Overview

Dataset statistics

Number of variables13
Number of observations400
Missing cells582
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.7 KiB
Average record size in memory109.3 B

Variable types

Text4
Numeric2
Categorical5
Boolean1
Unsupported1

Dataset

Description업체(시설)명,인허가번호,업종코드,업종명,지도점검일자,점검기관,점검기관명,지도점검구분,처분대상여부,점검사항,점검결과,소재지도로명주소,소재지주소
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-10586/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
업종명 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
업종코드 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
인허가번호 is highly overall correlated with 업종코드 and 1 other fieldsHigh correlation
처분대상여부 is highly imbalanced (92.2%)Imbalance
처분대상여부 has 89 (22.2%) missing valuesMissing
점검결과 has 400 (100.0%) missing valuesMissing
소재지도로명주소 has 76 (19.0%) missing valuesMissing
소재지주소 has 17 (4.2%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:05:58.062926
Analysis finished2024-05-11 06:06:00.518351
Duration2.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct149
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-05-11T15:06:00.832334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length8.7225
Min length3

Characters and Unicode

Total characters3489
Distinct characters256
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

Unique72 ?
Unique (%)18.0%

Sample

1st row서울특별시보라매병원
2nd row(주)아스타아이비에스보라매나산스위트
3rd row전문건설공제조합
4th row롯데타워업무시설관리단대표회의
5th row서울특별시보라매병원
ValueCountFrequency (%)
범한택시여객자동차(주 18
 
4.1%
수협노량진수산(주 13
 
3.0%
서울특별시보라매병원 12
 
2.8%
중앙대학교 12
 
2.8%
현대자동차(주)남부사업소 11
 
2.5%
대방대림아파트 9
 
2.1%
대성산업(주)노량진주유소 9
 
2.1%
숭실대학교 9
 
2.1%
노량진수산(주 8
 
1.8%
주)gimco 8
 
1.8%
Other values (153) 325
74.9%
2024-05-11T15:06:01.598345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 188
 
5.4%
동 132
 
3.8%
( 132
 
3.8%
) 132
 
3.8%
대 119
 
3.4%
차 98
 
2.8%
원 85
 
2.4%
사 76
 
2.2%
소 71
 
2.0%
자 67
 
1.9%
Other values (246) 2389
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3079
88.2%
Open Punctuation 132
 
3.8%
Close Punctuation 132
 
3.8%
Uppercase Letter 73
 
2.1%
Space Separator 34
 
1.0%
Decimal Number 30
 
0.9%
Lowercase Letter 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 188
 
6.1%
동 132
 
4.3%
대 119
 
3.9%
차 98
 
3.2%
원 85
 
2.8%
사 76
 
2.5%
소 71
 
2.3%
자 67
 
2.2%
유 61
 
2.0%
의 58
 
1.9%
Other values (228) 2124
69.0%
Uppercase Letter
ValueCountFrequency (%)
S 18
24.7%
K 15
20.5%
G 8
11.0%
I 8
11.0%
M 8
11.0%
C 8
11.0%
O 8
11.0%
Decimal Number
ValueCountFrequency (%)
3 10
33.3%
2 9
30.0%
1 9
30.0%
5 1
 
3.3%
6 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
l 3
33.3%
e 3
33.3%
f 3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3079
88.2%
Common 328
 
9.4%
Latin 82
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 188
 
6.1%
동 132
 
4.3%
대 119
 
3.9%
차 98
 
3.2%
원 85
 
2.8%
사 76
 
2.5%
소 71
 
2.3%
자 67
 
2.2%
유 61
 
2.0%
의 58
 
1.9%
Other values (228) 2124
69.0%
Latin
ValueCountFrequency (%)
S 18
22.0%
K 15
18.3%
G 8
9.8%
I 8
9.8%
M 8
9.8%
C 8
9.8%
O 8
9.8%
l 3
 
3.7%
e 3
 
3.7%
f 3
 
3.7%
Common
ValueCountFrequency (%)
( 132
40.2%
) 132
40.2%
34
 
10.4%
3 10
 
3.0%
2 9
 
2.7%
1 9
 
2.7%
5 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3079
88.2%
ASCII 410
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 188
 
