Overview

Dataset statistics

Number of variables4
Number of observations396
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory32.3 B

Variable types

Text3
DateTime1

Dataset

Description부산광역시수영구_종량제봉투판매소현황_20230816
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078430

Alerts

종량제봉투 판매소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:53:08.962315
Analysis finished2023-12-10 16:53:09.505085
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종량제봉투 판매소명
Text

UNIQUE 

Distinct396
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-11T01:53:09.715970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.4469697
Min length2

Characters and Unicode

Total characters3345
Distinct characters296
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

Unique396 ?
Unique (%)100.0%

Sample

1st row(주)메가마트 남천점
2nd row(주)쿱스토어부산 남천점
3rd rowCU편의점 남천점
4th rowGS25 남천강안점
5th rowGS25 남천바다점
ValueCountFrequency (%)
씨유 51
 
8.1%
gs25 44
 
7.0%
세븐일레븐 42
 
6.7%
이마트24 17
 
2.7%
미니스톱 11
 
1.8%
남천점 7
 
1.1%
수영점 6
 
1.0%
망미점 5
 
0.8%
위드미 5
 
0.8%
cu 4
 
0.6%
Other values (402) 435
69.4%
2023-12-11T01:53:10.180628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
6.9%
점 225
 
6.7%
마 103
 
3.1%
트 101
 
3.0%
븐 98
 
2.9%
광 91
 
2.7%
2 89
 
2.7%
수 85
 
2.5%
안 84
 
2.5%
영 78
 
2.3%
Other values (286) 2160
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2705
80.9%
Space Separator 231
 
6.9%
Decimal Number 183
 
5.5%
Uppercase Letter 138
 
4.1%
Open Punctuation 39
 
1.2%
Close Punctuation 39
 
1.2%
Lowercase Letter 8
 
0.2%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 225
 
8.3%
마 103
 
3.8%
트 101
 
3.7%
븐 98
 
3.6%
광 91
 
3.4%
수 85
 
3.1%
안 84
 
3.1%
영 78
 
2.9%
산 70
 
2.6%
세 68
 
2.5%
Other values (259) 1702
62.9%
Uppercase Letter
ValueCountFrequency (%)
S 55
39.9%
G 54
39.1%
C 10
 
7.2%
U 5
 
3.6%
J 4
 
2.9%
B 2
 
1.4%
R 2
 
1.4%
M 2
 
1.4%
K 1
 
0.7%
N 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 89
48.6%
5 62
33.9%
4 24
 
13.1%
1 4
 
2.2%
7 2
 
1.1%
3 2
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
s 3
37.5%
k 2
25.0%
e 2
25.0%
g 1
 
12.5%
Space Separator
ValueCountFrequency (%)
231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2705
80.9%
Common 494
 
14.8%
Latin 146
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 225
 
8.3%
마 103
 
3.8%
트 101
 
3.7%
븐 98
 
3.6%
광 91
 
3.4%
수 85
 
3.1%
안 84
 
3.1%
영 78
 
2.9%
산 70
 
2.6%
세 68
 
2.5%
Other values (259) 1702
62.9%
Latin
ValueCountFrequency (%)
S 55
37.7%
G 54
37.0%
C 10
 
6.8%
U 5
 
3.4%
J 4
 
2.7%
s 3
 
2.1%
k 2
 
1.4%
B 2
 
1.4%
R 2
 
1.4%
M 2
 
1.4%
Other values (6) 7
 
4.8%
Common
ValueCountFrequency (%)
231
46.8%
2 89
 
18.0%
5 62
 
12.6%
( 39
 
7.9%
) 39
 
7.9%
4 24
 
4.9%
1 4
 
0.8%
7 2
 
0.4%
3 2
 
0.4%
& 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2705
80.9%
ASCII 640
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
36.1%
2 89
 
13.9%
5 62
 
9.7%
S 55
 
8.6%
G 54
 
8.4%
( 39
 
6.1%
) 39
 
6.1%
4 24
 
3.8%
C 10
 
1.6%
U 5
 
0.8%
Other values (17) 32
 
5.0%
Hangul
ValueCountFrequency (%)
점 225
 
8.3%
마 103
 
3.8%
트 101
 
3.7%
븐 98
 
3.6%
광 91
 
3.4%
수 85
 
3.1%
안 84
 
3.1%
영 78
 
2.9%
산 70
 
2.6%
세 68
 
2.5%
Other values (259) 1702
62.9%

대표자명
Text

Distinct382
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-11T01:53:10.639161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0934343
Min length2

