Overview

Dataset statistics

Number of variables13
Number of observations747
Missing cells1710
Missing cells (%)17.6%
Duplicate rows2
Duplicate rows (%)0.3%
Total size in memory79.6 KiB
Average record size in memory109.2 B

Variable types

Text4
Numeric2
Categorical5
Boolean1
Unsupported1

Dataset

Description업체(시설)명,인허가번호,업종코드,업종명,지도점검일자,점검기관,점검기관명,지도점검구분,처분대상여부,점검사항,점검결과,소재지도로명주소,소재지주소
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-11048/S/1/datasetView.do

Alerts

점검기관 has constant value ""Constant
점검기관명 has constant value ""Constant
Dataset has 2 (0.3%) duplicate rowsDuplicates
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 2 other fieldsHigh correlation
처분대상여부 is highly overall correlated with 인허가번호High correlation
지도점검구분 is highly imbalanced (77.7%)Imbalance
처분대상여부 is highly imbalanced (88.9%)Imbalance
처분대상여부 has 271 (36.3%) missing valuesMissing
점검사항 has 95 (12.7%) missing valuesMissing
점검결과 has 747 (100.0%) missing valuesMissing
소재지도로명주소 has 490 (65.6%) missing valuesMissing
소재지주소 has 107 (14.3%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 03:36:00.859595
Analysis finished2024-05-11 03:36:06.707326
Duration5.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct355
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-05-11T03:36:07.118186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length8.91834
Min length3

Characters and Unicode

Total characters6662
Distinct characters367
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

Unique178 ?
Unique (%)23.8%

Sample

1st row내곡주유소
2nd row지쓰리(G3)카케어
3rd row현대공업사
4th row(주)농협유통하나로주유소
5th row위드모터스
ValueCountFrequency (%)
코오롱글로벌(주 10
 
1.1%
현대자동차 9
 
1.0%
주)천산 8
 
0.9%
주)농협유통하나로주유소 8
 
0.9%
엘지전자(주 7
 
0.8%
주)우림자동차 7
 
0.8%
지에스넥스테이션 7
 
0.8%
선우상사q엔느 7
 
0.8%
주)동원석유주유소 6
 
0.7%
대정자동차공업사 6
 
0.7%
Other values (393) 795
91.4%
2024-05-11T03:36:08.282299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 417
 
6.3%
( 269
 
4.0%
) 267
 
4.0%
스 217
 
3.3%
동 181
 
2.7%
차 180
 
2.7%
자 179
 
2.7%
유 166
 
2.5%
서 159
 
2.4%
소 133
 
2.0%
Other values (357) 4494
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5812
87.2%
Open Punctuation 270
 
4.1%
Close Punctuation 268
 
4.0%
Space Separator 123
 
1.8%
Uppercase Letter 76
 
1.1%
Decimal Number 59
 
0.9%
Dash Punctuation 37
 
0.6%
Lowercase Letter 9
 
0.1%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 417
 
7.2%
스 217
 
3.7%
동 181
 
3.1%
차 180
 
3.1%
자 179
 
3.1%
유 166
 
2.9%
서 159
 
2.7%
소 133
 
2.3%
사 119
 
2.0%
대 116
 
2.0%
Other values (312) 3945
67.9%
Uppercase Letter
ValueCountFrequency (%)
K 9
11.8%
S 8
10.5%
T 8
10.5%
Q 7
9.2%
M 7
9.2%
D 6
7.9%
G 6
7.9%
E 6
7.9%
I 5
6.6%
A 3
 
3.9%
Other values (8) 11
14.5%
Decimal Number
ValueCountFrequency (%)
2 14
23.7%
7 9
15.3%
1 9
15.3%
3 6
10.2%
6 6
10.2%
5 4
 
6.8%
4 4
 
6.8%
8 4
 
6.8%
0 2
 
3.4%
9 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
22.2%
m 1
11.1%
s 1
11.1%
r 1
11.1%
t 1
11.1%
e 1
11.1%
n 1
11.1%
i 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 1
 
