Overview

Dataset statistics

Number of variables16
Number of observations362
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.1 KiB
Average record size in memory130.4 B

Variable types

Text5
Categorical10
DateTime1

Dataset

Description파일 다운로드
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-10817/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
점검기관.1 has constant value ""Constant
업종명 is highly overall correlated with 업종코드High correlation
업종코드 is highly overall correlated with 업종명High correlation
인허가번호 is highly imbalanced (97.3%)Imbalance
지도점검구분 is highly imbalanced (66.2%)Imbalance
처분대상여부 is highly imbalanced (75.9%)Imbalance
조치내역 is highly imbalanced (90.0%)Imbalance
비고사항 is highly imbalanced (92.0%)Imbalance

Reproduction

Analysis started2024-05-11 06:49:08.974637
Analysis finished2024-05-11 06:49:10.995588
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct131
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T15:49:11.228728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length8.9889503
Min length3

Characters and Unicode

Total characters3254
Distinct characters221
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)8.8%

Sample

1st row중부운수(주)
2nd row대지손세차장
3rd row신길교통(주)
4th row(주)이지스오토랩
5th row남부빌딩 관리단
ValueCountFrequency (%)
탑 9
 
1.8%
신정서부점 9
 
1.8%
현대자동차 9
 
1.8%
디테일 9
 
1.8%
중부운수(주 8
 
1.6%
애니카랜드 8
 
1.6%
신정점 8
 
1.6%
서울교통공사 8
 
1.6%
신정차량사업소 8
 
1.6%
서울에너지공사 7
 
1.4%
Other values (157) 425
83.7%
2024-05-11T15:49:11.749545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 185
 
5.7%
) 148
 
4.5%
( 148
 
4.5%
146
 
4.5%
동 94
 
2.9%
차 88
 
2.7%
소 76
 
2.3%
서 76
 
2.3%
스 75
 
2.3%
지 63
 
1.9%
Other values (211) 2155
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2740
84.2%
Close Punctuation 149
 
4.6%
Open Punctuation 149
 
4.6%
Space Separator 146
 
4.5%
Uppercase Letter 46
 
1.4%
Lowercase Letter 20
 
0.6%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 185
 
6.8%
동 94
 
3.4%
차 88
 
3.2%
소 76
 
2.8%
서 76
 
2.8%
스 75
 
2.7%
지 63
 
2.3%
신 61
 
2.2%
유 61
 
2.2%
대 54
 
2.0%
Other values (187) 1907
69.6%
Uppercase Letter
ValueCountFrequency (%)
K 15
32.6%
S 9
19.6%
D 5
 
10.9%
M 5
 
10.9%
O 3
 
6.5%
T 3
 
6.5%
R 1
 
2.2%
E 1
 
2.2%
A 1
 
2.2%
V 1
 
2.2%
Other values (2) 2
 
4.3%
Decimal Number
ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
4 1
25.0%
6 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
a 10
50.0%
n 5
25.0%
i 5
25.0%
Close Punctuation
ValueCountFrequency (%)
) 148
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 148
99.3%
[ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2740
84.2%
Common 448
 
13.8%
Latin 66
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 185
 
6.8%
동 94
 
3.4%
차 88
 
3.2%
소 76
 
2.8%
서 76
 
2.8%
스 75
 
2.7%
지 63
 
2.3%
신 61
 
2.2%
유 61
 
2.2%
대 54
 
2.0%
Other values (187) 1907
69.6%
Latin
ValueCountFrequency (%)
K 15
22.7%
a 10
15.2%
S 9
13.6%
n 5
 
7.6%
i 5
 
7.6%
D 5
 
7.6%
M 5
 
7.6%
O 3
 
4.5%
T 3
 
4.5%
R 1
 
1.5%
Other values (5) 5
 
7.6%
Common
ValueCountFrequency (%)
) 148
33.0%
( 148
33.0%
146
32.6%
3 1
 
0.2%
[ 1
 
0.2%
] 1
 
0.2%
0 1
 
0.2%
4 1
 
0.2%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2740
84.2%
ASCII 514
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 185
 