Characters and Unicode

Total characters1225
Distinct characters173
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique371 ?
Unique (%)93.7%

Sample

1st row신동익
2nd row김영옥
3rd row김현자
4th row최치훈
5th row강경희
ValueCountFrequency (%)
최경호 6
 
1.5%
외 3
 
0.7%
이원진 2
 
0.5%
조정화 2
 
0.5%
박정숙 2
 
0.5%
1명 2
 
0.5%
고영민 2
 
0.5%
김미경 2
 
0.5%
김영옥 2
 
0.5%
이영호 2
 
0.5%
Other values (374) 380
93.8%
2023-12-11T01:53:11.245078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 83
 
6.8%
김 71
 
5.8%
정 60
 
4.9%
영 41
 
3.3%
박 40
 
3.3%
숙 30
 
2.4%
경 25
 
2.0%
희 24
 
2.0%
최 22
 
1.8%
선 22
 
1.8%
Other values (163) 807
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1205
98.4%
Space Separator 9
 
0.7%
Decimal Number 6
 
0.5%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 83
 
6.9%
김 71
 
5.9%
정 60
 
5.0%
영 41
 
3.4%
박 40
 
3.3%
숙 30
 
2.5%
경 25
 
2.1%
희 24
 
2.0%
최 22
 
1.8%
선 22
 
1.8%
Other values (158) 787
65.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Decimal Number
ValueCountFrequency (%)
1 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1205
98.4%
Common 20
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 83
 
6.9%
김 71
 
5.9%
정 60
 
5.0%
영 41
 
3.4%
박 40
 
3.3%
숙 30
 
2.5%
경 25
 
2.1%
희 24
 
2.0%
최 22
 
1.8%
선 22
 
1.8%
Other values (158) 787
65.3%
Common
ValueCountFrequency (%)
9
45.0%
1 6
30.0%
) 2
 
10.0%
( 2
 
10.0%
, 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1205
98.4%
ASCII 20
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 83
 
6.9%
김 71
 
5.9%
정 60
 
5.0%
영 41
 
3.4%
박 40
 
3.3%
숙 30
 
2.5%
경 25
 
2.1%
희 24
 
2.0%
최 22
 
1.8%
선 22
 
1.8%
Other values (158) 787
65.3%
ASCII
ValueCountFrequency (%)
9
45.0%
1 6
30.0%
) 2
 
10.0%
( 2
 
10.0%
, 1
 
5.0%

지정일자
Date

Distinct346
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1996-05-09 00:00:00
Maximum2023-08-09 00:00:00
2023-12-11T01:53:11.428362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:53:11.634073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업장 주소
Text

Distinct391
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-11T01:53:12.130295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length14.621212
Min length4

Characters and Unicode

Total characters5790
Distinct characters171
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique386 ?
Unique (%)97.5%

Sample

1st row수영구 황령대로 521
2nd row남천동로 15
3rd row수영구 황령대로 491
4th row수영구 수영로 481, 6동 8호
5th row부산시 수영구 남천1동 28-28
ValueCountFrequency (%)
수영구 138
 
11.0%
수영로 51
 
4.1%
1층 44
 
3.5%
연수로 25
 
2.0%
수영동 20
 
1.6%
망미1동 17
 
1.4%
민락동 17
 
1.4%
광안해변로 17
 
1.4%
광안1동 16
 
1.3%
101호 12
 
1.0%
Other values (543) 892
71.4%
2023-12-11T01:53:13.075666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
860
 
14.9%
1 520
 
9.0%
로 279
 
4.8%
수 278
 
4.8%
2 253
 
4.4%
영 244
 
4.2%
0 193
 
3.3%
번 190
 
3.3%
3 185
 
3.2%
길 180
 
3.1%
Other values (161) 2608
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2673
46.2%
Decimal Number 1983
34.2%
Space Separator 860
 
14.9%
Dash Punctuation 147
 
2.5%
Other Punctuation 58
 
1.0%
Open Punctuation 30
 
0.5%
Close Punctuation 30
 
0.5%
Uppercase Letter 6
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 279
 
