Overview

Dataset statistics

Number of variables3
Number of observations162
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory24.8 B

Variable types

Text2
DateTime1

Dataset

Description진주시 관내 특정토양오염관리대상시설 현황(업소명, 도로명주소, 위험물안전관리법 완공검사일)을 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15046106

Reproduction

Analysis started2023-12-29 22:14:41.254800
Analysis finished2023-12-29 22:14:42.093891
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct160
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-29T22:14:42.375918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length5
Mean length6.2839506
Min length3

Characters and Unicode

Total characters1018
Distinct characters187
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

Unique158 ?
Unique (%)97.5%

Sample

1st row반성주유소
2nd row진명주유소
3rd row씨제이대한통운㈜
4th row옥산주유소
5th row덕오주유소
ValueCountFrequency (%)
주유소 3
 
1.8%
한아름주유소 2
 
1.2%
대양주유소 2
 
1.2%
진주서부농협클린주유소 1
 
0.6%
초장주유소 1
 
0.6%
sk네트웍스(주)sk진주주유소 1
 
0.6%
장자저장소 1
 
0.6%
경남에너지 1
 
0.6%
㈜명진에너지(주유소 1
 
0.6%
주)동호주유소 1
 
0.6%
Other values (153) 153
91.6%
2023-12-29T22:14:42.994410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 136
 
13.4%
유 126
 
12.4%
소 120
 
11.8%
진 28
 
2.8%
㈜ 24
 
2.4%
대 21
 
2.1%
동 15
 
1.5%
산 14
 
1.4%
경 14
 
1.4%
농 13
 
1.3%
Other values (177) 507
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 953
93.6%
Other Symbol 24
 
2.4%
Open Punctuation 11
 
1.1%
Close Punctuation 11
 
1.1%
Uppercase Letter 8
 
0.8%
Space Separator 5
 
0.5%
Decimal Number 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 136
 
14.3%
유 126
 
13.2%
소 120
 
12.6%
진 28
 
2.9%
대 21
 
2.2%
동 15
 
1.6%
산 14
 
1.5%
경 14
 
1.5%
농 13
 
1.4%
금 13
 
1.4%
Other values (162) 453
47.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
K 2
25.0%
A 1
 
12.5%
M 1
 
12.5%
G 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
3 1
20.0%
2 1
20.0%
6 1
20.0%
9 1
20.0%
8 1
20.0%
Other Symbol
ValueCountFrequency (%)
㈜ 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 977
96.0%
Common 33
 
3.2%
Latin 8
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 136
 
13.9%
유 126
 
12.9%
소 120
 
12.3%
진 28
 
2.9%
㈜ 24
 
2.5%
대 21
 
2.1%
동 15
 
1.5%
산 14
 
1.4%
경 14
 
1.4%
농 13
 
1.3%
Other values (163) 466
47.7%
Common
ValueCountFrequency (%)
( 11
33.3%
) 11
33.3%
5
15.2%
. 1
 
3.0%
3 1
 
3.0%
2 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
8 1
 
3.0%
Latin
ValueCountFrequency (%)
S 3
37.5%
K 2
25.0%
A 1
 
12.5%
M 1
 
12.5%
G 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 953
93.6%
ASCII 41
 
4.0%
None 24
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 136
 
14.3%
유 126
 
13.2%
소 120
 
12.6%
진 28
 
2.9%
대 21
 
2.2%
동 15
 
1.6%
산 14
 
1.5%
경 14
 
1.5%
농 13
 
1.4%
금 13
 
1.4%
Other values (162) 453
47.5%
None
ValueCountFrequency (%)
㈜ 24
100.0%
ASCII
ValueCountFrequency (%)
( 11
26.8%
) 11
26.8%
5
12.2%
S 3
 
7.3%
K 2
 
4.9%
. 1
 
2.4%
A 1
 
2.4%
3 1
 
2.4%
M 1
 
2.4%
2 1
 
2.4%
Other values (4) 4
 
9.8%

새주소
Text

Distinct161
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-29T22:14:43.615745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length22
Mean length14.246914
Min length10

Characters and Unicode

Total characters2308
Distinct characters123
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)98.8%

Sample

1st row 이반성면 진마대로2498번길 2-91
2nd row 명석면 진주대로 2627
3rd row 남강로 1715 (초전동)
4th row 남강로 935 (상평동)
5th row 집현면 남강로 2019
ValueCountFrequency (%)
진주대로 20
 
