Overview

Dataset statistics

Number of variables3
Number of observations734
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)0.5%
Total size in memory17.3 KiB
Average record size in memory24.2 B

Variable types

Categorical1
Text2

Dataset

Description경기도 고양시 일산동구에서 판매되고 있는 종량제봉투판매처에 대한 현황자료로서 종량제봉투판매처 행정동, 판매소명, 주소 대한 데이터입니다.
Author고양도시관리공사
URLhttps://www.data.go.kr/data/15044398/fileData.do

Alerts

Dataset has 4 (0.5%) duplicate rowsDuplicates

Reproduction

Analysis started2024-04-06 08:35:02.045385
Analysis finished2024-04-06 08:35:02.787364
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct11
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
장항동
147 
백석동
119 
고봉동
100 
중산동
88 
정발산동
71 
Other values (6)
209 

Length

Max length4
Median length3
Mean length3.0953678
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row고봉동
2nd row고봉동
3rd row고봉동
4th row고봉동
5th row고봉동

Common Values

ValueCountFrequency (%)
장항동 147
20.0%
백석동 119
16.2%
고봉동 100
13.6%
중산동 88
12.0%
정발산동 71
9.7%
마두동 70
9.5%
식사동 68
9.3%
풍산동 64
8.7%
기타 4
 
0.5%
일산2동 2
 
0.3%

Length

2024-04-06T17:35:02.956977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장항동 147
20.0%
백석동 119
16.2%
고봉동 100
13.6%
중산동 88
12.0%
정발산동 71
9.7%
마두동 70
9.5%
식사동 68
9.3%
풍산동 64
8.7%
기타 4
 
0.5%
일산2동 2
 
0.3%

판매소명
Text

Distinct702
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-04-06T17:35:03.435232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length9.0095368
Min length2

Characters and Unicode

Total characters6613
Distinct characters410
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

Unique678 ?
Unique (%)92.4%

Sample

1st row동문마트
2nd row고양시슈퍼마켓협동조합
3rd row이마트24 고양사리현점
4th row오렌지마트
5th rowCU 일산운정로점
ValueCountFrequency (%)
gs25 108
 
8.9%
cu 98
 
8.0%
세븐일레븐 71
 
5.8%
이마트24 33
 
2.7%
주)코리아세븐 16
 
1.3%
코사마트 11
 
0.9%
두배로마트 11
 
0.9%
편의점 9
 
0.7%
일산점 8
 
0.7%
주식회사 7
 
0.6%
Other values (712) 848
69.5%
2024-04-06T17:35:04.604179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
492
 
7.4%
점 431
 
6.5%
마 252
 
3.8%
일 248
 
3.8%
산 246
 
3.7%
2 194
 
2.9%
트 188
 
2.8%
븐 170
 
2.6%
5 137
 
2.1%
S 116
 
1.8%
Other values (400) 4139
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5083
76.9%
Space Separator 492
 
7.4%
Uppercase Letter 486
 
7.3%
Decimal Number 414
 
6.3%
Open Punctuation 58
 
0.9%
Close Punctuation 58
 
0.9%
Lowercase Letter 14
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 431
 
8.5%
마 252
 
5.0%
일 248
 
4.9%
산 246
 
4.8%
트 188
 
3.7%
븐 170
 
3.3%
이 110
 
2.2%
스 102
 
2.0%
세 99
 
1.9%
레 92
 
1.8%
Other values (352) 3145
61.9%
Uppercase Letter
ValueCountFrequency (%)
S 116
23.9%
G 113
23.3%
C 109
22.4%
U 100
20.6%
E 5
 
1.0%
A 5
 
1.0%
K 5
 
1.0%
R 5
 
1.0%
T 4
 
0.8%
I 4
 
0.8%
Other values (12) 20
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
m 2
14.3%
o 2
14.3%
c 2
14.3%
d 1
7.1%
u 1
7.1%
p 1
7.1%
a 1
7.1%
s 1
7.1%
e 1
7.1%
y 1
7.1%
Decimal Number
ValueCountFrequency (%)
2 194
46.9%
5 137
33.1%
4 48
 
