Overview

Dataset statistics

Number of variables4
Number of observations425
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.4 KiB
Average record size in memory32.3 B

Variable types

Text2
Categorical2

Dataset

Description경기도 하남시 종량제봉투 판매소 현황에 대한 데이터로 거래처명, 행정동, 도로명주소, 데이터기준일자 등의 항목을 제공합니다.
Author경기도 하남시
URLhttps://www.data.go.kr/data/3047302/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2024-04-06 09:02:19.630943
Analysis finished2024-04-06 09:02:20.143543
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

거래처명
Text

Distinct424
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-06T18:02:20.387983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length10.703529
Min length3

Characters and Unicode

Total characters4549
Distinct characters344
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique423 ?
Unique (%)99.5%

Sample

1st row가람식품(로또슈퍼)
2nd row빙그레슈퍼(감일동)
3rd row한아름슈퍼
4th row부성마트
5th row감일슈퍼
ValueCountFrequency (%)
씨유 62
 
8.2%
세븐일레븐 38
 
5.0%
지에스(gs)25 26
 
3.4%
지에스25 24
 
3.2%
이마트24 23
 
3.0%
gs25 21
 
2.8%
주식회사 12
 
1.6%
주)코리아세븐 11
 
1.4%
cu 9
 
1.2%
지에스25(gs25 6
 
0.8%
Other values (477) 527
69.4%
2024-04-06T18:02:21.120059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
337
 
7.4%
점 292
 
6.4%
하 161
 
3.5%
남 151
 
3.3%
2 141
 
3.1%
사 140
 
3.1%
미 123
 
2.7%
스 120
 
2.6%
지 107
 
2.4%
5 107
 
2.4%
Other values (334) 2870
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3482
76.5%
Space Separator 337
 
7.4%
Decimal Number 315
 
6.9%
Uppercase Letter 227
 
5.0%
Open Punctuation 90
 
2.0%
Close Punctuation 89
 
2.0%
Lowercase Letter 5
 
0.1%
Other Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 292
 
8.4%
하 161
 
4.6%
남 151
 
4.3%
사 140
 
4.0%
미 123
 
3.5%
스 120
 
3.4%
지 107
 
3.1%
트 104
 
3.0%
마 101
 
2.9%
유 101
 
2.9%
Other values (296) 2082
59.8%
Uppercase Letter
ValueCountFrequency (%)
S 79
34.8%
G 76
33.5%
C 18
 
7.9%
U 16
 
7.0%
H 7
 
3.1%
R 6
 
2.6%
E 6
 
2.6%
T 5
 
2.2%
I 4
 
1.8%
A 4
 
1.8%
Other values (4) 6
 
2.6%
Decimal Number
ValueCountFrequency (%)
2 141
44.8%
5 107
34.0%
4 30
 
9.5%
1 21
 
6.7%
3 4
 
1.3%
7 3
 
1.0%
6 3
 
1.0%
8 3
 
1.0%
0 2
 
0.6%
9 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
r 1
20.0%
f 1
20.0%
l 1
20.0%
e 1
20.0%
s 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 86
95.6%
（ 4
 
4.4%
Close Punctuation
ValueCountFrequency (%)
) 85
95.5%
） 4
 
4.5%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
． 1
50.0%
Space Separator
ValueCountFrequency (%)
337
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3483
76.6%
Common 834
 
18.3%
Latin 232
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 292
 
8.4%
하 161
 
4.6%
남 151
 
4.3%
사 140
 
4.0%
미 123
 
3.5%
스 120
 
3.4%
지 107
 
3.1%
트 104
 
3.0%
마 101
 
2.9%
유 101
 
2.9%
Other values (297) 2083
59.8%
Latin
ValueCountFrequency (%)
S 79
34.1%
G 76
32.8%
C 18
 
7.8%
U 16
 
6.9%
H 7
 
3.0%
R 6
 
2.6%
E 6
 
2.6%
T 5
 
2.2%
I 4
 
1.7%
A 4
 
1.7%
Other values (9) 11
 
4.7%
Common
ValueCountFrequency (%)
337
40.4%
2 141
16.9%
5 107
 
12.8%
( 86
 
10.3%
) 85
 
10.2%
4 30
 
3.6%
1 21
 
2.5%
） 4
 
0.5%
（ 4
 
0.5%
3 4
 
0.5%
Other values (8) 15
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3482
76.5%
ASCII 1057
 
23.2%
None 10
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
337
31.9%
2 141
13.3%
5 107
 
10.1%
( 86
 
8.1%
) 85
 
8.0%
S 79
 
7.5%
G 76
 
7.2%
4 30
 
2.8%
1 21
 
2.0%
C 18
 
1.7%
Other values (24) 77
 
7.3%
Hangul
ValueCountFrequency (%)
점 292
 
8.4%
하 161
 
4.6%
남 151
 
4.3%
사 140
 
4.0%
미 123
 
3.5%
스 120
 
3.4%
지 107
 
3.1%
트 104
 
3.0%
마 101
 
2.9%
유 101
 
2.9%
Other values (296) 2082
59.8%
None
ValueCountFrequency (%)
） 4
40.0%
（ 4
40.0%
㈜ 1
 
10.0%
． 1
 
10.0%

행정동
Categorical

Distinct14
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
미사1동
71 
신장2동
50 
미사2동
44 
미사3동
35 
감일동
34 
Other values (9)
191 

Length

Max length4
Median length4
Mean length3.6870588
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미사1동 71
16.7%
신장2동 50
11.8%
미사2동 44
10.4%
미사3동 35
8.2%
감일동 34
8.0%
덕풍3동 31
7.3%
위례동 31
7.3%
덕풍2동 29
6.8%
천현동 26
 