6.8%
동 94
 
3.4%
차 88
 
3.2%
소 76
 
2.8%
서 76
 
2.8%
스 75
 
2.7%
지 63
 
2.3%
신 61
 
2.2%
유 61
 
2.2%
대 54
 
2.0%
Other values (187) 1907
69.6%
ASCII
ValueCountFrequency (%)
) 148
28.8%
( 148
28.8%
146
28.4%
K 15
 
2.9%
a 10
 
1.9%
S 9
 
1.8%
n 5
 
1.0%
i 5
 
1.0%
D 5
 
1.0%
M 5
 
1.0%
Other values (14) 18
 
3.5%

인허가번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3.14E+17
361 
 
1

Length

Max length8
Median length8
Mean length7.980663
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row3.14E+17
2nd row3.14E+17
3rd row3.14E+17
4th row3.14E+17
5th row3.14E+17

Common Values

ValueCountFrequency (%)
3.14E+17 361
99.7%
1
 
0.3%

Length

2024-05-11T15:49:11.971526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:12.104459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.14e+17 361
100.0%

업종코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
22
290 
21
72 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22
2nd row22
3rd row22
4th row22
5th row21

Common Values

ValueCountFrequency (%)
22 290
80.1%
21 72
 
19.9%

Length

2024-05-11T15:49:12.262511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:12.398232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 290
80.1%
21 72
 
19.9%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
폐수배출업소관리
290 
대기배출업소관리
72 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐수배출업소관리
2nd row폐수배출업소관리
3rd row폐수배출업소관리
4th row폐수배출업소관리
5th row대기배출업소관리

Common Values

ValueCountFrequency (%)
폐수배출업소관리 290
80.1%
대기배출업소관리 72
 
19.9%

Length

2024-05-11T15:49:12.524755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:12.683949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 290
80.1%
대기배출업소관리 72
 
19.9%

지도점검일자
Date

Distinct164
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2018-01-18 00:00:00
Maximum2023-12-28 00:00:00
2024-05-11T15:49:12.879661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:49:13.101791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3140000
362 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 362
100.0%

Length

2024-05-11T15:49:13.317878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:13.461919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 362
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
서울특별시 양천구
362 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 양천구
2nd row서울특별시 양천구
3rd row서울특별시 양천구
4th row서울특별시 양천구
5th row서울특별시 양천구

Common Values

ValueCountFrequency (%)
서울특별시 양천구 362
100.0%

Length

2024-05-11T15:49:13.616591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:13.779895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 362
50.0%
양천구 362
50.0%

점검기관.1
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
서울특별시 양천구
362 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 양천구
2nd row서울특별시 양천구
3rd row서울특별시 양천구
4th row서울특별시 양천구
5th row서울특별시 양천구

Common Values

ValueCountFrequency (%)
서울특별시 양천구 362
100.0%

Length

2024-05-11T15:49:13.911513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:14.028949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 362
50.0%
양천구 362
50.0%

지도점검구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
정기
323 
수시
36 
합동
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 323
89.2%
수시 36
 
9.9%
합동 3
 
0.8%

Length

2024-05-11T15:49:14.159020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:14.292922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 323
89.2%
수시 36
 
9.9%
합동 3
 
0.8%

처분대상여부
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
N
340 
 
16
Y
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 340
93.9%
16
 
4.4%
Y 6
 
1.7%

Length

2024-05-11T15:49:14.461214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:14.608861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 340
98.3%
y 6
 
1.7%

점검사항
Text

Distinct79
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T15:49:14.826728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length13.660221
Min length1

Characters and Unicode

Total characters4945
Distinct characters75
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)10.5%

Sample

1st row폐수배출방지시설 적정 운영여부 등
2nd row폐수배출방지시설 적정 운영여부 등
3rd row폐수배출방지시설 적정 운영여부 등
4th row폐수배출방지시설 적정 운영여부 등
5th row대기배출시설 및 방지시설 가동상태 환경기술인 교육 이수 여부 운영일지 작성 상태 등
ValueCountFrequency (%)
여부 129
12.1%
폐수배출방지시설 111
 