6.1%
동 132
 
4.3%
대 119
 
3.9%
차 98
 
3.2%
원 85
 
2.8%
사 76
 
2.5%
소 71
 
2.3%
자 67
 
2.2%
유 61
 
2.0%
의 58
 
1.9%
Other values (228) 2124
69.0%
ASCII
ValueCountFrequency (%)
( 132
32.2%
) 132
32.2%
34
 
8.3%
S 18
 
4.4%
K 15
 
3.7%
3 10
 
2.4%
2 9
 
2.2%
1 9
 
2.2%
G 8
 
2.0%
I 8
 
2.0%
Other values (8) 35
 
8.5%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1900002 × 1017
Minimum3.1900002 × 1017
Maximum3.1900006 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:01.885939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1900002 × 1017
5-th percentile3.1900002 × 1017
Q13.1900002 × 1017
median3.1900002 × 1017
Q33.1900002 × 1017
95-th percentile3.1900003 × 1017
Maximum3.1900006 × 1017
Range4.0001 × 1010
Interquartile range (IQR)900096

Descriptive statistics

Standard deviation3.7347879 × 109
Coefficient of variation (CV)1.1707798 × 10-8
Kurtosis61.574353
Mean3.1900002 × 1017
Median Absolute Deviation (MAD)899968
Skewness7.1091166
Sum-1.5271993 × 1018
Variance1.394864 × 1019
MonotonicityNot monotonic
2024-05-11T15:06:02.195599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
319000022200000015 18
 
4.5%
319000021200000002 11
 
2.8%
319000022200000020 10
 
2.5%
319000021200000003 9
 
2.2%
319000021200600002 9
 
2.2%
319000022200000025 9
 
2.2%
319000022200000043 9
 
2.2%
319000022200500282 9
 
2.2%
319000022200000026 9
 
2.2%
319000021200600001 7
 
1.8%
Other values (135) 300
75.0%
ValueCountFrequency (%)
319000021200000002 11
2.8%
319000021200000003 9
2.2%
319000021200600001 7
1.8%
319000021200600002 9
2.2%
319000021200600004 7
1.8%
319000021200700002 7
1.8%
319000021201500001 1
 
0.2%
319000021201500004 3
 
0.8%
319000021201500005 2
 
0.5%
319000021201500006 1
 
0.2%
ValueCountFrequency (%)
319000061201000003 1
0.2%
319000061201000002 1
0.2%
319000042201100003 1
0.2%
319000042201100001 1
0.2%
319000042200900002 1
0.2%
319000042200500001 2
0.5%
319000025201200003 1
0.2%
319000025201200002 1
0.2%
319000025201100133 1
0.2%
319000025201100006 1
0.2%

업종코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
22
228 
21
90 
25
77 
42
 
5

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
22 228
57.0%
21 90
 
22.5%
25 77
 
19.2%
42 5
 
1.2%

Length

2024-05-11T15:06:02.459071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:02.649279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 228
57.0%
21 90
 
22.5%
25 77
 
19.2%
42 5
 
1.2%

업종명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
폐수배출업소관리
204 
<NA>
88 
대기배출업소관리
69 
기타수질오염원관리
37 
유독물판매업관리
 
2

Length

Max length9
Median length8
Mean length7.2125
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 204
51.0%
<NA> 88
22.0%
대기배출업소관리 69
 
17.2%
기타수질오염원관리 37
 
9.2%
유독물판매업관리 2
 
0.5%

Length

2024-05-11T15:06:02.849789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:03.069375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 204
51.0%
na 88
22.0%
대기배출업소관리 69
 
17.2%
기타수질오염원관리 37
 
9.2%
유독물판매업관리 2
 
0.5%

지도점검일자
Real number (ℝ)

Distinct165
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20135587
Minimum20100115
Maximum20171027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:03.324656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100115
5-th percentile20100625
Q120120809
median20130627
Q320160519
95-th percentile20170915
Maximum20171027
Range70912
Interquartile range (IQR)39710

Descriptive statistics

Standard deviation22771.788
Coefficient of variation (CV)0.0011309225
Kurtosis-1.2182564
Mean20135587
Median Absolute Deviation (MAD)19915
Skewness0.12403655
Sum8.0542346 × 109
Variance5.1855435 × 108
MonotonicityDecreasing
2024-05-11T15:06:03.628016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121204 9
 