6.1%
신장1동 20
 
4.7%
Other values (4) 54
12.7%

Length

2024-04-06T18:02:21.367144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미사1동 71
16.7%
신장2동 50
11.8%
미사2동 44
10.4%
미사3동 35
8.2%
감일동 34
8.0%
덕풍3동 31
7.3%
위례동 31
7.3%
덕풍2동 29
6.8%
천현동 26
 
6.1%
신장1동 20
 
4.7%
Other values (4) 54
12.7%

주소
Text

Distinct370
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-06T18:02:21.970227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length12.536471
Min length10

Characters and Unicode

Total characters5328
Distinct characters56
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

Unique328 ?
Unique (%)77.2%

Sample

1st row하남시 감북동 419-21
2nd row하남시 감일동 249-4
3rd row하남시 감북동 273-5
4th row하남시 감일동 249-5
5th row하남시 감일동 14-5
ValueCountFrequency (%)
하남시 416
32.3%
망월동 103
 
8.0%
덕풍동 71
 
5.5%
신장동 57
 
4.4%
풍산동 35
 
2.7%
학암동 24
 
1.9%
감이동 22
 
1.7%
감일동 19
 
1.5%
창우동 18
 
1.4%
초이동 12
 
0.9%
Other values (382) 510
39.6%
2024-04-06T18:02:22.806662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
863
16.2%
동 426
 
8.0%
하 425
 
8.0%
시 422
 
7.9%
남 422
 
7.9%
1 321
 
6.0%
- 226
 
4.2%
4 209
 
3.9%
2 192
 
3.6%
5 184
 
3.5%
Other values (46) 1638
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2580
48.4%
Decimal Number 1654
31.0%
Space Separator 863
 
16.2%
Dash Punctuation 226
 
4.2%
Other Punctuation 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 426
16.5%
하 425
16.5%
시 422
16.4%
남 422
16.4%
풍 107
 
4.1%
월 103
 
4.0%
망 103
 
4.0%
덕 72
 
2.8%
신 58
 
2.2%
장 58
 
2.2%
Other values (32) 384
14.9%
Decimal Number
ValueCountFrequency (%)
1 321
19.4%
4 209
12.6%
2 192
11.6%
5 184
11.1%
3 174
10.5%
7 135
8.2%
6 124
 
7.5%
9 117
 
7.1%
0 111
 
6.7%
8 87
 
5.3%
Space Separator
ValueCountFrequency (%)
863
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 226
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2748
51.6%
Hangul 2580
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 426
16.5%
하 425
16.5%
시 422
16.4%
남 422
16.4%
풍 107
 
4.1%
월 103
 
4.0%
망 103
 
4.0%
덕 72
 
2.8%
신 58
 
2.2%
장 58
 
2.2%
Other values (32) 384
14.9%
Common
ValueCountFrequency (%)
863
31.4%
1 321
 
11.7%
- 226
 
8.2%
4 209
 
7.6%
2 192
 
7.0%
5 184
 
6.7%
3 174
 
6.3%
7 135
 
4.9%
6 124
 
4.5%
9 117
 
4.3%
Other values (4) 203
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2748
51.6%
Hangul 2580
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
863
31.4%
1 321
 
11.7%
- 226
 
8.2%
4 209
 
7.6%
2 192
 
7.0%
5 184
 
6.7%
3 174
 
6.3%
7 135
 
4.9%
6 124
 
4.5%
9 117
 
4.3%
Other values (4) 203
 
7.4%
Hangul
ValueCountFrequency (%)
동 426
16.5%
하 425
16.5%
시 422
16.4%
남 422
16.4%
풍 107
 
4.1%
월 103
 
4.0%
망 103
 
4.0%
덕 72
 
2.8%
신 58
 
2.2%
장 58
 
2.2%
Other values (32) 384
14.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14
425 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-14
2nd row2024-03-14
3rd row2024-03-14
4th row2024-03-14
5th row2024-03-14

Common Values

ValueCountFrequency (%)
2024-03-14 425
100.0%

Length

2024-04-06T18:02:23.048065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:02:23.224636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-14 425
100.0%

Missing values

2024-04-06T18:02:19.965570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:02:20.094192image/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

거래처명행정동주소데이터기준일자
0가람식품(로또슈퍼)감북동하남시 감북동 419-212024-03-14
1빙그레슈퍼(감일동)감북동하남시 감일동 249-42024-03-14
2한아름슈퍼감북동하남시 감북동 273-52024-03-14
3부성마트감북동하남시 감일동 249-52024-03-14
4감일슈퍼감북동하남시 감일동 14-52024-03-14
5GS25하남감북점감북동하남시 감북동 346-132024-03-14
6CU하남감북점감북동하남시 감북동 362-152024-03-14
7GS25 하남배다리점감북동하남시 감북동 419-112024-03-14
8GS25 하남서부점감북동하남시 감일동 2-52024-03-14
9GS25 하남충전소점감북동하남시 감북동 446-12024-03-14
거래처명행정동주소데이터기준일자
415초이휴캠핑장초이동하남시 초이동 692024-03-14
416하남크린주식회사초이동하남시 초일동 277-162024-03-14
417씨유 초광산단점초이동하남시 초이동 6232024-03-14
418GS25 하남춘궁점춘궁동하남시 하사창동 259-22024-03-14
419GS25 하남교산점춘궁동하남시 교산동 122-62024-03-14
420지에스25(GS25) 하남하사창동점춘궁동하남시 하사창동 117-132024-03-14
421CU하남둘레길점춘궁동하남시 춘궁동 308-42024-03-14
422마이편의점(하사창점)춘궁동하남시 하사창동 402-22024-03-14
423이마트24 하남춘궁점춘궁동하남시 춘궁동 315-12024-03-14
424서부농업협동조합춘궁동하남시 춘궁동 248-92024-03-14