Overview

Dataset statistics

Number of variables13
Number of observations431
Missing cells641
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.0 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
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-10509/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
지도점검구분 is highly imbalanced (69.8%)Imbalance
처분대상여부 has 54 (12.5%) missing valuesMissing
점검결과 has 431 (100.0%) missing valuesMissing
소재지도로명주소 has 118 (27.4%) missing valuesMissing
소재지주소 has 36 (8.4%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-14 02:50:17.180471
Analysis finished2024-04-14 02:50:22.773493
Duration5.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct117
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-04-14T11:50:23.482592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.8259861
Min length2

Characters and Unicode

Total characters3373
Distinct characters209
Distinct categories6 ?
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 (%)5.1%

Sample

1st row(주)은평자동차공업사
2nd row경부교통(주)
3rd row상록교통(주)
4th row(재)마리아수녀회 도티기념병원
5th row서울특별시 서북병원
ValueCountFrequency (%)
주)선진운수 24
 
5.3%
은평환경플랜트 17
 
3.7%
승진기업(주 12
 
2.6%
성원이앤에스(주)은평주유소 11
 
2.4%
상경운수(주 10
 
2.2%
현재오토카 7
 
1.5%
청구성심병원 7
 
1.5%
신성윤활유급유소 7
 
1.5%
서울석유(주)박석고개주유소 7
 
1.5%
동고택시(주 7
 
1.5%
Other values (114) 345
76.0%
2024-04-14T11:50:24.827286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 295
 
8.7%
( 193
 
5.7%
) 193
 
5.7%
유 150
 
4.4%
소 123
 
3.6%
스 86
 
2.5%
은 79
 
2.3%
평 77
 
2.3%
성 63
 
1.9%
차 61
 
1.8%
Other values (199) 2053
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2939
87.1%
Open Punctuation 193
 
5.7%
Close Punctuation 193
 
5.7%
Space Separator 23
 
0.7%
Lowercase Letter 14
 
0.4%
Uppercase Letter 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 295
 
10.0%
유 150
 
5.1%
소 123
 
4.2%
스 86
 
2.9%
은 79
 
2.7%
평 77
 
2.6%
성 63
 
2.1%
차 61
 
2.1%
원 55
 
1.9%
서 52
 
1.8%
Other values (184) 1898
64.6%
Lowercase Letter
ValueCountFrequency (%)
s 5
35.7%
k 2
 
14.3%
e 1
 
7.1%
h 1
 
7.1%
c 1
 
7.1%
a 1
 
7.1%
w 1
 
7.1%
o 1
 
7.1%
l 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
S 5
45.5%
K 5
45.5%
G 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 193
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2939
87.1%
Common 409
 
12.1%
Latin 25
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 295
 
10.0%
유 150
 
5.1%
소 123
 
4.2%
스 86
 
2.9%
은 79
 
2.7%
평 77
 
2.6%
성 63
 
2.1%
차 61
 
2.1%
원 55
 
1.9%
서 52
 
1.8%
Other values (184) 1898
64.6%
Latin
ValueCountFrequency (%)
s 5
20.0%
S 5
20.0%
K 5
20.0%
k 2
 
8.0%
e 1
 
4.0%
h 1
 
4.0%
c 1
 
4.0%
a 1
 
4.0%
w 1
 
4.0%
o 1
 
4.0%
Other values (2) 2
 
8.0%
Common
ValueCountFrequency (%)
( 193
47.2%
) 193
47.2%
23
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2939
87.1%
ASCII 434
 
12.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 295
 
10.0%
유 150
 
5.1%
소 123
 
4.2%
스 86
 
2.9%
은 79
 
2.7%
평 77
 
2.6%
성 63
 
2.1%
차 61
 
2.1%
원 55
 
1.9%
서 52
 
1.8%
Other values (184) 1898
64.6%
ASCII
ValueCountFrequency (%)
( 193
44.5%
) 193
44.5%
23
 
5.3%
s 5
 
1.2%
S 5
 
1.2%
K 5
 
1.2%
k 2
 
0.5%
e 1
 
0.2%
h 1
 
0.2%
c 1
 
0.2%
Other values (5) 5
 
1.2%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1100002 × 1017
Minimum3.1100002 × 1017
Maximum3.1100002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-14T11:50:25.270598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1100002 × 1017
5-th percentile3.1100002 × 1017
Q13.1100002 × 1017
median3.1100002 × 1017
Q33.1100002 × 1017
95-th percentile3.1100002 × 1017
Maximum3.1100002 × 1017
Range1.0017 × 109
Interquartile range (IQR)900032