2.2%
20121024 8
 
2.0%
20121023 7
 
1.8%
20151016 7
 
1.8%
20121217 7
 
1.8%
20151015 6
 
1.5%
20170525 6
 
1.5%
20171026 6
 
1.5%
20121121 6
 
1.5%
20130620 5
 
1.2%
Other values (155) 333
83.2%
ValueCountFrequency (%)
20100115 1
 
0.2%
20100223 3
0.8%
20100303 2
0.5%
20100316 1
 
0.2%
20100319 3
0.8%
20100423 2
0.5%
20100430 1
 
0.2%
20100520 2
0.5%
20100528 2
0.5%
20100607 1
 
0.2%
ValueCountFrequency (%)
20171027 5
1.2%
20171026 6
1.5%
20171025 1
 
0.2%
20171018 2
 
0.5%
20171017 3
0.8%
20171016 1
 
0.2%
20171010 1
 
0.2%
20170928 1
 
0.2%
20170914 4
1.0%
20170911 2
 
0.5%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
3190000
400 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 400
100.0%

Length

2024-05-11T15:06:03.901839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:04.077085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 400
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
서울특별시 동작구
400 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 동작구 400
100.0%

Length

2024-05-11T15:06:04.250793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:04.412333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 400
50.0%
동작구 400
50.0%

지도점검구분
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
정기
293 
수시
45 
합동
40 
기타
 
16
<NA>
 
6

Length

Max length4
Median length2
Mean length2.03
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 293
73.2%
수시 45
 
11.2%
합동 40
 
10.0%
기타 16
 
4.0%
<NA> 6
 
1.5%

Length

2024-05-11T15:06:04.608345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:04.802229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 293
73.2%
수시 45
 
11.2%
합동 40
 
10.0%
기타 16
 
4.0%
na 6
 
1.5%

처분대상여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.6%
Missing89
Missing (%)22.2%
Memory size932.0 B
False
308 
True
 
3
(Missing)
89 
ValueCountFrequency (%)
False 308
77.0%
True 3
 
0.8%
(Missing) 89
 
22.2%
2024-05-11T15:06:04.973416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct175
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-05-11T15:06:05.348202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51
Mean length20.3075
Min length2

Characters and Unicode

Total characters8123
Distinct characters138
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

Unique127 ?
Unique (%)31.8%

Sample

1st row배출시설 및 방지시설 적정가동 여부
2nd row배출시설 적정가동여부
3rd row배출시설 및 방지시설 적정가동여부
4th row배출시설 적정가동 여부
5th row배출시설 적정 가동 여부
ValueCountFrequency (%)
여부 267
 
13.6%
및 225
 
11.5%
방지시설 217
 
11.1%
배출시설 213
 
10.9%
적정가동 84
 
4.3%
정상가동 71
 
3.6%
등 70
 
3.6%
폐수배출시설 51
 
2.6%
적정 47
 
2.4%
기타수질오염원 43
 
2.2%
Other values (174) 672
34.3%
2024-05-11T15:06:06.066903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1560
19.2%
시 529
 
6.5%
설 519
 
6.4%
부 425
 
5.2%
여 419
 
5.2%
정 363
 
4.5%
출 313
 
3.9%
배 310
 
3.8%
가 259
 
3.2%
지 254
 
3.1%
Other values (128) 3172
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6536
80.5%
Space Separator 1560
 
19.2%
Other Punctuation 22
 
0.3%
Decimal Number 3
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 529
 
8.1%
설 519
 
7.9%
부 425
 
6.5%
여 419
 
6.4%
정 363
 
5.6%
출 313
 
4.8%
배 310
 
4.7%
가 259
 
4.0%
지 254
 
3.9%
동 253
 
3.9%
Other values (123) 2892
44.2%
Space Separator
ValueCountFrequency (%)
1560
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6536
80.5%
Common 1587
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 529
 
8.1%
설 519
 
7.9%
부 425
 
6.5%
여 419
 
6.4%
정 363
 
5.6%
출 313
 
4.8%
배 310
 
4.7%
가 259
 
4.0%
지 254
 
3.9%
동 253
 
3.9%
Other values (123) 2892
44.2%
Common
ValueCountFrequency (%)
1560
98.3%
, 22
 
