Overview

Dataset statistics

Number of variables3
Number of observations510
Missing cells95
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory24.3 B

Variable types

Text3

Dataset

Description서울특별시 영등포구 관내 음식물폐기물 다량배출 사업장 현황 - 제공정보: 사업장명, 사업장위치(도로명 주소), 전화번호
URLhttps://www.data.go.kr/data/15034294/fileData.do

Alerts

전화번호 has 95 (18.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:12:48.344985
Analysis finished2023-12-11 23:12:48.829601
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct507
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T08:12:48.967059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length8.8078431
Min length2

Characters and Unicode

Total characters4492
Distinct characters513
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique504 ?
Unique (%)98.8%

Sample

1st row도림초등학교
2nd row영동초등학교
3rd row대길초등학교
4th row당산초등학교
5th row도신초등학교
ValueCountFrequency (%)
여의도점 26
 
3.7%
당산점 7
 
1.0%
㈜현대그린푸드 6
 
0.9%
주식회사 6
 
0.9%
여의도 5
 
0.7%
서여의도점 4
 
0.6%
㈜아워홈 4
 
0.6%
영등포점 4
 
0.6%
㈜엔타스 3
 
0.4%
본우리집밥 3
 
0.4%
Other values (600) 630
90.3%
2023-12-12T08:12:49.274028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
207
 
4.6%
점 143
 
3.2%
도 107
 
2.4%
의 93
 
2.1%
여 88
 
2.0%
㈜ 84
 
1.9%
스 80
 
1.8%
) 74
 
1.6%
이 74
 
1.6%
( 74
 
1.6%
Other values (503) 3468
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3884
86.5%
Space Separator 207
 
4.6%
Other Symbol 84
 
1.9%
Uppercase Letter 84
 
1.9%
Close Punctuation 74
 
1.6%
Open Punctuation 74
 
1.6%
Decimal Number 49
 
1.1%
Lowercase Letter 27
 
0.6%
Other Punctuation 7
 
0.2%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 143
 
3.7%
도 107
 
2.8%
의 93
 
2.4%
여 88
 
2.3%
스 80
 
2.1%
이 74
 
1.9%
등 67
 
1.7%
드 59
 
1.5%
교 57
 
1.5%
서 54
 
1.4%
Other values (446) 3062
78.8%
Uppercase Letter
ValueCountFrequency (%)
K 17
20.2%
C 8
 
9.5%
B 6
 
7.1%
S 5
 
6.0%
F 5
 
6.0%
O 5
 
6.0%
M 5
 
6.0%
I 4
 
4.8%
H 4
 
4.8%
G 3
 
3.6%
Other values (12) 22
26.2%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
l 2
 
7.4%
u 2
 
7.4%
o 2
 
7.4%
y 2
 
7.4%
i 2
 
7.4%
d 2
 
7.4%
a 2
 
7.4%
t 2
 
7.4%
w 1
 
3.7%
Other values (6) 6
22.2%
Decimal Number
ValueCountFrequency (%)
3 12
24.5%
2 7
14.3%
4 7
14.3%
0 5
10.2%
1 4
 
8.2%
6 4
 
8.2%
7 4
 
8.2%
9 3
 
6.1%
5 2
 
4.1%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 3
42.9%
& 3
42.9%
/ 1
 
14.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
207
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3968
88.3%
Common 411
 
9.1%
Latin 113
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 143
 
3.6%
도 107
 
2.7%
의 93
 
2.3%
여 88
 
2.2%
㈜ 84
 
2.1%
스 80
 
2.0%
이 74
 
1.9%
등 67
 
1.7%
드 59
 
1.5%
교 57
 
1.4%
Other values (447) 3116
78.5%
Latin
ValueCountFrequency (%)
K 17
 
15.0%
C 8
 
7.1%
B 6
 
5.3%
S 5
 
4.4%
F 5
 
4.4%
O 5
 
4.4%
M 5
 
4.4%
I 4
 
3.5%
e 4
 
3.5%
H 4
 
3.5%
Other values (30) 50
44.2%
Common
ValueCountFrequency (%)
207
50.4%
) 74
 
18.0%
( 74
 
18.0%
3 12
 
2.9%
2 7
 
1.7%
4 7
 
1.7%
0 5
 
1.2%
1 4
 
1.0%
6 4
 
1.0%
7 4
 
1.0%
Other values (6) 13
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3884
86.5%
ASCII 522
 