Descriptive statistics

Standard deviation3.6699325 × 108
Coefficient of variation (CV)1.1800425 × 10-9
Kurtosis1.4678428
Mean3.1100002 × 1017
Median Absolute Deviation (MAD)499840
Skewness-1.8603857
Sum4.913801 × 1018
Variance1.3468405 × 1017
MonotonicityNot monotonic
2024-04-14T11:50:25.732131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
311000022200000027 17
 
3.9%
311000022200900004 11
 
2.6%
311000021200700001 10
 
2.3%
311000022200000031 9
 
2.1%
311000022201100004 8
 
1.9%
311000022200000036 8
 
1.9%
311000021200000010 7
 
1.6%
311000022200000009 7
 
1.6%
311000022200000012 7
 
1.6%
311000022200900002 7
 
1.6%
Other values (105) 340
78.9%
ValueCountFrequency (%)
311000021200000006 3
 
0.7%
311000021200000007 3
 
0.7%
311000021200000009 7
1.6%
311000021200000010 7
1.6%
311000021200400001 7
1.6%
311000021200400012 3
 
0.7%
311000021200700001 10
2.3%
311000021201500001 2
 
0.5%
311000021201500002 2
 
0.5%
311000021201500003 2
 
0.5%
ValueCountFrequency (%)
311000022201700002 1
 
0.2%
311000022201700001 1
 
0.2%
311000022201600001 1
 
0.2%
311000022201500006 2
0.5%
311000022201500005 2
0.5%
311000022201500004 2
0.5%
311000022201500003 2
0.5%
311000022201500002 2
0.5%
311000022201500001 2
0.5%
311000022201400005 3
0.7%

업종코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
22
362 
21
69 

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 (%)
22 362
84.0%
21 69
 
16.0%

Length

2024-04-14T11:50:26.132269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T11:50:26.451471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 362
84.0%
21 69
 
16.0%

업종명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
폐수배출업소관리
341 
<NA>
53 
대기배출업소관리
37 

Length

Max length8
Median length8
Mean length7.5081206
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
폐수배출업소관리 341
79.1%
<NA> 53
 
12.3%
대기배출업소관리 37
 
8.6%

Length

2024-04-14T11:50:26.840133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T11:50:27.344748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 341
79.1%
na 53
 
12.3%
대기배출업소관리 37
 
8.6%

지도점검일자
Real number (ℝ)

Distinct126
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20138937
Minimum20100127
Maximum20171130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-14T11:50:27.714051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100127
5-th percentile20100526
Q120120430
median20140813
Q320160615
95-th percentile20171063
Maximum20171130
Range71003
Interquartile range (IQR)40185

Descriptive statistics

Standard deviation23277.305
Coefficient of variation (CV)0.0011558358
Kurtosis-1.2229329
Mean20138937
Median Absolute Deviation (MAD)20093
Skewness-0.24546032
Sum8.6798819 × 109
Variance5.4183294 × 108
MonotonicityDecreasing
2024-04-14T11:50:28.173558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171109 9
 
2.1%
20110825 8
 
1.9%
20140729 7
 
1.6%
20130813 7
 
1.6%
20150820 7
 
1.6%
20141028 7
 
1.6%
20100929 7
 
1.6%
20150513 7
 
1.6%
20100625 7
 
1.6%
20150731 7
 
1.6%
Other values (116) 358
83.1%
ValueCountFrequency (%)
20100127 4
0.9%
20100225 2
 
0.5%
20100317 3
0.7%
20100430 5
1.2%
20100520 4
0.9%
20100526 6
1.4%
20100625 7
1.6%
20100630 4
0.9%
20100715 2
 
0.5%
20100824 5
1.2%
ValueCountFrequency (%)
20171130 3
 
0.7%
20171113 1
 
0.2%
20171110 4
0.9%
20171109 9
2.1%
20171108 3
 
0.7%
20171102 1
 
0.2%
20171101 1
 
0.2%
20171025 5
1.2%
20170920 2
 
0.5%
20170713 5
1.2%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
3110000
431 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 431
100.0%

Length

2024-04-14T11:50:28.583791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T11:50:28.888565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 431
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
서울특별시 은평구
431 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 은평구 431
100.0%

Length

2024-04-14T11:50:29.205923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T11:50:29.510414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 431
50.0%
은평구 431
50.0%

지도점검구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
정기
378 
수시
 
36
합동
 
10
<NA>
 
5
기타
 
2

Length

Max length4
Median length2
Mean length2.0232019
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 378
87.7%
수시 36
 
8.4%
합동 10
 
2.3%
<NA> 5
 
1.2%
기타 2
 
0.5%

Length

2024-04-14T11:50:29.872053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T11:50:30.227881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 378
87.7%
수시 36
 
