Overview

Dataset statistics

Number of variables4
Number of observations380
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory32.3 B

Variable types

Text3
DateTime1

Dataset

Description부산광역시수영구_종량제봉투판매소현황_20220826
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078430

Reproduction

Analysis started2023-12-10 16:53:14.623843
Analysis finished2023-12-10 16:53:15.195125
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종량제봉투 판매소명
Text

Distinct371
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-11T01:53:15.448496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.2421053
Min length2

Characters and Unicode

Total characters3132
Distinct characters293
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

Unique364 ?
Unique (%)95.8%

Sample

1st row(주)메가마트 남천점
2nd row(주)쿱스토어부산 남천점
3rd rowCU편의점 남천점
4th rowGS25 남천강안점
5th rowGS25 남천바다점
ValueCountFrequency (%)
씨유 45
 
7.6%
gs25 40
 
6.8%
세븐일레븐 36
 
6.1%
이마트24 14
 
2.4%
미니스톱 12
 
2.0%
남천점 6
 
1.0%
수영점 6
 
1.0%
더마트 5
 
0.8%
위드미 5
 
0.8%
망미점 5
 
0.8%
Other values (379) 415
70.5%
2023-12-11T01:53:15.952456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 209
 
6.7%
209
 
6.7%
마 104
 
3.3%
트 103
 
3.3%
븐 86
 
2.7%
2 82
 
2.6%
광 82
 
2.6%
수 77
 
2.5%
안 75
 
2.4%
영 71
 
2.3%
Other values (283) 2034
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2542
81.2%
Space Separator 209
 
6.7%
Decimal Number 169
 
5.4%
Uppercase Letter 128
 
4.1%
Open Punctuation 37
 
1.2%
Close Punctuation 37
 
1.2%
Lowercase Letter 8
 
0.3%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 209
 
8.2%
마 104
 
4.1%
트 103
 
4.1%
븐 86
 
3.4%
광 82
 
3.2%
수 77
 
3.0%
안 75
 
3.0%
영 71
 
2.8%
산 65
 
2.6%
세 65
 
2.6%
Other values (257) 1605
63.1%
Uppercase Letter
ValueCountFrequency (%)
S 51
39.8%
G 50
39.1%
C 10
 
7.8%
U 5
 
3.9%
J 4
 
3.1%
M 2
 
1.6%
B 2
 
1.6%
I 1
 
0.8%
K 1
 
0.8%
N 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 82
48.5%
5 58
34.3%
4 21
 
12.4%
1 4
 
2.4%
3 2
 
1.2%
7 2
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
s 3
37.5%
e 2
25.0%
k 2
25.0%
g 1
 
12.5%
Space Separator
ValueCountFrequency (%)
209
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2542
81.2%
Common 454
 
14.5%
Latin 136
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 209
 
8.2%
마 104
 
4.1%
트 103
 
4.1%
븐 86
 
3.4%
광 82
 
3.2%
수 77
 
3.0%
안 75
 
3.0%
영 71
 
2.8%
산 65
 
2.6%
세 65
 
2.6%
Other values (257) 1605
63.1%
Latin
ValueCountFrequency (%)
S 51
37.5%
G 50
36.8%
C 10
 
7.4%
U 5
 
3.7%
J 4
 
2.9%
s 3
 
2.2%
M 2
 
1.5%
B 2
 
1.5%
e 2
 
1.5%
k 2
 
1.5%
Other values (5) 5
 
3.7%
Common
ValueCountFrequency (%)
209
46.0%
2 82
 
18.1%
5 58
 
12.8%
( 37
 
8.1%
) 37
 
8.1%
4 21
 
4.6%
1 4
 
0.9%
3 2
 
0.4%
7 2
 
0.4%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2542
81.2%
ASCII 590
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 209
 
8.2%
마 104
 
4.1%
트 103
 
4.1%
븐 86
 
3.4%
광 82
 
3.2%
수 77
 
3.0%
안 75
 
3.0%
영 71
 
2.8%
산 65
 
2.6%
세 65
 
2.6%
Other values (257) 1605
63.1%
ASCII
ValueCountFrequency (%)
209
35.4%
2 82
 
13.9%
5 58
 
9.8%
S 51
 
8.6%
G 50
 
8.5%
( 37
 
6.3%
) 37
 
6.3%
4 21
 
3.6%
C 10
 
1.7%
U 5
 
0.8%
Other values (16) 30
 
5.1%

대표자명
Text

Distinct369
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-11T01:53:16.364793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0631579
Min length2

Characters and Unicode

Total characters1164
Distinct characters172
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique361 ?
Unique (%)95.0%

Sample

1st row신동익
2nd row김영옥
3rd row김현자
4th row최치훈
5th row강경희
ValueCountFrequency (%)
최경호 5
 
1.3%
김영옥 2
 
0.5%
이원진 2
 
0.5%
외 2
 
0.5%
김용선 2
 
0.5%
1명 2
 
0.5%
박선영 2
 
0.5%
김미경 2
 
0.5%
허다희 2
 
0.5%
이영호 2
 
0.5%
Other values (362) 362
94.0%
2023-12-11T01:53:16.936448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 74
 
6.4%
김 70
 
6.0%
정 57
 
4.9%
영 41
 
3.5%
박 38
 
3.3%
숙 29
 
2.5%
경 25
 
2.1%
최 23
 
2.0%
희 21
 
1.8%
순 19
 
1.6%
Other values (162) 767
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1151
98.9%
Space Separator 5
 
0.4%
Decimal Number 4
 
0.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 74
 
6.4%
김 70
 
6.1%
정 57
 
5.0%
영 41
 
3.6%
박 38
 
3.3%
숙 29
 
2.5%
경 25
 
2.2%
최 23
 
2.0%
희 21
 
1.8%
순 19
 
1.7%
Other values (158) 754
65.5%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
1 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1151
98.9%
Common 13
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 74
 