12.5%
？ 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 269
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 267
99.6%
] 1
 
0.4%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5812
87.2%
Common 765
 
11.5%
Latin 85
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 417
 
7.2%
스 217
 
3.7%
동 181
 
3.1%
차 180
 
3.1%
자 179
 
3.1%
유 166
 
2.9%
서 159
 
2.7%
소 133
 
2.3%
사 119
 
2.0%
대 116
 
2.0%
Other values (312) 3945
67.9%
Latin
ValueCountFrequency (%)
K 9
10.6%
S 8
 
9.4%
T 8
 
9.4%
Q 7
 
8.2%
M 7
 
8.2%
D 6
 
7.1%
G 6
 
7.1%
E 6
 
7.1%
I 5
 
5.9%
A 3
 
3.5%
Other values (16) 20
23.5%
Common
ValueCountFrequency (%)
( 269
35.2%
) 267
34.9%
123
16.1%
- 37
 
4.8%
2 14
 
1.8%
7 9
 
1.2%
1 9
 
1.2%
, 6
 
0.8%
3 6
 
0.8%
6 6
 
0.8%
Other values (9) 19
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5812
87.2%
ASCII 849
 
12.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 417
 
7.2%
스 217
 
3.7%
동 181
 
3.1%
차 180
 
3.1%
자 179
 
3.1%
유 166
 
2.9%
서 159
 
2.7%
소 133
 
2.3%
사 119
 
2.0%
대 116
 
2.0%
Other values (312) 3945
67.9%
ASCII
ValueCountFrequency (%)
( 269
31.7%
) 267
31.4%
123
14.5%
- 37
 
4.4%
2 14
 
1.6%
7 9
 
1.1%
1 9
 
1.1%
K 9
 
1.1%
S 8
 
0.9%
T 8
 
0.9%
Other values (34) 96
 
11.3%
None
ValueCountFrequency (%)
？ 1
100.0%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct340
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2100002 × 1017
Minimum3.2100002 × 1017
Maximum3.2100003 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-11T03:36:08.862679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2100002 × 1017
5-th percentile3.2100002 × 1017
Q13.2100002 × 1017
median3.2100002 × 1017
Q33.2100002 × 1017
95-th percentile3.2100002 × 1017
Maximum3.2100003 × 1017
Range1.30017 × 1010
Interquartile range (IQR)9.990999 × 108

Descriptive statistics

Standard deviation7.7026021 × 108
Coefficient of variation (CV)2.3995644 × 10-9
Kurtosis168.8361
Mean3.2100002 × 1017
Median Absolute Deviation (MAD)599872
Skewness10.50763
Sum-2.0656543 × 1016
Variance5.9330079 × 1017
MonotonicityNot monotonic
2024-05-11T03:36:09.714900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
321000022200600023 8
 
1.1%
321000022200800018 8
 
1.1%
321000022200000238 7
 
0.9%
321000022200900001 7
 
0.9%
321000022200000011 7
 
0.9%
321000022200700003 7
 
0.9%
321000022200000088 6
 
0.8%
321000022199100006 6
 
0.8%
321000022200600014 6
 
0.8%
321000022200000043 6
 
0.8%
Other values (330) 679
90.9%
ValueCountFrequency (%)
321000021199200003 2
0.3%
321000021199800002 1
 
0.1%
321000021199800009 1
 
0.1%
321000021199800010 1
 
0.1%
321000021199900001 1
 
0.1%
321000021199900003 3
0.4%
321000021200200001 2
0.3%
321000021200200005 1
 
0.1%
321000021200300003 1
 
0.1%
321000021200400006 1
 
0.1%
ValueCountFrequency (%)
321000034200900456 1
 
0.1%
321000034200900089 1
 
0.1%
321000022201600003 1
 
0.1%
321000022201600002 1
 
0.1%
321000022201600001 1
 
0.1%
321000022201500724 2
0.3%
321000022201500004 1
 
0.1%
321000022201500003 2
0.3%
321000022201500002 3
0.4%
321000022201500001 2
0.3%