1.4%
2 3
 
0.2%
( 1
 
0.1%
) 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6536
80.5%
ASCII 1587
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1560
98.3%
, 22
 
1.4%
2 3
 
0.2%
( 1
 
0.1%
) 1
 
0.1%
Hangul
ValueCountFrequency (%)
시 529
 
8.1%
설 519
 
7.9%
부 425
 
6.5%
여 419
 
6.4%
정 363
 
5.6%
출 313
 
4.8%
배 310
 
4.7%
가 259
 
4.0%
지 254
 
3.9%
동 253
 
3.9%
Other values (123) 2892
44.2%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing400
Missing (%)100.0%
Memory size3.6 KiB

소재지도로명주소
Text

MISSING 

Distinct141
Distinct (%)43.5%
Missing76
Missing (%)19.0%
Memory size3.3 KiB
2024-05-11T15:06:06.473851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length27.070988
Min length22

Characters and Unicode

Total characters8771
Distinct characters153
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)20.7%

Sample

1st row서울특별시 동작구 보라매로5길 20 (신대방동, 서울특별시보라매병원)
2nd row서울특별시 동작구 보라매로5가길 24 (신대방동, 보라매나산스위트)
3rd row서울특별시 동작구 보라매로5길 15 (신대방동, 전문건설회관빌딩)
4th row서울특별시 동작구 보라매로5길 51 (신대방동, 롯데타워)
5th row서울특별시 동작구 보라매로5길 20 (신대방동, 서울특별시보라매병원)
ValueCountFrequency (%)
서울특별시 324
19.2%
동작구 322
19.1%
대방동 77
 
4.6%
노량진동 49
 
2.9%
상도동 47
 
2.8%
신대방동 41
 
2.4%
사당동 40
 
2.4%
상도로 39
 
2.3%
노량진로 36
 
2.1%
노들로 21
 
1.2%
Other values (208) 691
41.0%
2024-05-11T15:06:06.961523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1417
 
16.2%
동 708
 
8.1%
작 358
 
4.1%
시 351
 
4.0%
서 344
 
3.9%
울 337
 
3.8%
별 335
 
3.8%
특 335
 
3.8%
구 327
 
3.7%
( 324
 
3.7%
Other values (143) 3935
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5522
63.0%
Space Separator 1417
 
16.2%
Decimal Number 1076
 
12.3%
Open Punctuation 324
 
3.7%
Close Punctuation 324
 
3.7%
Other Punctuation 97
 
1.1%
Dash Punctuation 7
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 708
 
12.8%
작 358
 
6.5%
시 351
 
6.4%
서 344
 
6.2%
울 337
 
6.1%
별 335
 
6.1%
특 335
 
6.1%
구 327
 
5.9%
로 306
 
5.5%
대 255
 
4.6%
Other values (125) 1866
33.8%
Decimal Number
ValueCountFrequency (%)
1 230
21.4%
2 157
14.6%
4 114
10.6%
6 114
10.6%
3 108
10.0%
5 83
 
7.7%
0 77
 
7.2%
8 70
 
6.5%
7 65
 
6.0%
9 58
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 94
96.9%
/ 3
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
B 2
50.0%
Space Separator
ValueCountFrequency (%)
1417
100.0%
Open Punctuation
ValueCountFrequency (%)
( 324
100.0%
Close Punctuation
ValueCountFrequency (%)
) 324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5522
63.0%
Common 3245
37.0%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 708
 
12.8%
작 358
 
6.5%
시 351
 
6.4%
서 344
 
6.2%
울 337
 
6.1%
별 335
 
6.1%
특 335
 
6.1%
구 327
 
5.9%
로 306
 
5.5%
대 255
 
4.6%
Other values (125) 1866
33.8%
Common
ValueCountFrequency (%)
1417
43.7%
( 324
 
10.0%
) 324
 
10.0%
1 230
 
7.1%
2 157
 
4.8%
4 114
 
3.5%
6 114
 
3.5%
3 108
 
3.3%
, 94
 
2.9%
5 83
 
2.6%
Other values (6) 280
 
8.6%
Latin
ValueCountFrequency (%)
D 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5522
63.0%
ASCII 3249
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1417
43.6%
( 324
 
