Overview

Dataset statistics

Number of variables13
Number of observations391
Missing cells800
Missing cells (%)15.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.7 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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-11202/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
처분대상여부 has constant value ""Constant
업종코드 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
인허가번호 is highly overall correlated with 업종코드 and 1 other fieldsHigh correlation
업종코드 is highly imbalanced (55.2%)Imbalance
처분대상여부 has 183 (46.8%) missing valuesMissing
점검결과 has 391 (100.0%) missing valuesMissing
소재지도로명주소 has 199 (50.9%) missing valuesMissing
소재지주소 has 27 (6.9%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 02:11:56.171965
Analysis finished2024-05-11 02:12:01.176128
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct153
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T02:12:01.412661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length7.5575448
Min length3

Characters and Unicode

Total characters2955
Distinct characters246
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

Unique72 ?
Unique (%)18.4%

Sample

1st row서진인쇄사
2nd row서울미라마유한회사
3rd row순천향대학병원
4th row임창피앤디
5th row임창피앤디
ValueCountFrequency (%)
호텔캐피탈 14
 
3.4%
순천향대학병원 12
 
2.9%
서울미라마유한회사 11
 
2.7%
애니카랜드 9
 
2.2%
우리문화 8
 
1.9%
신영인쇄 8
 
1.9%
jj쥬얼리 7
 
1.7%
솔로몬 7
 
1.7%
오토카정비공업사 7
 
1.7%
임창피앤디 7
 
1.7%
Other values (149) 324
78.3%
2024-05-11T02:12:02.323953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 124
 
4.2%
) 97
 
3.3%
( 97
 
3.3%
사 88
 
3.0%
차 60
 
2.0%
원 56
 
1.9%
정 54
 
1.8%
유 53
 
1.8%
비 53
 
1.8%
공 48
 
1.6%
Other values (236) 2225
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2676
90.6%
Close Punctuation 97
 
3.3%
Open Punctuation 97
 
3.3%
Uppercase Letter 36
 
1.2%
Space Separator 23
 
0.8%
Decimal Number 20
 
0.7%
Other Punctuation 3
 
0.1%
Connector Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 124
 
4.6%
사 88
 
3.3%
차 60
 
2.2%
원 56
 
2.1%
정 54
 
2.0%
유 53
 
2.0%
비 53
 
2.0%
공 48
 
1.8%
소 48
 
1.8%
업 46
 
1.7%
Other values (218) 2046
76.5%
Uppercase Letter
ValueCountFrequency (%)
J 14
38.9%
S 8
22.2%
K 7
19.4%
P 3
 
8.3%
E 3
 
8.3%
A 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
3 5
25.0%
6 4
20.0%
2 4
20.0%
8 4
20.0%
1 2
 
10.0%
4 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2676
90.6%
Common 243
 
8.2%
Latin 36
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 124
 
4.6%
사 88
 
3.3%
차 60
 
2.2%
원 56
 
2.1%
정 54
 
2.0%
유 53
 
2.0%
비 53
 
2.0%
공 48
 
1.8%
소 48
 
1.8%
업 46
 
1.7%
Other values (218) 2046
76.5%
Common
ValueCountFrequency (%)
) 97
39.9%
( 97
39.9%
23
 
9.5%
3 5
 
2.1%
6 4
 
1.6%
2 4
 
1.6%
8 4
 
1.6%
& 3
 
1.2%
_ 2
 
0.8%
1 2
 
0.8%
Other values (2) 2
 
0.8%
Latin
ValueCountFrequency (%)
J 14
38.9%
S 8
22.2%
K 7
19.4%
P 3
 
8.3%
E 3
 
8.3%
A 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2676
90.6%
ASCII 279
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 124
 
4.6%
사 88
 
3.3%
차 60
 
2.2%
원 56
 
2.1%
정 54
 
2.0%
유 53
 
2.0%
비 53
 
2.0%
공 48
 
1.8%
소 48
 
1.8%
업 46
 
1.7%
Other values (218) 2046
76.5%
ASCII
ValueCountFrequency (%)
) 97
34.8%
( 97
34.8%
23
 