업종코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
22
552 
21
193 
34
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
22 552
73.9%
21 193
 
25.8%
34 2
 
0.3%

Length

2024-05-11T03:36:10.290917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:36:10.642640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 552
73.9%
21 193
 
25.8%
34 2
 
0.3%

업종명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
폐수배출업소관리
430 
<NA>
281 
대기배출업소관리
 
36

Length

Max length8
Median length8
Mean length6.4953146
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 430
57.6%
<NA> 281
37.6%
대기배출업소관리 36
 
4.8%

Length

2024-05-11T03:36:11.005442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:36:11.434324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 430
57.6%
na 281
37.6%
대기배출업소관리 36
 
4.8%

지도점검일자
Real number (ℝ)

Distinct274
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20132298
Minimum20100209
Maximum20170713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-05-11T03:36:12.022447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100209
5-th percentile20100416
Q120110525
median20130808
Q320160315
95-th percentile20161031
Maximum20170713
Range70504
Interquartile range (IQR)49790

Descriptive statistics

Standard deviation22983.009
Coefficient of variation (CV)0.0011415989
Kurtosis-1.3851606
Mean20132298
Median Absolute Deviation (MAD)20296
Skewness0.071397799
Sum1.5038826 × 1010
Variance5.2821869 × 108
MonotonicityDecreasing
2024-05-11T03:36:12.507020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161024 22
 
2.9%
20161026 17
 
2.3%
20161025 15
 
2.0%
20161027 15
 
2.0%
20161019 14
 
1.9%
20161031 13
 
1.7%
20100927 11
 
1.5%
20100930 10
 
1.3%
20110324 9
 
1.2%
20161021 8
 
1.1%
Other values (264) 613
82.1%
ValueCountFrequency (%)
20100209 3
0.4%
20100223 3
0.4%
20100309 3
0.4%
20100311 3
0.4%
20100316 1
 
0.1%
20100324 3
0.4%
20100406 5
0.7%
20100409 5
0.7%
20100413 2
 
0.3%
20100414 6
0.8%
ValueCountFrequency (%)
20170713 4
0.5%
20170711 2
 
0.3%
20170705 4
0.5%
20170704 2
 
0.3%
20170630 5
0.7%
20170605 1
 
0.1%
20170519 1
 
0.1%
20170424 5
0.7%
20170421 3
0.4%
20170420 1
 
0.1%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
3210000
747 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 747
100.0%

Length

2024-05-11T03:36:13.053515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:36:13.395296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 747
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
서울특별시 서초구
747 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 서초구 747
100.0%

Length

2024-05-11T03:36:13.782266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:36:14.201930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 747
50.0%
서초구 747
50.0%

지도점검구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
정기
684 
기타
 
32
합동
 
13
<NA>
 
8
수시
 
8

Length

Max length4
Median length2
Mean length2.021419
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 684
91.6%
기타 32
 
4.3%
합동 13
 
1.7%
<NA> 8
 
1.1%
수시 8
 
1.1%
일제 2
 
0.3%

Length

2024-05-11T03:36:14.746645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:36:15.159755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 684
91.6%
기타 32
 
4.3%
합동 13
 
1.7%
na 8
 
1.1%
수시 8
 
1.1%
일제 2
 
0.3%

처분대상여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing271
Missing (%)36.3%
Memory size1.6 KiB
False
469 
True
 
7
(Missing)
271 
ValueCountFrequency (%)
False 469
62.8%
True 7
 
0.9%
(Missing) 271
36.3%
2024-05-11T03:36:15.538863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

MISSING 

Distinct117
Distinct (%)17.9%
Missing95
Missing (%)12.7%
Memory size6.0 KiB
2024-05-11T03:36:16.212088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length16.02454
Min length4

Characters and Unicode

Total characters10448
Distinct characters101
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)7.8%

