북도 정읍시 정우면 정우남로 6전라북도 정읍시 정우면 우산리 519-2063-537-99112023-12-13
2미래타조타운전라북도 정읍시 신태인읍 평화3길 70전라북도 정읍시 신태인읍 신태인리 572-1063-543-59662023-12-13
3화정상회전라북도 정읍시 황토현로 1213-15 (농소동)전라북도 정읍시 농소동 45-15063-535-62482023-12-13
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