8.2%
J 14
 
5.0%
S 8
 
2.9%
K 7
 
2.5%
3 5
 
1.8%
6 4
 
1.4%
2 4
 
1.4%
8 4
 
1.4%
Other values (8) 16
 
5.7%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct146
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0200002 × 1017
Minimum3.0200002 × 1017
Maximum3.0200004 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T02:12:02.754226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0200002 × 1017
5-th percentile3.0200002 × 1017
Q13.0200002 × 1017
median3.0200002 × 1017
Q33.0200002 × 1017
95-th percentile3.0200002 × 1017
Maximum3.0200004 × 1017
Range2.10014 × 1010
Interquartile range (IQR)2900288

Descriptive statistics

Standard deviation3.5126436 × 109
Coefficient of variation (CV)1.1631269 × 10-8
Kurtosis26.597551
Mean3.0200002 × 1017
Median Absolute Deviation (MAD)1100224
Skewness5.2720166
Sum7.4015444 × 1018
Variance1.2338665 × 1019
MonotonicityNot monotonic
2024-05-11T02:12:03.214954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302000022198800047 14
 
3.6%
302000022197400107 12
 
3.1%
302000022197500001 11
 
2.8%
302000022201000001 9
 
2.3%
302000022199400079 8
 
2.0%
302000022200300415 8
 
2.0%
302000022198000103 8
 
2.0%
302000022200200375 8
 
2.0%
302000022201200001 7
 
1.8%
302000022200100345 7
 
1.8%
Other values (136) 299
76.5%
ValueCountFrequency (%)
302000021200000001 2
 
0.5%
302000021200000002 2
 
0.5%
302000021200000003 5
1.3%
302000021200000005 5
1.3%
302000021200000011 5
1.3%
302000021200000012 5
1.3%
302000021200400001 5
1.3%
302000021200600002 3
0.8%
302000021200900001 5
1.3%
302000021201500003 1
 
0.3%
ValueCountFrequency (%)
302000042201400003 1
0.3%
302000042201400002 1
0.3%
302000042201400001 1
0.3%
302000042201200004 1
0.3%
302000042201200003 1
0.3%
302000042201200002 1
0.3%
302000042200800003 1
0.3%
302000042200800001 1
0.3%
302000042200500003 1
0.3%
302000042200500001 1
0.3%

업종코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
22
305 
21
62 
42
 
12
23
 
7
25
 
5

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22
2nd row22
3rd row22
4th row22
5th row23

Common Values

ValueCountFrequency (%)
22 305
78.0%
21 62
 
15.9%
42 12
 
3.1%
23 7
 
1.8%
25 5
 
1.3%

Length

2024-05-11T02:12:03.616375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:03.952167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 305
78.0%
21 62
 
15.9%
42 12
 
3.1%
23 7
 
1.8%
25 5
 
1.3%

업종명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐수배출업소관리
188 
<NA>
179 
대기배출업소관리
 
14
소음진동관리
 
5
기타수질오염원관리
 
5

Length

Max length9
Median length8
Mean length6.1560102
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 188
48.1%
<NA> 179
45.8%
대기배출업소관리 14
 
3.6%
소음진동관리 5
 
1.3%
기타수질오염원관리 5
 
1.3%

Length

2024-05-11T02:12:04.362975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:04.705426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 188
48.1%
na 179
45.8%
대기배출업소관리 14
 
3.6%
소음진동관리 5
 
1.3%
기타수질오염원관리 5
 
1.3%

지도점검일자
Real number (ℝ)

Distinct120
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20130564
Minimum20100202
Maximum20171026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T02:12:05.095845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100202
5-th percentile20100470
Q120110701
median20130813
Q320150421
95-th percentile20170421
Maximum20171026
Range70824
Interquartile range (IQR)39720

Descriptive statistics

Standard deviation23152.731
Coefficient of variation (CV)0.0011501283
Kurtosis-1.1485017
Mean20130564
Median Absolute Deviation (MAD)19982
Skewness0.32952115
Sum7.8710505 × 109
Variance5.3604895 × 108
MonotonicityNot monotonic
2024-05-11T02:12:05.600981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170223 14
 
3.6%
20110701 8
 
2.0%
20111222 7
 
1.8%
20110901 7
 
1.8%
20100910 6
 
1.5%
20120614 6
 
1.5%
20120712 6
 
1.5%
20121002 6
 
1.5%
20121031 6
 
1.5%
20110428 6
 
1.5%
Other values (110) 319
81.6%
ValueCountFrequency (%)
20100202 4
1.0%
20100210 4
1.0%
20100319 3
0.8%
20100324 6
1.5%
20100405 1
 