8.4%
합동 10
 
2.3%
na 5
 
1.2%
기타 2
 
0.5%

처분대상여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing54
Missing (%)12.5%
Memory size990.0 B
False
377 
(Missing)
54 
ValueCountFrequency (%)
False 377
87.5%
(Missing) 54
 
12.5%
2024-04-14T11:50:30.539796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct84
Distinct (%)19.6%
Missing2
Missing (%)0.5%
Memory size3.5 KiB
2024-04-14T11:50:31.195762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length25
Mean length17.634033
Min length2

Characters and Unicode

Total characters7565
Distinct characters78
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)8.9%

Sample

1st row대기배출시설(도장시설) 적정 운영여부
2nd row대기 배출시설 및 방지시설 적정 운영 여부
3rd row대기배출시설 및 방지시설 적정 운영 여부
4th row대기배출시설 정적 운영 여부
5th row대기배출시설 정적 운영 여부
ValueCountFrequency (%)
방지시설 275
14.7%
여부 273
14.6%
및 266
14.2%
적정 205
10.9%
폐수배출시설 194
10.3%
가동 140
7.5%
배출시설 59
 
3.1%
운영 52
 
2.8%
대기배출시설 36
 
1.9%
적정운영 33
 
1.8%
Other values (74) 343
18.3%
2024-04-14T11:50:32.352611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1447
19.1%
시 624
 
8.2%
설 622
 
8.2%
출 381
 
5.0%
배 380
 
5.0%
정 331
 
4.4%
부 331
 
4.4%
여 331
 
4.4%
지 330
 
4.4%
적 326
 
4.3%
Other values (68) 2462
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6114
80.8%
Space Separator 1447
 
19.1%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 624
 
10.2%
설 622
 
10.2%
출 381
 
6.2%
배 380
 
6.2%
정 331
 
5.4%
부 331
 
5.4%
여 331
 
5.4%
지 330
 
5.4%
적 326
 
5.3%
수 322
 
5.3%
Other values (63) 2136
34.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
？ 1
50.0%
Space Separator
ValueCountFrequency (%)
1447
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6114
80.8%
Common 1451
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 624
 
10.2%
설 622
 
10.2%
출 381
 
6.2%
배 380
 
6.2%
정 331
 
5.4%
부 331
 
5.4%
여 331
 
5.4%
지 330
 
5.4%
적 326
 
5.3%
수 322
 
5.3%
Other values (63) 2136
34.9%
Common
ValueCountFrequency (%)
1447
99.7%
, 1
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
？ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6114
80.8%
ASCII 1450
 
19.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1447
99.8%
, 1
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
Hangul
ValueCountFrequency (%)
시 624
 
10.2%
설 622
 
10.2%
출 381
 
6.2%
배 380
 
6.2%
정 331
 
5.4%
부 331
 
5.4%
여 331
 
5.4%
지 330
 
5.4%
적 326
 
5.3%
수 322
 
5.3%
Other values (63) 2136
34.9%
None
ValueCountFrequency (%)
？ 1
100.0%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing431
Missing (%)100.0%
Memory size3.9 KiB

소재지도로명주소
Text

MISSING 

Distinct102
Distinct (%)32.6%
Missing118
Missing (%)27.4%
Memory size3.5 KiB
2024-04-14T11:50:33.284480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length36
Mean length25.194888
Min length22

Characters and Unicode

Total characters7886
Distinct characters103
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

Unique21 ?
Unique (%)6.7%

Sample

1st row서울특별시 은평구 서오릉로 250 (갈현동)
2nd row서울특별시 은평구 증산서길 20-6 (증산동)
3rd row서울특별시 은평구 백련산로14길 20-11 (응암동)
4th row서울특별시 은평구 갈현로7길 49 (역촌동, 시립서북병원)
5th row서울특별시 은평구 불광로 20 (대조동, NC백화점)
ValueCountFrequency (%)
서울특별시 313
19.6%
은평구 313
19.6%
통일로 63
 
4.0%
진관동 37
 
2.3%
녹번동 37
 
2.3%
역촌동 37
 
2.3%
서오릉로 34
 
2.1%
연서로 33
 
2.1%
수색로 31
 
1.9%
응암동 30
 
1.9%
Other values (127) 666
41.8%
2024-04-14T11:50:34.719190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1423
18.0%
서 432
 
5.5%
은 333
 
4.2%
평 333
 
4.2%
구 332
 
4.2%
시 315
 
4.0%
울 314
 
4.0%
) 313
 
4.0%
동 313
 
4.0%
( 313
 
4.0%
Other values (93) 3465
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4711
59.7%
Space Separator 1423
 