10.4%
적정 108
 
10.2%
적정운영 107
 
10.1%
배출시설 72
 
6.8%
운영여부 59
 
5.5%
운영 58
 
5.5%
적정운영여부 55
 
5.2%
등 46
 
4.3%
방지시설 32
 
3.0%
Other values (56) 287
27.0%
2024-05-11T15:49:15.350942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
804
16.3%
설 319
 
6.5%
시 307
 
6.2%
배 303
 
6.1%
출 303
 
6.1%
운 295
 
6.0%
영 295
 
6.0%
정 280
 
5.7%
적 279
 
5.6%
여 246
 
5.0%
Other values (65) 1514
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4137
83.7%
Space Separator 804
 
16.3%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 319
 
7.7%
시 307
 
7.4%
배 303
 
7.3%
출 303
 
7.3%
운 295
 
7.1%
영 295
 
7.1%
정 280
 
6.8%
적 279
 
6.7%
여 246
 
5.9%
부 246
 
5.9%
Other values (62) 1264
30.6%
Space Separator
ValueCountFrequency (%)
804
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4137
83.7%
Common 808
 
16.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 319
 
7.7%
시 307
 
7.4%
배 303
 
7.3%
출 303
 
7.3%
운 295
 
7.1%
영 295
 
7.1%
정 280
 
6.8%
적 279
 
6.7%
여 246
 
5.9%
부 246
 
5.9%
Other values (62) 1264
30.6%
Common
ValueCountFrequency (%)
804
99.5%
) 2
 
0.2%
( 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4137
83.7%
ASCII 808
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
804
99.5%
) 2
 
0.2%
( 2
 
0.2%
Hangul
ValueCountFrequency (%)
설 319
 
7.7%
시 307
 
7.4%
배 303
 
7.3%
출 303
 
7.3%
운 295
 
7.1%
영 295
 
7.1%
정 280
 
6.8%
적 279
 
6.7%
여 246
 
5.9%
부 246
 
5.9%
Other values (62) 1264
30.6%

점검결과
Text

Distinct66
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T15:49:15.692992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length107
Median length7
Mean length9.0414365
Min length1

Characters and Unicode

Total characters3273
Distinct characters184
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)14.6%

Sample

1st row특이사항 없음
2nd row특이사항 없음
3rd row특이사항 없음
4th row특이사항 없음
5th row이상없음
ValueCountFrequency (%)
없음 257
31.5%
특이사항 254
31.1%
특이사항없음 44
 
5.4%
당시 13
 
1.6%
적정운영 12
 
1.5%
시료채취 6
 
0.7%
점검 5
 
0.6%
적정관리 5
 
0.6%
환경오염도 4
 
0.5%
방지시설 4
 
0.5%
Other values (172) 213
26.1%
2024-05-11T15:49:16.302928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
467
14.3%
이 312
 
9.5%
사 312
 
9.5%
항 308
 
9.4%
음 308
 
9.4%
없 305
 
9.3%
특 298
 
9.1%
시 45
 
1.4%
정 28
 
0.9%
. 26
 
0.8%
Other values (174) 864
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2670
81.6%
Space Separator 467
 
14.3%
Decimal Number 65
 
2.0%
Other Punctuation 29
 
0.9%
Close Punctuation 13
 
0.4%
Open Punctuation 13
 
0.4%
Dash Punctuation 9
 
0.3%
Uppercase Letter 5
 
0.2%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 312
11.7%
사 312
11.7%
항 308
11.5%
음 308
11.5%
없 305
11.4%
특 298
11.2%
시 45
 
1.7%
정 28
 
1.0%
수 24
 
0.9%
적 23
 
0.9%
Other values (152) 707
26.5%
Decimal Number
ValueCountFrequency (%)
0 18
27.7%
1 17
26.2%
2 12
18.5%
9 6
 
9.2%
6 3
 
4.6%
5 3
 
4.6%
8 2
 
3.1%
3 2
 
3.1%
7 2
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
T 1
20.0%
O 1
20.0%
C 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 26
89.7%
· 2
 
6.9%
% 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
p 1
50.0%
Space Separator
ValueCountFrequency (%)
467
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2670
81.6%
Common 596
 
18.2%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 312
11.7%
사 312
11.7%
항 308
11.5%
음 308
11.5%
없 305
11.4%
특 298
11.2%
시 45
 