0.3%
20100428 2
 
0.5%
20100512 1
 
0.3%
20100513 2
 
0.5%
20100527 2
 
0.5%
20100611 2
 
0.5%
ValueCountFrequency (%)
20171026 3
 
0.8%
20170831 4
 
1.0%
20170622 3
 
0.8%
20170620 3
 
0.8%
20170614 3
 
0.8%
20170609 2
 
0.5%
20170421 3
 
0.8%
20170420 2
 
0.5%
20170227 6
1.5%
20170223 14
3.6%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3020000
391 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 391
100.0%

Length

2024-05-11T02:12:06.126063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:06.462830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 391
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
서울특별시 용산구
391 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 용산구 391
100.0%

Length

2024-05-11T02:12:06.760030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:07.166914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 391
50.0%
용산구 391
50.0%

지도점검구분
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
정기
251 
수시
111 
<NA>
 
18
기타
 
9
합동
 
1

Length

Max length4
Median length2
Mean length2.0920716
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
정기 251
64.2%
수시 111
28.4%
<NA> 18
 
4.6%
기타 9
 
2.3%
합동 1
 
0.3%
일제 1
 
0.3%

Length

2024-05-11T02:12:07.505555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:12:07.875421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 251
64.2%
수시 111
28.4%
na 18
 
4.6%
기타 9
 
2.3%
합동 1
 
0.3%
일제 1
 
0.3%

처분대상여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing183
Missing (%)46.8%
Memory size914.0 B
False
208 
(Missing)
183 
ValueCountFrequency (%)
False 208
53.2%
(Missing) 183
46.8%
2024-05-11T02:12:08.199327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct111
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T02:12:08.824308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length36
Mean length17.677749
Min length8

Characters and Unicode

Total characters6912
Distinct characters140
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)14.3%

Sample

1st row설연휴 특별점검
2nd row배출시설 및 방지시설 적정운영여부 등
3rd row배출시설 및 방지시설 적정운영여부 등
4th row폐수적정위탁처리여부 등 수질법 위반사항
5th row배출시설 및 방지시설 적정운영여부
ValueCountFrequency (%)
및 208
 
13.3%
방지시설 192
 
12.3%
배출시설 162
 
10.4%
등 99
 
6.3%
적정운영여부 94
 
6.0%
여부 91
 
5.8%
폐수배출시설 64
 
4.1%
적정운영 60
 
3.8%
정상가동여부 32
 
2.0%
점검 23
 
1.5%
Other values (143) 538
34.4%
2024-05-11T02:12:09.849738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1175
17.0%
설 484
 
7.0%
시 482
 
7.0%
부 319
 
4.6%
여 317
 
4.6%
정 288
 
4.2%
출 247
 
3.6%
배 245
 
3.5%
적 245
 
3.5%
지 217
 
3.1%
Other values (130) 2893
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5696
82.4%
Space Separator 1175
 
17.0%
Decimal Number 10
 
0.1%
Dash Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 484
 
8.5%
시 482
 
8.5%
부 319
 
5.6%
여 317
 
5.6%
정 288
 
5.1%
출 247
 
4.3%
배 245
 
4.3%
적 245
 
4.3%
지 217
 
3.8%
및 213
 
3.7%
Other values (118) 2639
46.3%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
9 1
 
10.0%
4 1
 
10.0%
6 1
 
10.0%
7 1
 
10.0%
3 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5696
82.4%
Common 1216
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 484
 
8.5%
시 482
 
8.5%
부 319
 
5.6%
여 317
 
5.6%
정 288
 
5.1%
출 247
 
4.3%
배 245
 
4.3%
적 245
 
4.3%
지 217
 
3.8%
및 213
 
3.7%
Other values (118) 2639
46.3%
Common
ValueCountFrequency (%)
1175
96.6%
- 8
 
0.7%
) 8
 
0.7%
( 8
 
0.7%
, 7
 
0.6%
1 3
 
0.2%
2 2
 
0.2%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5696
82.4%
ASCII 1216
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1175
96.6%
- 8
 