10.0%
) 324
 
10.0%
1 230
 
7.1%
2 157
 
4.8%
4 114
 
3.5%
6 114
 
3.5%
3 108
 
3.3%
, 94
 
2.9%
5 83
 
2.6%
Other values (8) 284
 
8.7%
Hangul
ValueCountFrequency (%)
동 708
 
12.8%
작 358
 
6.5%
시 351
 
6.4%
서 344
 
6.2%
울 337
 
6.1%
별 335
 
6.1%
특 335
 
6.1%
구 327
 
5.9%
로 306
 
5.5%
대 255
 
4.6%
Other values (125) 1866
33.8%

소재지주소
Text

MISSING 

Distinct134
Distinct (%)35.0%
Missing17
Missing (%)4.2%
Memory size3.3 KiB
2024-05-11T15:06:07.305918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length23.339426
Min length14

Characters and Unicode

Total characters8939
Distinct characters90
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)15.1%

Sample

1st row서울특별시 동작구 신대방동 395-68번지
2nd row서울특별시 동작구 신대방동 395-70번지
3rd row서울특별시 동작구 노량진동 330번지
4th row서울특별시 동작구 상도동 188-19번지
5th row서울특별시 동작구 상도동 1-1번지
ValueCountFrequency (%)
서울특별시 383
23.7%
동작구 383
23.7%
대방동 100
 
6.2%
상도동 82
 
5.1%
신대방동 66
 
4.1%
사당동 59
 
3.6%
노량진동 41
 
2.5%
흑석동 28
 
1.7%
397-2번지 13
 
0.8%
70-1번지 13
 
0.8%
Other values (165) 450
27.8%
2024-05-11T15:06:07.866308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1625
18.2%
동 781
 
8.7%
서 394
 
4.4%
특 392
 
4.4%
별 392
 
4.4%
시 392
 
4.4%
울 392
 
4.4%
작 383
 
4.3%
구 383
 
4.3%
지 381
 
4.3%
Other values (80) 3424
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5408
60.5%
Space Separator 1625
 
18.2%
Decimal Number 1581
 
17.7%
Dash Punctuation 315
 
3.5%
Other Punctuation 4
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 781
14.4%
서 394
 
7.3%
특 392
 
7.2%
별 392
 
7.2%
시 392
 
7.2%
울 392
 
7.2%
작 383
 
7.1%
구 383
 
7.1%
지 381
 
7.0%
번 371
 
6.9%
Other values (63) 1147
21.2%
Decimal Number
ValueCountFrequency (%)
1 324
20.5%
3 188
11.9%
4 185
11.7%
2 183
11.6%
6 143
9.0%
7 142
9.0%
8 121
 
7.7%
0 117
 
7.4%
5 98
 
6.2%
9 80
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
B 2
50.0%
Space Separator
ValueCountFrequency (%)
1625
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 315
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5408
60.5%
Common 3527
39.5%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 781
14.4%
서 394
 
7.3%
특 392
 
7.2%
별 392
 
7.2%
시 392
 
7.2%
울 392
 
7.2%
작 383
 
7.1%
구 383
 
7.1%
지 381
 
7.0%
번 371
 
6.9%
Other values (63) 1147
21.2%
Common
ValueCountFrequency (%)
1625
46.1%
1 324
 
9.2%
- 315
 
8.9%
3 188
 
5.3%
4 185
 
5.2%
2 183
 
5.2%
6 143
 
4.1%
7 142
 
4.0%
8 121
 
3.4%
0 117
 
3.3%
Other values (5) 184
 
5.2%
Latin
ValueCountFrequency (%)
D 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5408
60.5%
ASCII 3531
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1625
46.0%
1 324
 