6.4%
김 70
 
6.1%
정 57
 
5.0%
영 41
 
3.6%
박 38
 
3.3%
숙 29
 
2.5%
경 25
 
2.2%
최 23
 
2.0%
희 21
 
1.8%
순 19
 
1.7%
Other values (158) 754
65.5%
Common
ValueCountFrequency (%)
5
38.5%
1 4
30.8%
( 2
 
15.4%
) 2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1151
98.9%
ASCII 13
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 74
 
6.4%
김 70
 
6.1%
정 57
 
5.0%
영 41
 
3.6%
박 38
 
3.3%
숙 29
 
2.5%
경 25
 
2.2%
최 23
 
2.0%
희 21
 
1.8%
순 19
 
1.7%
Other values (158) 754
65.5%
ASCII
ValueCountFrequency (%)
5
38.5%
1 4
30.8%
( 2
 
15.4%
) 2
 
15.4%

지정일자
Date

Distinct337
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1996-05-09 00:00:00
Maximum2022-08-01 00:00:00
2023-12-11T01:53:17.142603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:53:17.293302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업장 주소
Text

Distinct378
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-11T01:53:17.585470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length14.460526
Min length4

Characters and Unicode

Total characters5495
Distinct characters170
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

Unique376 ?
Unique (%)98.9%

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 134
 
11.4%
수영로 44
 
3.7%
1층 35
 
3.0%
연수로 22
 
1.9%
수영동 21
 
1.8%
망미1동 18
 
1.5%
민락동 17
 
1.4%
광안1동 17
 
1.4%
광안해변로 15
 
1.3%
광안3동 12
 
1.0%
Other values (539) 843
71.6%
2023-12-11T01:53:18.020874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
804
 
14.6%
1 491
 
8.9%
수 263
 
4.8%
로 258
 
4.7%
2 242
 
4.4%
영 230
 
4.2%
0 186
 
3.4%
3 180
 
3.3%
동 173
 
3.1%
번 172
 
3.1%
Other values (160) 2496
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2543
46.3%
Decimal Number 1889
34.4%
Space Separator 804
 
14.6%
Dash Punctuation 150
 
2.7%
Other Punctuation 42
 
0.8%
Close Punctuation 29
 
0.5%
Open Punctuation 29
 
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 (%)
수 263
 
10.3%
로 258
 
10.1%
영 230
 
9.0%
동 173
 
6.8%
번 172
 
6.8%
길 165
 
6.5%
구 150
 
5.9%
광 114
 
4.5%
안 88
 
3.5%
호 58
 
2.3%
Other values (135) 872
34.3%
Decimal Number
ValueCountFrequency (%)
1 491
26.0%
2 242
12.8%
0 186
 
9.8%
3 180
 
9.5%
4 169
 
8.9%
5 152
 
8.0%
6 133
 
7.0%
7 117
 
6.2%
8 114
 
6.0%
9 105
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
T 1
16.7%
O 1
16.7%
C 1
16.7%
B 1
16.7%
A 1
16.7%
M 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 38
90.5%
/ 3
 
7.1%
. 1
 
2.4%
Space Separator
ValueCountFrequency (%)
804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2945
53.6%
Hangul 2543
46.3%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 263
 
10.3%
로 258
 
10.1%
영 230
 
9.0%
동 173
 
6.8%
번 172
 
6.8%
길 165
 
6.5%
구 150
 
5.9%
광 114
 
4.5%
안 88
 
3.5%
호 58
 
2.3%
Other values (135) 872
34.3%
Common
ValueCountFrequency (%)
804
27.3%
1 491
16.7%
2 242
 
8.2%
0 186
 
6.3%
3 180
 
6.1%
4 169
 
5.7%
5 152
 
5.2%
- 150
 
5.1%
6 133
 
4.5%
7 117
 
4.0%
Other values (8) 321
 
10.9%
Latin
ValueCountFrequency (%)
T 1
14.3%
O 1
14.3%
C 1
14.3%
B 1
14.3%
A 1
14.3%
M 1
14.3%
e 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2952
53.7%
Hangul 2543
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
804
27.2%
1 491
16.6%
2 242
 
8.2%
0 186
 
6.3%
3 180
 
6.1%
4 169
 
5.7%
5 152
 
5.1%
- 150
 
5.1%
6 133
 
4.5%
7 117
 
4.0%
Other values (15) 328
11.1%
Hangul
ValueCountFrequency (%)
수 263
 
10.3%
로 258
 
10.1%
영 230
 
9.0%
동 173
 
6.8%
번 172
 
6.8%
길 165
 
6.5%
구 150
 
5.9%
광 114
 
4.5%
안 88
 
3.5%
호 58
 
2.3%
Other values (135) 872
34.3%

Missing values

2023-12-11T01:53:15.039928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:53:15.151965image/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
370이마트24 센텀비치푸르지오점이정석2020-01-14광안해변로 420, 상가동 2층 209~210호
371이마트24 수영다온채점김명숙2020-09-24수영구 광안해변로 307번길 15, 1층
372자유시간김영희2006-02-14민락동 18-1
373정마트이민정2016-01-04광안해변로 292 104호
374지에스(gs)25 광안오션테라스점권규정2020-05-27광안해변로 326번길 32, 112호
375탑세일마트안순호1997-02-19수영구 민락로34번길 62
376푸르지오수퍼고현근2006-07-28민락동 108-1 민락푸르지오 상가-210
377함안상회임평선2012-06-29민락동 161-7
378함양상회김동호2006-05-25민락동 714-11
379후레쉬 원 편의점오정화2007-08-07민락동 110-87 수변공원1길 39