11.6%
None 84
 
1.9%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
207
39.7%
) 74
 
14.2%
( 74
 
14.2%
K 17
 
3.3%
3 12
 
2.3%
C 8
 
1.5%
2 7
 
1.3%
4 7
 
1.3%
B 6
 
1.1%
S 5
 
1.0%
Other values (44) 105
20.1%
Hangul
ValueCountFrequency (%)
점 143
 
3.7%
도 107
 
2.8%
의 93
 
2.4%
여 88
 
2.3%
스 80
 
2.1%
이 74
 
1.9%
등 67
 
1.7%
드 59
 
1.5%
교 57
 
1.5%
서 54
 
1.4%
Other values (446) 3062
78.8%
None
ValueCountFrequency (%)
㈜ 84
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

소재지
Text

Distinct503
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T08:12:49.548332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length52.5
Mean length32.464706
Min length17

Characters and Unicode

Total characters16557
Distinct characters281
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)97.3%

Sample

1st row서울특별시 영등포구 가마산로65길 22 (신길동)
2nd row서울특별시 영등포구 국회대로53길 20 (당산동)
3rd row서울특별시 영등포구 대방천로 206 (신길동)
4th row서울특별시 영등포구 선유로55길 32 (양평동4가)
5th row서울특별시 영등포구 도림로53길 32-9 (대림동)
ValueCountFrequency (%)
서울특별시 511
 
17.1%
영등포구 510
 
17.1%
지하1층 87
 
2.9%
여의도동 81
 
2.7%
1층 44
 
1.5%
2층 42
 
1.4%
국제금융로2길 26
 
0.9%
신길동 21
 
0.7%
영등포로 21
 
0.7%
의사당대로 21
 
0.7%
Other values (759) 1624
54.4%
2023-12-12T08:12:49.976812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2495
 
15.1%
1 674
 
4.1%
영 642
 
3.9%
등 592
 
3.6%
포 591
 
3.6%
서 531
 
3.2%
시 519
 
3.1%
울 519
 
3.1%
별 515
 
3.1%
구 514
 
3.1%
Other values (271) 8965
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10222
61.7%
Decimal Number 2525
 
15.3%
Space Separator 2495
 
15.1%
Other Punctuation 482
 
2.9%
Close Punctuation 328
 
2.0%
Open Punctuation 328
 
2.0%
Uppercase Letter 115
 
0.7%
Dash Punctuation 35
 
0.2%
Math Symbol 24
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 642
 
6.3%
등 592
 
5.8%
포 591
 
5.8%
서 531
 
5.2%
시 519
 
5.1%
울 519
 
5.1%
별 515
 
5.0%
구 514
 
5.0%
로 513
 
5.0%
특 511
 
5.0%
Other values (236) 4775
46.7%
Uppercase Letter
ValueCountFrequency (%)
B 38
33.0%
K 17
14.8%
C 11
 
9.6%
S 10
 
8.7%
T 6
 
5.2%
A 6
 
5.2%
G 5
 
4.3%
N 4
 
3.5%
V 4
 
3.5%
P 3
 
2.6%
Other values (6) 11
 
9.6%
Decimal Number
ValueCountFrequency (%)
1 674
26.7%
2 423
16.8%
3 305
12.1%
0 231
 
9.1%
6 204
 
8.1%
5 162
 
6.4%
4 161
 
6.4%
7 154
 
6.1%
8 149
 
5.9%
9 62
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 481
99.8%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 328
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10224
61.8%
Common 6217
37.5%
Latin 116
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 642
 
6.3%
등 592
 
5.8%
포 591
 
5.8%
서 531
 
5.2%
시 519
 
5.1%
울 519
 
5.1%
별 515
 
5.0%
구 514
 
5.0%
로 513
 
5.0%
특 511
 
5.0%
Other values (237) 4777
46.7%
Common
ValueCountFrequency (%)
2495
40.1%
1 674
 
10.8%
, 481
 
7.7%
2 423
 
6.8%
) 328
 
5.3%
( 328
 
5.3%
3 305
 
4.9%
0 231
 
3.7%
6 204
 
3.3%
5 162
 
2.6%
Other values (7) 586
 
9.4%
Latin
ValueCountFrequency (%)
B 38
32.8%
K 17
14.7%
C 11
 
9.5%
S 10
 
8.6%
T 6
 
5.2%
A 6
 
5.2%
G 5
 
4.3%
N 4
 
3.4%
V 4
 
3.4%
P 3
 
2.6%
Other values (7) 12
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10222
61.7%
ASCII 6333
38.2%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2495
39.4%
1 674
 
10.6%
, 481
 
7.6%
2 423
 
6.7%
) 328
 
5.2%
( 328
 
5.2%
3 305
 
4.8%
0 231
 
3.6%
6 204
 
3.2%
5 162
 
2.6%
Other values (24) 702
 
11.1%
Hangul
ValueCountFrequency (%)
영 642
 
6.3%
등 592
 
5.8%
포 591
 
5.8%
서 531
 
5.2%
시 519
 
5.1%
울 519
 
5.1%
별 515
 
5.0%
구 514
 
5.0%
로 513
 
5.0%
특 511
 
5.0%
Other values (236) 4775
46.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