11.6%
3 7
 
1.7%
1 6
 
1.4%
0 6
 
1.4%
6 6
 
1.4%
9 5
 
1.2%
8 3
 
0.7%
7 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 2
 
25.0%
Space Separator
ValueCountFrequency (%)
492
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5083
76.9%
Common 1030
 
15.6%
Latin 500
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 431
 
8.5%
마 252
 
5.0%
일 248
 
4.9%
산 246
 
4.8%
트 188
 
3.7%
븐 170
 
3.3%
이 110
 
2.2%
스 102
 
2.0%
세 99
 
1.9%
레 92
 
1.8%
Other values (352) 3145
61.9%
Latin
ValueCountFrequency (%)
S 116
23.2%
G 113
22.6%
C 109
21.8%
U 100
20.0%
E 5
 
1.0%
A 5
 
1.0%
K 5
 
1.0%
R 5
 
1.0%
T 4
 
0.8%
I 4
 
0.8%
Other values (23) 34
 
6.8%
Common
ValueCountFrequency (%)
492
47.8%
2 194
 
18.8%
5 137
 
13.3%
( 58
 
5.6%
) 58
 
5.6%
4 48
 
4.7%
3 7
 
0.7%
1 6
 
0.6%
, 6
 
0.6%
0 6
 
0.6%
Other values (5) 18
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5083
76.9%
ASCII 1530
 
23.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
492
32.2%
2 194
 
12.7%
5 137
 
9.0%
S 116
 
7.6%
G 113
 
7.4%
C 109
 
7.1%
U 100
 
6.5%
( 58
 
3.8%
) 58
 
3.8%
4 48
 
3.1%
Other values (38) 105
 
6.9%
Hangul
ValueCountFrequency (%)
점 431
 
8.5%
마 252
 
5.0%
일 248
 
4.9%
산 246
 
4.8%
트 188
 
3.7%
븐 170
 
3.3%
이 110
 
2.2%
스 102
 
2.0%
세 99
 
1.9%
레 92
 
1.8%
Other values (352) 3145
61.9%

주소
Text

Distinct635
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-04-06T17:35:05.098475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length18.134877
Min length10

Characters and Unicode

Total characters13311
Distinct characters130
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

Unique553 ?
Unique (%)75.3%

Sample

1st row일산동구 공릉천로 68(사리현동)
2nd row일산동구 성석로 332-21(성석동)
3rd row일산동구 성현로659번길 180(사리현동)
4th row일산동구 견달산로 349(문봉동)
5th row일산동구 운정로 190(성석동)
ValueCountFrequency (%)
일산동구 734
33.0%
일산로 44
 
2.0%
중앙로 43
 
1.9%
호수로 28
 
1.3%
무궁화로 28
 
1.3%
고봉로 28
 
1.3%
중산로 21
 
0.9%
산두로 18
 
0.8%
숲속마을1로 17
 
0.8%
성석로 16
 
0.7%
Other values (766) 1246
56.1%
2024-04-06T17:35:05.868893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1489
 
11.2%
동 1388
 
10.4%
산 1056
 
7.9%
일 816
 
6.1%
구 737
 
5.5%
로 686
 
5.2%
) 627
 
4.7%
( 627
 
4.7%
1 563
 
4.2%
2 374
 
2.8%
Other values (120) 4948
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7769
58.4%
Decimal Number 2599
 
19.5%
Space Separator 1489
 
11.2%
Close Punctuation 627
 
4.7%
Open Punctuation 627
 
4.7%
Dash Punctuation 174
 
1.3%
Other Punctuation 21
 
0.2%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1388
17.9%
산 1056
13.6%
일 816
 
10.5%
구 737
 
9.5%
로 686
 
8.8%
길 207
 
2.7%
석 188
 
2.4%
중 181
 
2.3%
장 171
 
2.2%
번 170
 
2.2%
Other values (100) 2169
27.9%
Decimal Number
ValueCountFrequency (%)
1 563
21.7%
2 374
14.4%
3 315
12.1%
4 274
10.5%
5 216
 