Sample

1st row폐수배출시설 및 방지시설 적정운영 여부
2nd row폐수배출시설 및 방지시설 적정운영 여부
3rd row폐수배출시설 및 방지시설 적정운영 여부
4th row폐수배출시설 및 방지시설 적정운영 여부
5th row폐수배출시설 및 방지시설 적정운영 여부
ValueCountFrequency (%)
배출시설 399
16.3%
여부 344
14.1%
방지시설 330
13.5%
및 318
13.0%
적정가동 150
 
6.1%
적정가동여부 100
 
4.1%
적정운영 92
 
3.8%
적정관리 76
 
3.1%
대기배출시설 67
 
2.7%
폐수배출시설 48
 
2.0%
Other values (97) 523
21.4%
2024-05-11T03:36:17.293026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1795
17.2%
시 935
 
8.9%
설 918
 
8.8%
배 574
 
5.5%
출 574
 
5.5%
부 566
 
5.4%
여 565
 
5.4%
정 553
 
5.3%
적 473
 
4.5%
방 378
 
3.6%
Other values (91) 3117
29.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8613
82.4%
Space Separator 1795
 
17.2%
Other Punctuation 26
 
0.2%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 935
 
10.9%
설 918
 
10.7%
배 574
 
6.7%
출 574
 
6.7%
부 566
 
6.6%
여 565
 
6.6%
정 553
 
6.4%
적 473
 
5.5%
방 378
 
4.4%
지 368
 
4.3%
Other values (86) 2709
31.5%
Other Punctuation
ValueCountFrequency (%)
, 23
88.5%
? 3
 
11.5%
Space Separator
ValueCountFrequency (%)
1795
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8613
82.4%
Common 1835
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 935
 
10.9%
설 918
 
10.7%
배 574
 
6.7%
출 574
 
6.7%
부 566
 
6.6%
여 565
 
6.6%
정 553
 
6.4%
적 473
 
5.5%
방 378
 
4.4%
지 368
 
4.3%
Other values (86) 2709
31.5%
Common
ValueCountFrequency (%)
1795
97.8%
, 23
 
1.3%
) 7
 
0.4%
( 7
 
0.4%
? 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8613
82.4%
ASCII 1835
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1795
97.8%
, 23
 
1.3%
) 7
 
0.4%
( 7
 
0.4%
? 3
 
0.2%
Hangul
ValueCountFrequency (%)
시 935
 
10.9%
설 918
 
10.7%
배 574
 
6.7%
출 574
 
6.7%
부 566
 
6.6%
여 565
 
6.6%
정 553
 
6.4%
적 473
 
5.5%
방 378
 
4.4%
지 368
 
4.3%
Other values (86) 2709
31.5%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing747
Missing (%)100.0%
Memory size6.7 KiB

소재지도로명주소
Text

MISSING 

Distinct184
Distinct (%)71.6%
Missing490
Missing (%)65.6%
Memory size6.0 KiB
2024-05-11T03:36:18.132926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length26.77821
Min length21

Characters and Unicode

Total characters6882
Distinct characters192
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

Unique136 ?
Unique (%)52.9%

Sample

1st row서울특별시 서초구 헌릉로 210 (내곡동)
2nd row서울특별시 서초구 명달로 101 (서초동)
3rd row서울특별시 서초구 명달로 36-1 (서초동)
4th row서울특별시 서초구 남부순환로296길 4-16 (방배동)
5th row서울특별시 서초구 남부순환로342길 62-26 (양재동)
ValueCountFrequency (%)
서울특별시 257
19.1%
서초구 257
19.1%
방배동 61
 
4.5%
양재동 53
 
3.9%
서초동 52
 
3.9%
반포동 49
 
3.6%
반포대로 23
 
1.7%
신반포로 18
 
1.3%
남부순환로 16
 
1.2%
바우뫼로 16
 
1.2%
Other values (263) 545
40.5%
2024-05-11T03:36:19.345094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1159
 
16.8%
서 614
 
8.9%
초 345
 
5.0%
동 270
 
3.9%
울 267
 
3.9%
) 262
 
3.8%
( 262
 
3.8%
구 261
 
3.8%
시 261
 
3.8%
특 257
 
3.7%
Other values (182) 2924
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4257
61.9%
Space Separator 1159
 