전화번호
Text

MISSING 

Distinct408
Distinct (%)98.3%
Missing95
Missing (%)18.6%
Memory size4.1 KiB
2023-12-12T08:12:50.226252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length11.645783
Min length9

Characters and Unicode

Total characters4833
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)96.6%

Sample

1st row02-832-0590
2nd row02-2633-7450
3rd row02-842-3500
4th row070-4345-3774
5th row02-835-1504
ValueCountFrequency (%)
02-761-0073 2
 
0.5%
02-2019-9280 2
 
0.5%
02-2678-7898 2
 
0.5%
02-2177-8300 2
 
0.5%
02-2676-3374 2
 
0.5%
02-761-9937 2
 
0.5%
02-833-6488 2
 
0.5%
02-761-1666 1
 
0.2%
070-4830-4161 1
 
0.2%
02-782-9995 1
 
0.2%
Other values (398) 398
95.9%
2023-12-12T08:12:50.615323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 831
17.2%
2 798
16.5%
0 766
15.8%
7 457
9.5%
6 403
8.3%
8 397
8.2%
3 301
 
6.2%
1 259
 
5.4%
5 224
 
4.6%
9 205
 
4.2%
Other values (6) 192
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3996
82.7%
Dash Punctuation 831
 
17.2%
Space Separator 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 798
20.0%
0 766
19.2%
7 457
11.4%
6 403
10.1%
8 397
9.9%
3 301
 
7.5%
1 259
 
6.5%
5 224
 
5.6%
9 205
 
5.1%
4 186
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
, 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 831
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 831
17.2%
2 798
16.5%
0 766
15.8%
7 457
9.5%
6 403
8.3%
8 397
8.2%
3 301
 
6.2%
1 259
 
5.4%
5 224
 
4.6%
9 205
 
4.2%
Other values (6) 192
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 831
17.2%
2 798
16.5%
0 766
15.8%
7 457
9.5%
6 403
8.3%
8 397
8.2%
3 301
 
6.2%
1 259
 
5.4%
5 224
 
4.6%
9 205
 
4.2%
Other values (6) 192
 
4.0%

Missing values

2023-12-12T08:12:48.735413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:12:48.801153image/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

사업장명소재지전화번호
0도림초등학교서울특별시 영등포구 가마산로65길 22 (신길동)02-832-0590
1영동초등학교서울특별시 영등포구 국회대로53길 20 (당산동)02-2633-7450
2대길초등학교서울특별시 영등포구 대방천로 206 (신길동)02-842-3500
3당산초등학교서울특별시 영등포구 선유로55길 32 (양평동4가)070-4345-3774
4도신초등학교서울특별시 영등포구 도림로53길 32-9 (대림동)02-835-1504
5서울영문초등학교서울특별시 영등포구 문래로 56 (문래동6가)02-2068-5858
6당중초등학교서울특별시 영등포구 선유로 131 (양평동3가)02-2633-0149
7엄마손감자탕서울특별시 영등포구 은행로 3 (여의도동,익스콘벤처타워 비103호)02-2168-1258
8백두산 감자탕, 장군보쌈서울특별시 영등포구 도림로 176 (대림동)02-841-6614
9잠수함서울특별시 영등포구 여의대방로65길 20 (여의도동,외1필지 호성빌딩 지하1층(일부))02-780-7720
사업장명소재지전화번호
500본우리집밥 영등포구청점서울특별시 영등포구 당산로 123, 영등포구청 지하1층<NA>
501하반서울특별시 영등포구 63로 36, 2층 202호(여의도동, 리버타워)<NA>
502올리브 가든서울특별시 영등포구 경인로 775, 에이스하이테크시티 지하1층 148호<NA>
503푸디스트㈜한국예탁결제원점서울특별시 영등포구 여의나루로4길 23, 한국예탁결제원서울사옥 12층<NA>
504주식회사 하트웰(서울지방병무청)서울특별시 영등포구 여의대방로43길 13, 서울지방병무청(신길동)02-908-7711
505셀립 여의서울특별시 영등포구 영등포로 389<NA>
506소울한우 동여의도점서울특별시 영등포구 여의대방로67길 9, 지하1층<NA>
507흥부골 숯불돼지 왕갈비 영등포점서울특별시 영등포구 영중로 47, 1층<NA>
508경복궁여의도아이에프씨점㈜덕용푸드시스템서울특별시 영등포구 국제금융로 10, 지하층 101호02-6137-3050
509삿뽀로여의도아이에프씨점㈜덕용푸드시스템서울특별시 영등포구 국제금융로 10, 지하층 102호02-6137-3060