Overview

Dataset statistics

Number of variables3
Number of observations152
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory24.9 B

Variable types

Categorical1
Text2

Dataset

Description서울특별시 성동구 음식물폐기물 다량배출사업장 현황 자료입니다. 사업장명, 소재지 시군구, 도로명주소 등의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15034303/fileData.do

Alerts

시군구 has constant value ""Constant
사업장명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:38:02.741529
Analysis finished2023-12-12 02:38:03.169057
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
성동구
152 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 152
100.0%

Length

2023-12-12T11:38:03.246549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:38:03.371726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성동구 152
100.0%

사업장명
Text

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T11:38:03.727031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length23
Mean length10.118421
Min length2

Characters and Unicode

Total characters1538
Distinct characters286
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

Unique152 ?
Unique (%)100.0%

Sample

1st row대림리빙프라자(행당대림상가)
2nd row우리집_밥
3rd row인생한우
4th row한우마을
5th row채선당 성수점
ValueCountFrequency (%)
한양대학교 6
 
2.5%
주식회사 6
 
2.5%
성수점 5
 
2.1%
㈜아워홈 4
 
1.7%
구내식당 4
 
1.7%
장학복지회 4
 
1.7%
㈜엘에스씨푸드 2
 
0.8%
육백 2
 
0.8%
서울숲점 2
 
0.8%
서울교통공사 2
 
0.8%
Other values (201) 204
84.6%
2023-12-12T11:38:04.288353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
5.9%
학 63
 
4.1%
교 58
 
3.8%
) 32
 
2.1%
( 32
 
2.1%
등 30
 
2.0%
대 29
 
1.9%
서 29
 
1.9%
원 28
 
1.8%
드 26
 
1.7%
Other values (276) 1121
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1339
87.1%
Space Separator 90
 
5.9%
Close Punctuation 33
 
2.1%
Open Punctuation 33
 
2.1%
Other Symbol 19
 
1.2%
Decimal Number 10
 
0.7%
Other Punctuation 6
 
0.4%
Uppercase Letter 5
 
0.3%
Dash Punctuation 2
 
0.1%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 63
 
4.7%
교 58
 
4.3%
등 30
 
2.2%
대 29
 
2.2%
서 29
 
2.2%
원 28
 
2.1%
드 26
 
1.9%
성 26
 
1.9%
한 26
 
1.9%
식 25
 
1.9%
Other values (258) 999
74.6%
Decimal Number
ValueCountFrequency (%)
2 3
30.0%
9 2
20.0%
8 2
20.0%
1 2
20.0%
0 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
T 2
40.0%
V 1
20.0%
I 1
20.0%
W 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 32
97.0%
] 1
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 32
97.0%
[ 1
 
3.0%
Space Separator
ValueCountFrequency (%)
90
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1358
88.3%
Common 175
 
11.4%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 63
 
4.6%
교 58
 
4.3%
등 30
 
2.2%
대 29
 
2.1%
서 29
 
2.1%
원 28
 
2.1%
드 26
 
1.9%
성 26
 
1.9%
한 26
 
1.9%
식 25
 
1.8%
Other values (259) 1018
75.0%
Common
ValueCountFrequency (%)
90
51.4%
) 32
 
18.3%
( 32
 
18.3%
. 6
 
3.4%
2 3
 
1.7%
- 2
 
1.1%
9 2
 
1.1%
8 2
 
1.1%
1 2
 
1.1%
_ 1
 
0.6%
Other values (3) 3
 
1.7%
Latin
ValueCountFrequency (%)
T 2
40.0%
V 1
20.0%
I 1
20.0%
W 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1339
87.1%
ASCII 180
 
11.7%
None 19
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
50.0%
) 32
 
17.8%
( 32
 
17.8%
. 6
 
3.3%
2 3
 
1.7%
- 2
 
1.1%
9 2
 
1.1%
8 2
 
1.1%
1 2
 
1.1%
T 2
 
1.1%
Other values (7) 7
 
3.9%
Hangul
ValueCountFrequency (%)
학 63
 
4.7%
교 58
 
4.3%
등 30
 
2.2%
대 29
 
2.2%
서 29
 
2.2%
원 28
 
2.1%
드 26
 
1.9%
성 26
 
1.9%
한 26
 
1.9%
식 25
 
1.9%
Other values (258) 999
74.6%
None
ValueCountFrequency (%)
㈜ 19
100.0%

주소
Text

Distinct147
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T11:38:04.647969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length14.421053
Min length7

Characters and Unicode

Total characters2192
Distinct characters146
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

Unique143 ?
Unique (%)94.1%

Sample

1st row 행당로 87
2nd row 성수이로 147 지하1층 105호
3rd row 마장로31길 43, 지상2층
4th row 고산자로24길 11, 2층
5th row 왕십리로 38
ValueCountFrequency (%)
왕십리로 22
 
5.2%
지하1층 11
 
2.6%
아차산로 10
 
2.4%
2층 8
 
1.9%
222 7
 
1.7%
1층 7
 
1.7%
천호대로 6
 
1.4%
성수일로 6
 
1.4%
성수이로 6
 
1.4%
마장로 5
 
1.2%
Other values (251) 334
79.1%
2023-12-12T11:38:05.231578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
426
19.4%
1 177
 