10.4%
수 278
 
10.4%
영 244
 
9.1%
번 190
 
7.1%
길 180
 
6.7%
동 171
 
6.4%
구 154
 
5.8%
광 118
 
4.4%
안 88
 
3.3%
호 64
 
2.4%
Other values (136) 907
33.9%
Decimal Number
ValueCountFrequency (%)
1 520
26.2%
2 253
12.8%
0 193
 
9.7%
3 185
 
9.3%
4 171
 
8.6%
5 156
 
7.9%
6 147
 
7.4%
7 124
 
6.3%
8 119
 
6.0%
9 115
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
T 1
16.7%
B 1
16.7%
C 1
16.7%
M 1
16.7%
A 1
16.7%
O 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 54
93.1%
/ 3
 
5.2%
. 1
 
1.7%
Space Separator
ValueCountFrequency (%)
860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3110
53.7%
Hangul 2673
46.2%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 279
 
10.4%
수 278
 
10.4%
영 244
 
9.1%
번 190
 
7.1%
길 180
 
6.7%
동 171
 
6.4%
구 154
 
5.8%
광 118
 
4.4%
안 88
 
3.3%
호 64
 
2.4%
Other values (136) 907
33.9%
Common
ValueCountFrequency (%)
860
27.7%
1 520
16.7%
2 253
 
8.1%
0 193
 
6.2%
3 185
 
5.9%
4 171
 
5.5%
5 156
 
5.0%
- 147
 
4.7%
6 147
 
4.7%
7 124
 
4.0%
Other values (8) 354
11.4%
Latin
ValueCountFrequency (%)
T 1
14.3%
B 1
14.3%
C 1
14.3%
M 1
14.3%
A 1
14.3%
O 1
14.3%
e 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3117
53.8%
Hangul 2673
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
860
27.6%
1 520
16.7%
2 253
 
8.1%
0 193
 
6.2%
3 185
 
5.9%
4 171
 
5.5%
5 156
 
5.0%
- 147
 
4.7%
6 147
 
4.7%
7 124
 
4.0%
Other values (15) 361
11.6%
Hangul
ValueCountFrequency (%)
로 279
 
10.4%
수 278
 
10.4%
영 244
 
9.1%
번 190
 
7.1%
길 180
 
6.7%
동 171
 
6.4%
구 154
 
5.8%
광 118
 
4.4%
안 88
 
3.3%
호 64
 
2.4%
Other values (136) 907
33.9%

Missing values

2023-12-11T01:53:09.390864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:53:09.471955image/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

종량제봉투 판매소명대표자명지정일자사업장 주소
0(주)메가마트 남천점신동익2002-07-23수영구 황령대로 521
1(주)쿱스토어부산 남천점김영옥2018-10-24남천동로 15
2CU편의점 남천점김현자2016-09-06수영구 황령대로 491
3GS25 남천강안점최치훈2010-10-05수영구 수영로 481, 6동 8호
4GS25 남천바다점강경희2012-02-09부산시 수영구 남천1동 28-28
5GS25 남천코오롱점이홍원2012-09-20수영구 수영로 476번길 11 101호
6GS25 남천파크장영혜2021-10-22수영구 남천동로 10번길 58 1
7GS25 힐사이드점이은자2006-02-10수영구 황령산로7번길 4
8GS편의점 남천봉황점이항2016-09-26남천동로24번길 30 1층 111호
9JC할인마트(남천점)박종철2007-01-25동래구 안락동 453-9 2/5
종량제봉투 판매소명대표자명지정일자사업장 주소
386이마트24 수영센텀점이민서2022.12.08수영로 679번길 19, 1층
387GS25 광안장대골점김병수2022.09.20수영구 장대골로 7번길 4, 1층 102호
388세븐일레븐 부산광안협성최경호, 류세진2022.11.16수영구 광일로 29번길 68, 1층
389이마트24 스마트광안수영로점김미향2022.11.09수영로 611번길 13
390(주)온어스코리아이상원2023.04.12민락수변로 95
391(주)프로유통박철원2022.10.24수영구 광안해변로 292, 103,104호
392(주)휴디앤씨이권주2023.04.13감포로 82
393세븐일레븐 부산광안바다점임종호2022.10.31부산시 수영구 민락수변로 9-1
394씨유 광안디오션점고영민 외1명2023.02.15광안해변로 284번길 38,상가동 121호
395이마트 R광안테라스타최선옥2022.10.31광안해변로 269, 1층 101호