16.8%
Decimal Number 848
 
12.3%
Close Punctuation 262
 
3.8%
Open Punctuation 262
 
3.8%
Other Punctuation 53
 
0.8%
Dash Punctuation 33
 
0.5%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 614
14.4%
초 345
 
8.1%
동 270
 
6.3%
울 267
 
6.3%
구 261
 
6.1%
시 261
 
6.1%
특 257
 
6.0%
별 257
 
6.0%
로 249
 
5.8%
포 100
 
2.3%
Other values (163) 1376
32.3%
Decimal Number
ValueCountFrequency (%)
2 164
19.3%
1 154
18.2%
6 92
10.8%
3 85
10.0%
4 84
9.9%
7 78
9.2%
5 57
 
6.7%
9 47
 
5.5%
8 44
 
5.2%
0 43
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
B 2
25.0%
G 1
 
12.5%
L 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 262
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4257
61.9%
Common 2617
38.0%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 614
14.4%
초 345
 
8.1%
동 270
 
6.3%
울 267
 
6.3%
구 261
 
6.1%
시 261
 
6.1%
특 257
 
6.0%
별 257
 
6.0%
로 249
 
5.8%
포 100
 
2.3%
Other values (163) 1376
32.3%
Common
ValueCountFrequency (%)
1159
44.3%
) 262
 
10.0%
( 262
 
10.0%
2 164
 
6.3%
1 154
 
5.9%
6 92
 
3.5%
3 85
 
3.2%
4 84
 
3.2%
7 78
 
3.0%
5 57
 
2.2%
Other values (5) 220
 
8.4%
Latin
ValueCountFrequency (%)
C 4
50.0%
B 2
25.0%
G 1
 
12.5%
L 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4257
61.9%
ASCII 2625
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1159
44.2%
) 262
 
10.0%
( 262
 
10.0%
2 164
 
6.2%
1 154
 
5.9%
6 92
 
3.5%
3 85
 
3.2%
4 84
 
3.2%
7 78
 
3.0%
5 57
 
2.2%
Other values (9) 228
 
8.7%
Hangul
ValueCountFrequency (%)
서 614
14.4%
초 345
 
8.1%
동 270
 
6.3%
울 267
 
6.3%
구 261
 
6.1%
시 261
 
6.1%
특 257
 
6.0%
별 257
 
6.0%
로 249
 
5.8%
포 100
 
2.3%
Other values (163) 1376
32.3%

소재지주소
Text

MISSING 

Distinct220
Distinct (%)34.4%
Missing107
Missing (%)14.3%
Memory size6.0 KiB
2024-05-11T03:36:20.068212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length36
Mean length22.778125
Min length14

Characters and Unicode

Total characters14578
Distinct characters71
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

Unique62 ?
Unique (%)9.7%

Sample

1st row서울특별시 서초구 내곡동 142-3번지
2nd row서울특별시 서초구 서초동 1516-1번지
3rd row서울특별시 서초구 양재동 229번지
4th row서울특별시 서초구 서초동 1487-137번지
5th row서울특별시 서초구 방배동 584번지
ValueCountFrequency (%)
서울특별시 640
24.1%
서초구 640
24.1%
양재동 189
 
7.1%
방배동 172
 
6.5%
서초동 151
 
5.7%
반포동 66
 
2.5%
내곡동 23
 
0.9%
우면동 18
 
0.7%
584번지 14
 
0.5%
산 12
 
0.5%
Other values (233) 729
27.5%
2024-05-11T03:36:21.469372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2674
18.3%
서 1439
 
9.9%
초 791
 
5.4%
1 666
 
4.6%
지 657
 
4.5%
울 648
 
4.4%
동 642
 
4.4%
구 640
 
4.4%
시 640
 
4.4%
별 640
 
4.4%
Other values (61) 5141
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8538
58.6%
Decimal Number 2781
 