8.1%
2 130
 
5.9%
로 127
 
5.8%
길 72
 
3.3%
3 59
 
2.7%
층 58
 
2.6%
0 57
 
2.6%
, 49
 
2.2%
4 46
 
2.1%
Other values (136) 991
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 994
45.3%
Decimal Number 641
29.2%
Space Separator 426
19.4%
Other Punctuation 49
 
2.2%
Dash Punctuation 20
 
0.9%
Close Punctuation 19
 
0.9%
Open Punctuation 19
 
0.9%
Uppercase Letter 19
 
0.9%
Lowercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 127
 
12.8%
길 72
 
7.2%
층 58
 
5.8%
호 33
 
3.3%
리 30
 
3.0%
수 27
 
2.7%
성 26
 
2.6%
산 24
 
2.4%
지 23
 
2.3%
왕 23
 
2.3%
Other values (109) 551
55.4%
Decimal Number
ValueCountFrequency (%)
1 177
27.6%
2 130
20.3%
3 59
 
9.2%
0 57
 
8.9%
4 46
 
7.2%
7 45
 
7.0%
6 36
 
5.6%
8 34
 
5.3%
9 29
 
4.5%
5 28
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
26.3%
R 3
15.8%
A 3
15.8%
T 3
15.8%
I 2
 
10.5%
L 1
 
5.3%
J 1
 
5.3%
S 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
w 2
40.0%
r 1
20.0%
o 1
20.0%
e 1
20.0%
Space Separator
ValueCountFrequency (%)
426
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1174
53.6%
Hangul 994
45.3%
Latin 24
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 127
 
12.8%
길 72
 
7.2%
층 58
 
5.8%
호 33
 
3.3%
리 30
 
3.0%
수 27
 
2.7%
성 26
 
2.6%
산 24
 
2.4%
지 23
 
2.3%
왕 23
 
2.3%
Other values (109) 551
55.4%
Common
ValueCountFrequency (%)
426
36.3%
1 177
15.1%
2 130
 
11.1%
3 59
 
5.0%
0 57
 
4.9%
, 49
 
4.2%
4 46
 
3.9%
7 45
 
3.8%
6 36
 
3.1%
8 34
 
2.9%
Other values (5) 115
 
9.8%
Latin
ValueCountFrequency (%)
B 5
20.8%
R 3
12.5%
A 3
12.5%
T 3
12.5%
I 2
 
8.3%
w 2
 
8.3%
L 1
 
4.2%
J 1
 
4.2%
S 1
 
4.2%
r 1
 
4.2%
Other values (2) 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1198
54.7%
Hangul 994
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
426
35.6%
1 177
14.8%
2 130
 
10.9%
3 59
 
4.9%
0 57
 
4.8%
, 49
 
4.1%
4 46
 
3.8%
7 45
 
3.8%
6 36
 
3.0%
8 34
 
2.8%
Other values (17) 139
 
11.6%
Hangul
ValueCountFrequency (%)
로 127
 
12.8%
길 72
 
7.2%
층 58
 
5.8%
호 33
 
3.3%
리 30
 
3.0%
수 27
 
2.7%
성 26
 
2.6%
산 24
 
2.4%
지 23
 
2.3%
왕 23
 
2.3%
Other values (109) 551
55.4%

Missing values

2023-12-12T11:38:03.033236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:38:03.124435image/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

시군구사업장명주소
0성동구대림리빙프라자(행당대림상가)행당로 87
1성동구우리집_밥성수이로 147 지하1층 105호
2성동구인생한우마장로31길 43, 지상2층
3성동구한우마을고산자로24길 11, 2층
4성동구채선당 성수점왕십리로 38
5성동구주식회사 레노스고산자로 202
6성동구㈜한아름라이프(한양대병원 장례식장)왕십리로 222-1지층
7성동구조개창고(구. 왕십리조개창고 주식회사)왕십리로 331
8성동구정은회관(구. 은행나무집)금호로 45(정은타워1층)
9성동구전주본가영양돌솥밥한림말길 18
시군구사업장명주소
142성동구성수동 셋째집상원1길 26, 서울숲A타워 1층 101호, 102호,103호
143성동구본우리집밥 한양대학교 서울병원점왕십리로 222, 한양대학교 지1층 (04763)
144성동구이십사절기 주식회사왕십리로 222, 한양대학교 701동 6층 (04763)
145성동구주식회사 카페온화 성수점아차산로 78, 1층
146성동구연세슬기병원무학로2길 8 (04707)
147성동구픽스홀딩 본말감자탕아차산로 49, 103호 104호
148성동구살롱드호우섬 성수점왕십리로 83-21 디타워 아크로포레스트 지하1층 B101-1호 (04769)
149성동구설내옥설렁탕금호로 141-2, 1층, 2층(04728)
150성동구왕십리포차무학로2길 52, 1층(04709)
151성동구모르므로연무장길 17, 2층