4.2%
남강로 17
 
3.6%
상평동 16
 
3.3%
동부로 13
 
2.7%
문산읍 12
 
2.5%
월아산로 12
 
2.5%
진산로 12
 
2.5%
대신로 10
 
2.1%
초전동 8
 
1.7%
상대동 8
 
1.7%
Other values (240) 350
73.2%
2023-12-29T22:14:44.639158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
480
20.8%
로 154
 
6.7%
1 131
 
5.7%
동 125
 
5.4%
) 100
 
4.3%
( 100
 
4.3%
2 65
 
2.8%
대 57
 
2.5%
4 55
 
2.4%
진 53
 
2.3%
Other values (113) 988
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1079
46.8%
Decimal Number 540
23.4%
Space Separator 480
20.8%
Close Punctuation 100
 
4.3%
Open Punctuation 100
 
4.3%
Dash Punctuation 8
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 154
 
14.3%
동 125
 
11.6%
대 57
 
5.3%
진 53
 
4.9%
면 49
 
4.5%
산 44
 
4.1%
상 29
 
2.7%
평 27
 
2.5%
남 27
 
2.5%
주 25
 
2.3%
Other values (98) 489
45.3%
Decimal Number
ValueCountFrequency (%)
1 131
24.3%
2 65
12.0%
4 55
10.2%
3 50
 
9.3%
5 47
 
8.7%
6 46
 
8.5%
0 39
 
7.2%
8 37
 
6.9%
7 36
 
6.7%
9 34
 
6.3%
Space Separator
ValueCountFrequency (%)
480
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1229
53.2%
Hangul 1079
46.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 154
 
14.3%
동 125
 
11.6%
대 57
 
5.3%
진 53
 
4.9%
면 49
 
4.5%
산 44
 
4.1%
상 29
 
2.7%
평 27
 
2.5%
남 27
 
2.5%
주 25
 
2.3%
Other values (98) 489
45.3%
Common
ValueCountFrequency (%)
480
39.1%
1 131
 
10.7%
) 100
 
8.1%
( 100
 
8.1%
2 65
 
5.3%
4 55
 
4.5%
3 50
 
4.1%
5 47
 
3.8%
6 46
 
3.7%
0 39
 
3.2%
Other values (5) 116
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1229
53.2%
Hangul 1079
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
480
39.1%
1 131
 
10.7%
) 100
 
8.1%
( 100
 
8.1%
2 65
 
5.3%
4 55
 
4.5%
3 50
 
4.1%
5 47
 
3.8%
6 46
 
3.7%
0 39
 
3.2%
Other values (5) 116
 
9.4%
Hangul
ValueCountFrequency (%)
로 154
 
14.3%
동 125
 
11.6%
대 57
 
5.3%
진 53
 
4.9%
면 49
 
4.5%
산 44
 
4.1%
상 29
 
2.7%
평 27
 
2.5%
남 27
 
2.5%
주 25
 
2.3%
Other values (98) 489
45.3%

위험물안전관리법완공검사일
Date

Distinct157
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1974-04-29 00:00:00
Maximum2015-10-07 00:00:00
2023-12-29T22:14:45.041494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:14:45.484196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2023-12-29T22:14:41.745568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-29T22:14:41.990127image/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

업소명새주소위험물안전관리법완공검사일
0반성주유소이반성면 진마대로2498번길 2-911993-09-25
1진명주유소명석면 진주대로 26271989-09-08
2씨제이대한통운㈜남강로 1715 (초전동)1995-06-22
3옥산주유소남강로 935 (상평동)1995-04-08
4덕오주유소집현면 남강로 20191995-03-03
5GMS원당산업㈜남강로 718 (옥봉동)1988-12-08
6개양주유소진주대로 414 (가좌동)1995-02-21
7경남주유소진산로 349 (장재동)1993-02-12
8현대주유소대신로 431 (초전동)1994-10-07
9선학주유소모덕로 115 (상대동)1993-12-29
업소명새주소위험물안전관리법완공검사일
152상평교주유소호탄길34번길 25 (호탄동)2010-05-06
153㈜삼립식품 진주휴게소 (주유소)호탄동 385-1 외622010-07-28
154현대오일뱅크㈜직영 유천현대주유소말티고개로 77(초전동)2010-09-14
155동부농협주유소진산로 216 (장재동)2010-09-15
156영남레미콘㈜큰들로 157(상평동)2012-08-07
157진주남부농협내동주유소내동면 순환로 3672012-09-27
158진주서부농협클린주유소서장대로 215 (이현동)2013-03-06
159금산농협주유소금산면 금산순환로 262010-10-20
160남부농협정촌주유소정촌면 화개천로 1202013-10-28
161금곡농협주유소금곡면 월아산로 1132015-01-13