1.7%
정 28
 
1.0%
수 24
 
0.9%
적 23
 
0.9%
Other values (152) 707
26.5%
Common
ValueCountFrequency (%)
467
78.4%
. 26
 
4.4%
0 18
 
3.0%
1 17
 
2.9%
) 13
 
2.2%
( 13
 
2.2%
2 12
 
2.0%
- 9
 
1.5%
9 6
 
1.0%
6 3
 
0.5%
Other values (6) 12
 
2.0%
Latin
ValueCountFrequency (%)
S 2
28.6%
T 1
14.3%
h 1
14.3%
p 1
14.3%
O 1
14.3%
C 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2670
81.6%
ASCII 601
 
18.4%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
467
77.7%
. 26
 
4.3%
0 18
 
3.0%
1 17
 
2.8%
) 13
 
2.2%
( 13
 
2.2%
2 12
 
2.0%
- 9
 
1.5%
9 6
 
1.0%
6 3
 
0.5%
Other values (11) 17
 
2.8%
Hangul
ValueCountFrequency (%)
이 312
11.7%
사 312
11.7%
항 308
11.5%
음 308
11.5%
없 305
11.4%
특 298
11.2%
시 45
 
1.7%
정 28
 
1.0%
수 24
 
0.9%
적 23
 
0.9%
Other values (152) 707
26.5%
None
ValueCountFrequency (%)
· 2
100.0%

조치내역
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
349 
.
 
3
과태료
 
2
경고
 
2
<NA>
 
1
Other values (5)
 
5

Length

Max length19
Median length1
Mean length1.1353591
Min length1

Unique

Unique6 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
349
96.4%
. 3
 
0.8%
과태료 2
 
0.6%
경고 2
 
0.6%
<NA> 1
 
0.3%
경고 과태료 개선명령 1
 
0.3%
경고 과태료 1
 
0.3%
ㅡ 1
 
0.3%
경고 및 과태료 1
 
0.3%
행정처분(1차 조업정지10일) 고발 1
 
0.3%

Length

2024-05-11T15:49:16.513021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:16.687878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과태료 5
25.0%
경고 5
25.0%
3
15.0%
na 1
 
5.0%
개선명령 1
 
5.0%
ㅡ 1
 
5.0%
및 1
 
5.0%
행정처분(1차 1
 
5.0%
조업정지10일 1
 
5.0%
고발 1
 
5.0%

비고사항
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
355 
시료채취
 
5
특이사항 없음
 
1
가동개시
 
1

Length

Max length7
Median length1
Mean length1.0662983
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
355
98.1%
시료채취 5
 
1.4%
특이사항 없음 1
 
0.3%
가동개시 1
 
0.3%

Length

2024-05-11T15:49:16.895052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:49:17.075122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시료채취 5
62.5%
특이사항 1
 
12.5%
없음 1
 
12.5%
가동개시 1
 
12.5%

소재지(도로명)
Text

Distinct115
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T15:49:17.537014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length22.889503
Min length1

Characters and Unicode

Total characters8286
Distinct characters129
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)6.6%

Sample

1st row서울특별시 양천구 지양로 106 (신월동)
2nd row서울특별시 양천구 곰달래로14길 20 (신월동)
3rd row서울특별시 양천구 월정로 117 신길교통 주식회사 (신월동)
4th row서울특별시 양천구 가로공원로 133 스위트드림빌딩 (신월동)
5th row서울특별시 양천구 신월로 389 남부빌딩 (신정동)
ValueCountFrequency (%)
서울특별시 323
19.0%
양천구 323
19.0%
신월동 128
 
7.5%
신정동 126
 
7.4%
목동 69
 
4.1%
남부순환로 35
 
2.1%
안양천로 24
 
1.4%
지양로 21
 
1.2%
가로공원로 20
 
1.2%
중앙로 13
 
0.8%
Other values (164) 621
36.5%
2024-05-11T15:49:18.056186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1419
 
17.1%
동 409
 
4.9%
양 371
 
4.5%
천 347
 
4.2%
로 344
 
4.2%
서 342
 
4.1%
울 328
 
4.0%
별 326
 
3.9%
특 324
 
3.9%
시 324
 
3.9%
Other values (119) 3752
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5212
62.9%
Space Separator 1419
 