9.2%
- 315
 
8.9%
3 188
 
5.3%
4 185
 
5.2%
2 183
 
5.2%
6 143
 
4.0%
7 142
 
4.0%
8 121
 
3.4%
0 117
 
3.3%
Other values (7) 188
 
5.3%
Hangul
ValueCountFrequency (%)
동 781
14.4%
서 394
 
7.3%
특 392
 
7.2%
별 392
 
7.2%
시 392
 
7.2%
울 392
 
7.2%
작 383
 
7.1%
구 383
 
7.1%
지 381
 
7.0%
번 371
 
6.9%
Other values (63) 1147
21.2%

Interactions

2024-05-11T15:05:59.255411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:58.922021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:59.440240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:59.076341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:06:08.158389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부
인허가번호1.0000.9720.9740.5730.3500.000
업종코드0.9721.0001.0000.6330.3690.000
업종명0.9741.0001.0000.6790.2340.000
지도점검일자0.5730.6330.6791.0000.5570.000
지도점검구분0.3500.3690.2340.5571.0000.000
처분대상여부0.0000.0000.0000.0000.0001.000
2024-05-11T15:06:08.354707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명지도점검구분업종코드처분대상여부
업종명1.0000.0931.0000.000
지도점검구분0.0931.0000.1510.000
업종코드1.0000.1511.0000.000
처분대상여부0.0000.0000.0001.000
2024-05-11T15:06:08.552116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호지도점검일자업종코드업종명지도점검구분처분대상여부
인허가번호1.000-0.1470.7730.7810.1420.000
지도점검일자-0.1471.0000.3230.3570.2750.000
업종코드0.7730.3231.0001.0000.1510.000
업종명0.7810.3571.0001.0000.0930.000
지도점검구분0.1420.2750.1510.0931.0000.000
처분대상여부0.0000.0000.0000.0000.0001.000

Missing values

2024-05-11T15:05:59.723911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:06:00.085139image/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.
2024-05-11T15:06:00.395275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
0서울특별시보라매병원31900002120150000821대기배출업소관리201710273190000서울특별시 동작구정기N배출시설 및 방지시설 적정가동 여부<NA>서울특별시 동작구 보라매로5길 20 (신대방동, 서울특별시보라매병원)<NA>
1(주)아스타아이비에스보라매나산스위트31900002120150001821대기배출업소관리201710273190000서울특별시 동작구정기N배출시설 적정가동여부<NA>서울특별시 동작구 보라매로5가길 24 (신대방동, 보라매나산스위트)서울특별시 동작구 신대방동 395-68번지
2전문건설공제조합31900002120150000521대기배출업소관리201710273190000서울특별시 동작구정기N배출시설 및 방지시설 적정가동여부<NA>서울특별시 동작구 보라매로5길 15 (신대방동, 전문건설회관빌딩)서울특별시 동작구 신대방동 395-70번지
3롯데타워업무시설관리단대표회의31900002120150000721대기배출업소관리201710273190000서울특별시 동작구정기N배출시설 적정가동 여부<NA>서울특별시 동작구 보라매로5길 51 (신대방동, 롯데타워)<NA>
4서울특별시보라매병원31900002120150000821대기배출업소관리201710273190000서울특별시 동작구정기N배출시설 적정 가동 여부<NA>서울특별시 동작구 보라매로5길 20 (신대방동, 서울특별시보라매병원)<NA>
5삼익사우나31900002120150001521대기배출업소관리201710263190000서울특별시 동작구정기N배출시설 및 방지시설 적정가동 여부<NA>서울특별시 동작구 만양로 84, 지하1층 (노량진동, 삼익주상복합아파트)서울특별시 동작구 노량진동 330번지
6의료법인성석의료재단 동작경희병원31900002220000015022폐수배출업소관리201710263190000서울특별시 동작구정기N배출시설 및 방지시설 적정가동 여부<NA>서울특별시 동작구 상도로 146 (상도동)서울특별시 동작구 상도동 188-19번지
7숭실대학교31900002220000002122폐수배출업소관리201710263190000서울특별시 동작구정기N개선명령 이행사항 확인<NA>서울특별시 동작구 상도로 369 (상도1동)서울특별시 동작구 상도동 1-1번지
8경유산업(주)31900002120150001721대기배출업소관리201710263190000서울특별시 동작구정기N배출시설 적정가동여부<NA>서울특별시 동작구 동작대로 115 (사당동, 태평백화점)서울특별시 동작구 사당동 136-1번지
9동작문화복지센터31900002120150001221대기배출업소관리201710263190000서울특별시 동작구정기N배출시설 및 방지지설 적정 가동여부<NA>서울특별시 동작구 장승배기로10길 42 (상도동, 동작문화복지센타)서울특별시 동작구 상도동 176-3번지
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
390범한택시여객자동차(주)31900002220000002622폐수배출업소관리201003193190000서울특별시 동작구정기N배출시설 및 방지시설 정상가동여부 확인<NA><NA>서울특별시 동작구 대방동 397-2번지
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