0.7%
) 8
 
0.7%
( 8
 
0.7%
, 7
 
0.6%
1 3
 
0.2%
2 2
 
0.2%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
설 484
 
8.5%
시 482
 
8.5%
부 319
 
5.6%
여 317
 
5.6%
정 288
 
5.1%
출 247
 
4.3%
배 245
 
4.3%
적 245
 
4.3%
지 217
 
3.8%
및 213
 
3.7%
Other values (118) 2639
46.3%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing391
Missing (%)100.0%
Memory size3.6 KiB

소재지도로명주소
Text

MISSING 

Distinct111
Distinct (%)57.8%
Missing199
Missing (%)50.9%
Memory size3.2 KiB
2024-05-11T02:12:10.492336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length37
Mean length26.661458
Min length22

Characters and Unicode

Total characters5119
Distinct characters144
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

Unique73 ?
Unique (%)38.0%

Sample

1st row서울특별시 용산구 이촌로 318 (이촌동)
2nd row서울특별시 용산구 청파로 327 (청파동1가)
3rd row서울특별시 용산구 원효로 86 (원효로4가)
4th row서울특별시 용산구 청파로 327 (청파동1가)
5th row서울특별시 용산구 장문로 23 (이태원동)
ValueCountFrequency (%)
서울특별시 192
19.2%
용산구 192
19.2%
한남동 29
 
2.9%
청파로 25
 
2.5%
이태원동 25
 
2.5%
23 21
 
2.1%
원효로1가 19
 
1.9%
장문로 17
 
1.7%
원효로 15
 
1.5%
이촌로 15
 
1.5%
Other values (183) 452
45.1%
2024-05-11T02:12:11.565544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
824
 
16.1%
로 246
 
4.8%
서 217
 
4.2%
용 212
 
4.1%
산 211
 
4.1%
울 194
 
3.8%
( 193
 
3.8%
별 193
 
3.8%
구 193
 
3.8%
) 193
 
3.8%
Other values (134) 2443
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3157
61.7%
Space Separator 824
 
16.1%
Decimal Number 688
 
13.4%
Open Punctuation 193
 
3.8%
Close Punctuation 193
 
3.8%
Other Punctuation 36
 
0.7%
Dash Punctuation 17
 
0.3%
Uppercase Letter 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 246
 
7.8%
서 217
 
6.9%
용 212
 
6.7%
산 211
 
6.7%
울 194
 
6.1%
별 193
 
6.1%
구 193
 
6.1%
특 192
 
6.1%
시 192
 
6.1%
동 150
 
4.8%
Other values (114) 1157
36.6%
Decimal Number
ValueCountFrequency (%)
1 133
19.3%
3 131
19.0%
2 119
17.3%
6 51
 
7.4%
4 50
 
7.3%
0 46
 
6.7%
8 46
 
6.7%
7 42
 
6.1%
5 39
 
5.7%
9 31
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
L 3
27.3%
K 2
18.2%
T 2
18.2%
C 1
 
9.1%
Space Separator
ValueCountFrequency (%)
824
100.0%
Open Punctuation
ValueCountFrequency (%)
( 193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 193
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3157
61.7%
Common 1951
38.1%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 246
 
7.8%
서 217
 
6.9%
용 212
 
6.7%
산 211
 
6.7%
울 194
 
6.1%
별 193
 
6.1%
구 193
 
6.1%
특 192
 
6.1%
시 192
 
6.1%
동 150
 
4.8%
Other values (114) 1157
36.6%
Common
ValueCountFrequency (%)
824
42.2%
( 193
 
9.9%
) 193
 
9.9%
1 133
 
6.8%
3 131
 
6.7%
2 119
 
6.1%
6 51
 
2.6%
4 50
 
2.6%
0 46
 
2.4%
8 46
 
2.4%
Other values (5) 165
 
8.5%
Latin
ValueCountFrequency (%)
S 3
27.3%
L 3
27.3%
K 2
18.2%
T 2
18.2%
C 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3157
61.7%
ASCII 1962
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
824
42.0%
( 193
 