17.1%
Decimal Number 985
 
11.9%
Open Punctuation 323
 
3.9%
Close Punctuation 323
 
3.9%
Dash Punctuation 22
 
0.3%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 409
 
7.8%
양 371
 
7.1%
천 347
 
6.7%
로 344
 
6.6%
서 342
 
6.6%
울 328
 
6.3%
별 326
 
6.3%
특 324
 
6.2%
시 324
 
6.2%
구 323
 
6.2%
Other values (103) 1774
34.0%
Decimal Number
ValueCountFrequency (%)
1 242
24.6%
2 142
14.4%
3 114
11.6%
7 93
 
9.4%
0 80
 
8.1%
4 79
 
8.0%
5 71
 
7.2%
6 69
 
7.0%
9 50
 
5.1%
8 45
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
1419
100.0%
Open Punctuation
ValueCountFrequency (%)
( 323
100.0%
Close Punctuation
ValueCountFrequency (%)
) 323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5212
62.9%
Common 3072
37.1%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 409
 
7.8%
양 371
 
7.1%
천 347
 
6.7%
로 344
 
6.6%
서 342
 
6.6%
울 328
 
6.3%
별 326
 
6.3%
특 324
 
6.2%
시 324
 
6.2%
구 323
 
6.2%
Other values (103) 1774
34.0%
Common
ValueCountFrequency (%)
1419
46.2%
( 323
 
10.5%
) 323
 
10.5%
1 242
 
7.9%
2 142
 
4.6%
3 114
 
3.7%
7 93
 
3.0%
0 80
 
2.6%
4 79
 
2.6%
5 71
 
2.3%
Other values (4) 186
 
6.1%
Latin
ValueCountFrequency (%)
M 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5212
62.9%
ASCII 3074
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1419
46.2%
( 323
 
10.5%
) 323
 
10.5%
1 242
 
7.9%
2 142
 
4.6%
3 114
 
3.7%
7 93
 
3.0%
0 80
 
2.6%
4 79
 
2.6%
5 71
 
2.3%
Other values (6) 188
 
6.1%
Hangul
ValueCountFrequency (%)
동 409
 
7.8%
양 371
 
7.1%
천 347
 
6.7%
로 344
 
6.6%
서 342
 
6.6%
울 328
 
6.3%
별 326
 
6.3%
특 324
 
6.2%
시 324
 
6.2%
구 323
 
6.2%
Other values (103) 1774
34.0%

소재지(지번)
Text

Distinct110
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T15:49:18.383925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length19.038674
Min length1

Characters and Unicode

Total characters6892
Distinct characters101
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)6.1%

Sample

1st row서울특별시 양천구 신월동 338
2nd row서울특별시 양천구 신월동 234-24
3rd row서울특별시 양천구 신월동 228-2 신길교통 주식회사
4th row서울특별시 양천구 신월동 82-1 스위트드림빌딩
5th row서울특별시 양천구 신정동 1009-6 남부빌딩
ValueCountFrequency (%)
서울특별시 323
23.5%
양천구 323
23.5%
신정동 130
 
9.5%
신월동 128
 
9.3%
목동 65
 
4.7%
900 13
 
0.9%
939-7 9
 
0.7%
목동오피스텔 9
 
0.7%
212-1 9
 
0.7%
338 8
 
0.6%
Other values (119) 356
25.9%
2024-05-11T15:49:18.861294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1402
20.3%
동 334
 
4.8%
울 326
 
4.7%
서 326
 
4.7%
별 325
 
4.7%
양 324
 
4.7%
천 323
 
4.7%
구 323
 
4.7%
시 323
 
4.7%
특 323
 
4.7%
Other values (91) 2563
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3834
55.6%
Space Separator 1402
 
20.3%
Decimal Number 1374
 
19.9%
Dash Punctuation 280
 
4.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 334
8.7%
울 326
8.5%
서 326
8.5%
별 325
8.5%
양 324
8.5%
천 323
8.4%
구 323
8.4%
시 323
8.4%
특 323
8.4%
신 267
7.0%
Other values (77) 640
16.7%
Decimal Number
ValueCountFrequency (%)
1 288
21.0%
2 173
12.6%
9 151
11.0%
4 123
9.0%
3 114
 