19.1%
Space Separator 2674
 
18.3%
Dash Punctuation 519
 
3.6%
Other Punctuation 34
 
0.2%
Close Punctuation 11
 
0.1%
Open Punctuation 11
 
0.1%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1439
16.9%
초 791
9.3%
지 657
7.7%
울 648
7.6%
동 642
7.5%
구 640
7.5%
시 640
7.5%
별 640
7.5%
특 640
7.5%
번 638
7.5%
Other values (44) 1163
13.6%
Decimal Number
ValueCountFrequency (%)
1 666
23.9%
3 341
12.3%
2 319
11.5%
5 234
 
8.4%
4 233
 
8.4%
9 227
 
8.2%
6 210
 
7.6%
0 195
 
7.0%
7 187
 
6.7%
8 169
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
C 8
80.0%
B 2
 
20.0%
Space Separator
ValueCountFrequency (%)
2674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 519
100.0%
Other Punctuation
ValueCountFrequency (%)
, 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8538
58.6%
Common 6030
41.4%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1439
16.9%
초 791
9.3%
지 657
7.7%
울 648
7.6%
동 642
7.5%
구 640
7.5%
시 640
7.5%
별 640
7.5%
특 640
7.5%
번 638
7.5%
Other values (44) 1163
13.6%
Common
ValueCountFrequency (%)
2674
44.3%
1 666
 
11.0%
- 519
 
8.6%
3 341
 
5.7%
2 319
 
5.3%
5 234
 
3.9%
4 233
 
3.9%
9 227
 
3.8%
6 210
 
3.5%
0 195
 
3.2%
Other values (5) 412
 
6.8%
Latin
ValueCountFrequency (%)
C 8
80.0%
B 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8538
58.6%
ASCII 6040
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2674
44.3%
1 666
 
11.0%
- 519
 
8.6%
3 341
 
5.6%
2 319
 
5.3%
5 234
 
3.9%
4 233
 
3.9%
9 227
 
3.8%
6 210
 
3.5%
0 195
 
3.2%
Other values (7) 422
 
7.0%
Hangul
ValueCountFrequency (%)
서 1439
16.9%
초 791
9.3%
지 657
7.7%
울 648
7.6%
동 642
7.5%
구 640
7.5%
시 640
7.5%
별 640
7.5%
특 640
7.5%
번 638
7.5%
Other values (44) 1163
13.6%

Interactions

2024-05-11T03:36:04.002652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:36:03.270646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:36:04.424645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:36:03.631077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T03:36:21.954414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부
인허가번호1.0001.000NaN0.1880.000NaN
업종코드1.0001.0001.0000.4280.0950.000
업종명NaN1.0001.0000.5730.0000.000
지도점검일자0.1880.4280.5731.0000.2850.540
지도점검구분0.0000.0950.0000.2851.0000.000
처분대상여부NaN0.0000.0000.5400.0001.000
2024-05-11T03:36:22.383748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지도점검구분업종명업종코드처분대상여부
지도점검구분1.0000.0000.0710.000
업종명0.0001.0000.9850.000
업종코드0.0710.9851.0000.000
처분대상여부0.0000.0000.0001.000
2024-05-11T03:36:22.704982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호지도점검일자업종코드업종명지도점검구분처분대상여부
인허가번호1.000-0.0450.9991.0000.0001.000
지도점검일자-0.0451.0000.3000.4230.1790.405
업종코드0.9990.3001.0000.9850.0710.000
업종명1.0000.4230.9851.0000.0000.000
지도점검구분0.0000.1790.0710.0001.0000.000
처분대상여부1.0000.4050.0000.0000.0001.000