8.3%
6 193
 
7.4%
7 184
 
7.1%
0 177
 
6.8%
8 163
 
6.3%
9 140
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
F 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 20
95.2%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
1489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 627
100.0%
Open Punctuation
ValueCountFrequency (%)
( 627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7769
58.4%
Common 5537
41.6%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1388
17.9%
산 1056
13.6%
일 816
 
10.5%
구 737
 
9.5%
로 686
 
8.8%
길 207
 
2.7%
석 188
 
2.4%
중 181
 
2.3%
장 171
 
2.2%
번 170
 
2.2%
Other values (100) 2169
27.9%
Common
ValueCountFrequency (%)
1489
26.9%
) 627
11.3%
( 627
11.3%
1 563
 
10.2%
2 374
 
6.8%
3 315
 
5.7%
4 274
 
4.9%
5 216
 
3.9%
6 193
 
3.5%
7 184
 
3.3%
Other values (6) 675
12.2%
Latin
ValueCountFrequency (%)
B 2
40.0%
c 1
20.0%
F 1
20.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7769
58.4%
ASCII 5542
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1489
26.9%
) 627
11.3%
( 627
11.3%
1 563
 
10.2%
2 374
 
6.7%
3 315
 
5.7%
4 274
 
4.9%
5 216
 
3.9%
6 193
 
3.5%
7 184
 
3.3%
Other values (10) 680
12.3%
Hangul
ValueCountFrequency (%)
동 1388
17.9%
산 1056
13.6%
일 816
 
10.5%
구 737
 
9.5%
로 686
 
8.8%
길 207
 
2.7%
석 188
 
2.4%
중 181
 
2.3%
장 171
 
2.2%
번 170
 
2.2%
Other values (100) 2169
27.9%

Missing values

2024-04-06T17:35:02.551974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:35:02.728411image/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

행정동판매소명주소
0고봉동동문마트일산동구 공릉천로 68(사리현동)
1고봉동고양시슈퍼마켓협동조합일산동구 성석로 332-21(성석동)
2고봉동이마트24 고양사리현점일산동구 성현로659번길 180(사리현동)
3고봉동오렌지마트일산동구 견달산로 349(문봉동)
4고봉동CU 일산운정로점일산동구 운정로 190(성석동)
5고봉동농업회사법인 주식회사 자연터일산동구 성현로 400
6고봉동포시즌마트일산동구 고봉로 529(성석동)
7고봉동이마트24 고양성석시티점일산동구 고봉로531번길 67(성석동)
8고봉동세븐일레븐 일산밀알점일산동구 성현로 149(성석동)
9고봉동코사마트 지영점일산동구 통일로1267번길 144-40(지영동)
행정동판매소명주소
724풍산동CU 일산풍동동문점일산동구 은행마을로6번길 30(풍동)
725풍산동이마트24 일산풍동숲속점일산동구 숲속마을2로 133
726풍산동세븐일레븐 퐁동YMCA점일산동구 애현로 53
727풍산동CU 풍동중앙하이츠일산동구 고일로 175
728풍산동그린건철일산동구 고풍로 33
729풍산동세븐일레븐 풍동주은점일산동구 숲속마을1로 28-8(풍동)
730풍산동제주점빵일산동구 숲속마을로 49-28
731풍산동일산농협 풍산지점일산동구 숲속마을1로 34(풍동)
732풍산동주식회사 비비하우스일산동구 백마로 506
733행신3동GS25 행신본점일산동구 행신로311번길 56(행신동)

Duplicate rows

Most frequently occurring

행정동판매소명주소# duplicates
0고봉동GS25 고양성석점일산동구 성현로 201(성석동)2
1백석동CU 백석호수점일산동구 강촌로 24(백석동)2
2장항동GS25 장항드림점일산동구 고봉로 32-9(장항동)2
3장항동GS25 장항중앙점일산동구 중앙로1275번길 86-1(장항동)2