8.3%
0 111
 
8.1%
8 111
 
8.1%
5 104
 
7.6%
7 101
 
7.4%
6 98
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
1402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3834
55.6%
Common 3056
44.3%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 334
8.7%
울 326
8.5%
서 326
8.5%
별 325
8.5%
양 324
8.5%
천 323
8.4%
구 323
8.4%
시 323
8.4%
특 323
8.4%
신 267
7.0%
Other values (77) 640
16.7%
Common
ValueCountFrequency (%)
1402
45.9%
1 288
 
9.4%
- 280
 
9.2%
2 173
 
5.7%
9 151
 
4.9%
4 123
 
4.0%
3 114
 
3.7%
0 111
 
3.6%
8 111
 
3.6%
5 104
 
3.4%
Other values (2) 199
 
6.5%
Latin
ValueCountFrequency (%)
J 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3834
55.6%
ASCII 3058
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1402
45.8%
1 288
 
9.4%
- 280
 
9.2%
2 173
 
5.7%
9 151
 
4.9%
4 123
 
4.0%
3 114
 
3.7%
0 111
 
3.6%
8 111
 
3.6%
5 104
 
3.4%
Other values (4) 201
 
6.6%
Hangul
ValueCountFrequency (%)
동 334
8.7%
울 326
8.5%
서 326
8.5%
별 325
8.5%
양 324
8.5%
천 323
8.4%
구 323
8.4%
시 323
8.4%
특 323
8.4%
신 267
7.0%
Other values (77) 640
16.7%

Correlations

2024-05-11T15:49:18.974204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검구분처분대상여부점검사항점검결과조치내역비고사항
인허가번호1.0000.0000.0000.0000.0000.0001.0000.0000.000
업종코드0.0001.0001.0000.1050.1160.9440.5520.0850.000
업종명0.0001.0001.0000.1050.1160.9440.5520.0850.000
지도점검구분0.0000.1050.1051.0000.6370.7690.7810.1120.077
처분대상여부0.0000.1160.1160.6371.0000.7320.9250.6710.240
점검사항0.0000.9440.9440.7690.7321.0000.9840.9500.714
점검결과1.0000.5520.5520.7810.9250.9841.0000.9900.718
조치내역0.0000.0850.0850.1120.6710.9500.9901.0000.000
비고사항0.0000.0000.0000.0770.2400.7140.7180.0001.000
2024-05-11T15:49:19.113486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고사항지도점검구분조치내역처분대상여부인허가번호업종명업종코드
비고사항1.0000.0720.0000.2290.0000.0000.000
지도점검구분0.0721.0000.0480.3010.0000.1740.174
조치내역0.0000.0481.0000.3800.0000.0830.083
처분대상여부0.2290.3010.3801.0000.0000.1910.191
인허가번호0.0000.0000.0000.0001.0000.0000.000
업종명0.0000.1740.0830.1910.0001.0000.991
업종코드0.0000.1740.0830.1910.0000.9911.000
2024-05-11T15:49:19.224225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검구분처분대상여부조치내역비고사항
인허가번호1.0000.0000.0000.0000.0000.0000.000
업종코드0.0001.0000.9910.1740.1910.0830.000
업종명0.0000.9911.0000.1740.1910.0830.000
지도점검구분0.0000.1740.1741.0000.3010.0480.072
처분대상여부0.0000.1910.1910.3011.0000.3800.229
조치내역0.0000.0830.0830.0480.3801.0000.000
비고사항0.0000.0000.0000.0720.2290.0001.000

Missing values

2024-05-11T15:49:10.574174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:49:10.875523image/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