Missing values

2024-05-11T03:36:05.046615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T03:36:05.804040image/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.
2024-05-11T03:36:06.336747image/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
0내곡주유소32100002220000001122폐수배출업소관리201707133210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 헌릉로 210 (내곡동)서울특별시 서초구 내곡동 142-3번지
1지쓰리(G3)카케어32100002220150072422폐수배출업소관리201707133210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 명달로 101 (서초동)<NA>
2현대공업사32100002220050002222폐수배출업소관리201707133210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA><NA>서울특별시 서초구 서초동 1516-1번지
3(주)농협유통하나로주유소32100002220070000322폐수배출업소관리201707133210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA><NA>서울특별시 서초구 양재동 229번지
4위드모터스32100002220150000322폐수배출업소관리201707113210000서울특별시 서초구정기Y폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 명달로 36-1 (서초동)<NA>
5발전카세차장32100002220000014522폐수배출업소관리201707113210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA><NA>서울특별시 서초구 서초동 1487-137번지
6(주)서하앤컴퍼니32100002220080001822폐수배출업소관리201707053210000서울특별시 서초구정기Y폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 남부순환로296길 4-16 (방배동)서울특별시 서초구 방배동 584번지
7양재자동자운전학원32100002220000043722폐수배출업소관리201707053210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 남부순환로342길 62-26 (양재동)서울특별시 서초구 양재동 174번지
8카웍스32100002220020058522폐수배출업소관리201707053210000서울특별시 서초구정기Y폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 남부순환로 2224 (방배동)서울특별시 서초구 방배동 623-5번지
9(주)골든듀32100002220150000122폐수배출업소관리201707053210000서울특별시 서초구정기N폐수배출시설 및 방지시설 적정운영 여부<NA>서울특별시 서초구 남부순환로 2365 (서초동)<NA>
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
737(주)강남서초에너지 금정주유소32100002220090000122폐수배출업소관리201003113210000서울특별시 서초구정기N배출시설 및 방지시설 정상가동여부<NA><NA>서울특별시 서초구 양재동 106-5번지
738에스케이네트웍스(주)사평로주유소32100002220000017122폐수배출업소관리201003093210000서울특별시 서초구정기N배출시설및 방지시설 정상가동 여부<NA><NA>서울특별시 서초구 서초동 1302번지
739효성토요타(주)32100002220100000122폐수배출업소관리201003093210000서울특별시 서초구정기N배출시설및 방지시설 정상가동 여부<NA><NA>서울특별시 서초구 반포동 63-7번지
740연일주유소32100002220000017022폐수배출업소관리201003093210000서울특별시 서초구정기N배출시설및 방지시설 정상가동 여부<NA><NA>서울특별시 서초구 서초동 1426-13번지
741두꺼비카랜드32100002220000010622폐수배출업소관리201002233210000서울특별시 서초구정기N배출시설 및 방지시설 적정가동여부<NA><NA>서울특별시 서초구 양재동 350-10번지
742동양자동차32100002220080001622폐수배출업소관리201002233210000서울특별시 서초구정기N배출시설 및 방지시설 적정가동여부<NA><NA>서울특별시 서초구 양재동 262-5번지
743르노삼성자동차양재개포점32100002220000010922폐수배출업소관리201002233210000서울특별시 서초구정기N배출시설 및 방지시설 적정가동여부<NA><NA>서울특별시 서초구 양재동 263-3번지
744광혁건설(주)32100002220080001322폐수배출업소관리201002093210000서울특별시 서초구정기N배출시설 및 방지시설 적정 가동여부<NA><NA>서울특별시 서초구 우면동 산 67-8번지
745신분당선 2공구32100002220080001022폐수배출업소관리201002093210000서울특별시 서초구정기N배출시설 및 방지시설 적정 가동여부<NA><NA>서울특별시 서초구 양재동 232번지 대
746신분당선전철공사-3번환기구 상일토건(주)32100002220070001622폐수배출업소관리201002093210000서울특별시 서초구정기N배출시설 및 방지시설 적정 가동여부<NA><NA>서울특별시 서초구 양재동 126-1번지

Duplicate rows

Most frequently occurring

업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항소재지도로명주소소재지주소# duplicates
0스페이스카세차장32100002220080000822폐수배출업소관리201105183210000서울특별시 서초구정기N배출시설 및 방지시설 적정가동 여부<NA>서울특별시 서초구 서초동 1537-3번지2
1태봉주유소32100002220000020622폐수배출업소관리201205033210000서울특별시 서초구정기N배출시설 적정가동여부<NA>서울특별시 서초구 우면동 13-4,5,6번지2