9.8%
) 193
 
9.8%
1 133
 
6.8%
3 131
 
6.7%
2 119
 
6.1%
6 51
 
2.6%
4 50
 
2.5%
0 46
 
2.3%
8 46
 
2.3%
Other values (10) 176
 
9.0%
Hangul
ValueCountFrequency (%)
로 246
 
7.8%
서 217
 
6.9%
용 212
 
6.7%
산 211
 
6.7%
울 194
 
6.1%
별 193
 
6.1%
구 193
 
6.1%
특 192
 
6.1%
시 192
 
6.1%
동 150
 
4.8%
Other values (114) 1157
36.6%

소재지주소
Text

MISSING 

Distinct114
Distinct (%)31.3%
Missing27
Missing (%)6.9%
Memory size3.2 KiB
2024-05-11T02:12:12.156623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35.5
Mean length23.942308
Min length19

Characters and Unicode

Total characters8715
Distinct characters81
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)11.3%

Sample

1st row서울특별시 용산구 서계동 260-1번지
2nd row서울특별시 용산구 한남동 747-7번지
3rd row서울특별시 용산구 한남동 657-58번지
4th row서울특별시 용산구 원효로1가 54-6번지
5th row서울특별시 용산구 원효로1가 54-6번지
ValueCountFrequency (%)
서울특별시 364
23.8%
용산구 364
23.8%
한남동 63
 
4.1%
원효로1가 58
 
3.8%
서계동 37
 
2.4%
이태원동 34
 
2.2%
한강로3가 28
 
1.8%
260-1번지 18
 
1.2%
이촌동 17
 
1.1%
후암동 16
 
1.0%
Other values (148) 532
34.7%
2024-05-11T02:12:13.220285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1528
17.5%
서 404
 
4.6%
1 380
 
4.4%
용 379
 
4.3%
산 379
 
4.3%
지 371
 
4.3%
특 364
 
4.2%
별 364
 
4.2%
시 364
 
4.2%
구 364
 
4.2%
Other values (71) 3818
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5071
58.2%
Decimal Number 1736
 
19.9%
Space Separator 1528
 
17.5%
Dash Punctuation 336
 
3.9%
Other Punctuation 28
 
0.3%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 404
 
8.0%
용 379
 
7.5%
산 379
 
7.5%
지 371
 
7.3%
특 364
 
7.2%
별 364
 
7.2%
시 364
 
7.2%
구 364
 
7.2%
울 364
 
7.2%
번 364
 
7.2%
Other values (56) 1354
26.7%
Decimal Number
ValueCountFrequency (%)
1 380
21.9%
2 311
17.9%
5 182
10.5%
3 167
9.6%
6 163
9.4%
4 145
 
8.4%
0 144
 
8.3%
7 144
 
8.3%
8 56
 
3.2%
9 44
 
2.5%
Space Separator
ValueCountFrequency (%)
1528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 336
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5071
58.2%
Common 3644
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 404
 
8.0%
용 379
 
7.5%
산 379
 
7.5%
지 371
 
7.3%
특 364
 
7.2%
별 364
 
7.2%
시 364
 
7.2%
구 364
 
7.2%
울 364
 
7.2%
번 364
 
7.2%
Other values (56) 1354
26.7%
Common
ValueCountFrequency (%)
1528
41.9%
1 380
 
10.4%
- 336
 
9.2%
2 311
 
8.5%
5 182
 
5.0%
3 167
 
4.6%
6 163
 
4.5%
4 145
 
4.0%
0 144
 
4.0%
7 144
 
4.0%
Other values (5) 144
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5071
58.2%
ASCII 3644
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1528
41.9%
1 380
 