업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명점검기관.1지도점검구분처분대상여부점검사항점검결과조치내역비고사항소재지(도로명)소재지(지번)
0중부운수(주)3.14E+1722폐수배출업소관리2023-12-283140000서울특별시 양천구서울특별시 양천구정기N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 지양로 106 (신월동)서울특별시 양천구 신월동 338
1대지손세차장3.14E+1722폐수배출업소관리2023-12-283140000서울특별시 양천구서울특별시 양천구정기N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 곰달래로14길 20 (신월동)서울특별시 양천구 신월동 234-24
2신길교통(주)3.14E+1722폐수배출업소관리2023-12-203140000서울특별시 양천구서울특별시 양천구정기N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 월정로 117 신길교통 주식회사 (신월동)서울특별시 양천구 신월동 228-2 신길교통 주식회사
3(주)이지스오토랩3.14E+1722폐수배출업소관리2023-12-203140000서울특별시 양천구서울특별시 양천구정기N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 가로공원로 133 스위트드림빌딩 (신월동)서울특별시 양천구 신월동 82-1 스위트드림빌딩
4남부빌딩 관리단3.14E+1721대기배출업소관리2023-12-213140000서울특별시 양천구서울특별시 양천구정기N대기배출시설 및 방지시설 가동상태 환경기술인 교육 이수 여부 운영일지 작성 상태 등이상없음서울특별시 양천구 신월로 389 남부빌딩 (신정동)서울특별시 양천구 신정동 1009-6 남부빌딩
5서울시학생체육관 강서분관3.14E+1721대기배출업소관리2023-12-213140000서울특별시 양천구서울특별시 양천구정기N대기배출시설 및 방지시설 가동상태 환경기술인 교육 이수 여부 운영일지 작성 상태 등이상없음서울특별시 양천구 월정로 280 (신월동)
6목동현대자동차정비3.14E+1721대기배출업소관리2023-12-213140000서울특별시 양천구서울특별시 양천구정기대기배출시설 및 방지시설 가동 상태 환경기술인 교육 이수 여부 운영일지 작성 상태 등이상없음서울특별시 양천구 신정중앙로 81 (신정동)서울특별시 양천구 신정동 886-12
7에이치디현대오일뱅크(주)직영 양천현대셀프주유소3.14E+1722폐수배출업소관리2023-12-073140000서울특별시 양천구서울특별시 양천구수시N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 안양천로 1179 (목동)
8SK에너지(주) 경인주유소3.14E+1722폐수배출업소관리2023-12-073140000서울특별시 양천구서울특별시 양천구수시N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 국회대로 170 (신정동)서울특별시 양천구 신정동 872-5
9에이치지에너지3.14E+1722폐수배출업소관리2023-12-053140000서울특별시 양천구서울특별시 양천구정기N폐수배출방지시설 적정 운영여부 등특이사항 없음서울특별시 양천구 월정로 208 (신월동)서울특별시 양천구 신월동 87-10
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명점검기관.1지도점검구분처분대상여부점검사항점검결과조치내역비고사항소재지(도로명)소재지(지번)
352신목동세차장3.14E+1722폐수배출업소관리2018-05-183140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 목동동로10길 13 (신정동 외 9필지)서울특별시 양천구 신정동 296-5 외 9필지
353(주)서부티엔디주유소3.14E+1722폐수배출업소관리2018-05-183140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 신정동 743
354삼보이엔씨(주)3.14E+1722폐수배출업소관리2018-05-173140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 신월동 863
355광혁건설(주)3.14E+1722폐수배출업소관리2018-05-173140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 목동 914-5
356서울에너지공사 서부지사(목동열병합발전소)3.14E+1722폐수배출업소관리2018-04-043140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 목동 900
357양천자원회수시설3.14E+1722폐수배출업소관리2018-04-043140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 목동 900
358목동열병합발전소3.14E+1721대기배출업소관리2018-04-043140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 목동서로 20 (목동)서울특별시 양천구 목동 900
359양천자원회수시설3.14E+1721대기배출업소관리2018-04-043140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 안양천로 1121 (목동)서울특별시 양천구 목동 900
360에이치지에너지(가로공원주유소)3.14E+1722폐수배출업소관리2018-02-013140000서울특별시 양천구서울특별시 양천구수시N특이사항 없음서울특별시 양천구 월정로 208 (신월동)서울특별시 양천구 신월동 87-10
361애니카랜드 신정점3.14E+1722폐수배출업소관리2018-01-183140000서울특별시 양천구서울특별시 양천구정기N특이사항 없음서울특별시 양천구 중앙로32길 85 (신정동)서울특별시 양천구 신정동 1015-14