10.4%
- 336
 
9.2%
2 311
 
8.5%
5 182
 
5.0%
3 167
 
4.6%
6 163
 
4.5%
4 145
 
4.0%
0 144
 
4.0%
7 144
 
4.0%
Other values (5) 144
 
4.0%
Hangul
ValueCountFrequency (%)
서 404
 
8.0%
용 379
 
7.5%
산 379
 
7.5%
지 371
 
7.3%
특 364
 
7.2%
별 364
 
7.2%
시 364
 
7.2%
구 364
 
7.2%
울 364
 
7.2%
번 364
 
7.2%
Other values (56) 1354
26.7%

Interactions

2024-05-11T02:11:58.562759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:11:57.738638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:11:59.083972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:11:58.100436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:12:13.736006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분
인허가번호1.0001.0001.0000.4940.060
업종코드1.0001.0001.0000.4920.331
업종명1.0001.0001.0000.7040.191
지도점검일자0.4940.4920.7041.0000.384
지도점검구분0.0600.3310.1910.3841.000
2024-05-11T02:12:14.075013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드지도점검구분업종명
업종코드1.0000.1291.000
지도점검구분0.1291.0000.180
업종명1.0000.1801.000
2024-05-11T02:12:14.388152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호지도점검일자업종코드업종명지도점검구분
인허가번호1.000-0.1120.9970.9950.025
지도점검일자-0.1121.0000.3270.3730.251
업종코드0.9970.3271.0001.0000.129
업종명0.9950.3731.0001.0000.180
지도점검구분0.0250.2510.1290.1801.000

Missing values

2024-05-11T02:11:59.787704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:12:00.561871image/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.
2024-05-11T02:12:00.964327image/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
0서진인쇄사30200002219940007922폐수배출업소관리201002023020000서울특별시 용산구수시N설연휴 특별점검<NA><NA>서울특별시 용산구 서계동 260-1번지
1서울미라마유한회사30200002219750000122폐수배출업소관리201003193020000서울특별시 용산구정기N배출시설 및 방지시설 적정운영여부 등<NA><NA>서울특별시 용산구 한남동 747-7번지
2순천향대학병원30200002219740010722폐수배출업소관리201003193020000서울특별시 용산구정기N배출시설 및 방지시설 적정운영여부 등<NA><NA>서울특별시 용산구 한남동 657-58번지
3임창피앤디30200002219860002822폐수배출업소관리201003243020000서울특별시 용산구정기N폐수적정위탁처리여부 등 수질법 위반사항<NA><NA>서울특별시 용산구 원효로1가 54-6번지
4임창피앤디30200002320000001223소음진동관리201003243020000서울특별시 용산구정기N배출시설 및 방지시설 적정운영여부<NA><NA>서울특별시 용산구 원효로1가 54-6번지
5명보전산품(주)30200002220020036722폐수배출업소관리201003243020000서울특별시 용산구정기N폐수적정위탁처리 등 적정운영여부<NA><NA>서울특별시 용산구 문배동 40-5번지
6금강인쇄30200002220060043122폐수배출업소관리201003243020000서울특별시 용산구정기N폐수적정위탁처리 등 적정운영여부<NA><NA>서울특별시 용산구 원효로1가 120-26번지 2층
7선주인쇄30200002220080043622폐수배출업소관리201003243020000서울특별시 용산구정기N폐수적정위탁처리 등 적정운영여부<NA><NA>서울특별시 용산구 원효로1가 119-13번지
8명성문화사30200002220080043722폐수배출업소관리201003243020000서울특별시 용산구정기N폐수적정위탁처리 등 적정운영여부<NA><NA>서울특별시 용산구 문배동 40-5번지
9용산셀프세차장30200002220090044022폐수배출업소관리201004053020000서울특별시 용산구수시N개선명령이행사항 확인<NA><NA>서울특별시 용산구 보광동 123번지 ,129-5
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
381강원자동차정비사업소30200002120000001221<NA>201706223020000서울특별시 용산구정기<NA>배출시설 및 방지시설 정상가동여부<NA>서울특별시 용산구 원효로 165 (원효로2가)서울특별시 용산구 원효로2가 90번지
382국방부정비지원센타30200002120040000121<NA>201706223020000서울특별시 용산구정기<NA>배출시설 및 방지시설 적정운영여부<NA>서울특별시 용산구 이태원로 22 (용산동3가)서울특별시 용산구 용산동3가 11-2번지
383제일윤활유급유소30200002219750014822폐수배출업소관리201706093020000서울특별시 용산구정기N폐수배출업소 적정운영 관리 여부<NA>서울특별시 용산구 청파로 355 (서계동)서울특별시 용산구 서계동 136번지
384한국석유공업(주)한석주유소30200002219990028622폐수배출업소관리201708313020000서울특별시 용산구정기N수질 수생태계 보전에 관한 법률 준수 여부<NA>서울특별시 용산구 이촌로 166 (이촌동)서울특별시 용산구 이촌동 302-79번지 한석주유소
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