18.0%
Decimal Number 1013
 
12.8%
Close Punctuation 313
 
4.0%
Open Punctuation 313
 
4.0%
Other Punctuation 53
 
0.7%
Dash Punctuation 50
 
0.6%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 432
 
9.2%
은 333
 
7.1%
평 333
 
7.1%
구 332
 
7.0%
시 315
 
6.7%
울 314
 
6.7%
동 313
 
6.6%
별 313
 
6.6%
특 313
 
6.6%
로 295
 
6.3%
Other values (73) 1418
30.1%
Decimal Number
ValueCountFrequency (%)
1 207
20.4%
2 176
17.4%
3 106
10.5%
0 88
8.7%
5 84
8.3%
9 80
 
7.9%
4 74
 
7.3%
6 68
 
6.7%
8 67
 
6.6%
7 63
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 2
20.0%
C 2
20.0%
P 2
20.0%
T 2
20.0%
A 2
20.0%
Space Separator
ValueCountFrequency (%)
1423
100.0%
Close Punctuation
ValueCountFrequency (%)
) 313
100.0%
Open Punctuation
ValueCountFrequency (%)
( 313
100.0%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4711
59.7%
Common 3165
40.1%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 432
 
9.2%
은 333
 
7.1%
평 333
 
7.1%
구 332
 
7.0%
시 315
 
6.7%
울 314
 
6.7%
동 313
 
6.6%
별 313
 
6.6%
특 313
 
6.6%
로 295
 
6.3%
Other values (73) 1418
30.1%
Common
ValueCountFrequency (%)
1423
45.0%
) 313
 
9.9%
( 313
 
9.9%
1 207
 
6.5%
2 176
 
5.6%
3 106
 
3.3%
0 88
 
2.8%
5 84
 
2.7%
9 80
 
2.5%
4 74
 
2.3%
Other values (5) 301
 
9.5%
Latin
ValueCountFrequency (%)
N 2
20.0%
C 2
20.0%
P 2
20.0%
T 2
20.0%
A 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4711
59.7%
ASCII 3175
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1423
44.8%
) 313
 
9.9%
( 313
 
9.9%
1 207
 
6.5%
2 176
 
5.5%
3 106
 
3.3%
0 88
 
2.8%
5 84
 
2.6%
9 80
 
2.5%
4 74
 
2.3%
Other values (10) 311
 
9.8%
Hangul
ValueCountFrequency (%)
서 432
 
9.2%
은 333
 
7.1%
평 333
 
7.1%
구 332
 
7.0%
시 315
 
6.7%
울 314
 
6.7%
동 313
 
6.6%
별 313
 
6.6%
특 313
 
6.6%
로 295
 
6.3%
Other values (73) 1418
30.1%

소재지주소
Text

MISSING 

Distinct86
Distinct (%)21.8%
Missing36
Missing (%)8.4%
Memory size3.5 KiB
2024-04-14T11:50:35.646698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length22.197468
Min length14

Characters and Unicode

Total characters8768
Distinct characters62
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

Unique11 ?
Unique (%)2.8%

Sample

1st row서울특별시 은평구 갈현동 326-14번지
2nd row서울특별시 은평구 증산동 221-3번지
3rd row서울특별시 은평구 신사동 142-1번지
4th row서울특별시 은평구 응암동 42-5번지
5th row서울특별시 은평구 응암동 산 6-46번지
ValueCountFrequency (%)
서울특별시 395
24.4%
은평구 395
24.4%
진관동 54
 
3.3%
갈현동 54
 
3.3%
역촌동 46
 
2.8%
신사동 46
 
2.8%
녹번동 41
 
2.5%
증산동 39
 
2.4%
응암동 30
 
1.9%
수색동 29
 
1.8%
Other values (95) 491
30.3%
2024-04-14T11:50:37.030338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1624
18.5%
번 417
 
4.8%
구 411
 
4.7%
은 402
 
4.6%
평 402
 
4.6%
시 400
 
4.6%
동 400
 
4.6%
별 395
 
4.5%
특 395
 
4.5%
울 395
 
4.5%
Other values (52) 3527
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5248
59.9%
Space Separator 1624
 
18.5%
Decimal Number 1530
 
17.4%
Dash Punctuation 361
 
4.1%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 417
 
7.9%
구 411
 
7.8%
은 402
 
7.7%
평 402
 
7.7%
시 400
 
7.6%
동 400
 
7.6%
별 395
 
7.5%
특 395
 
7.5%
울 395
 
7.5%
서 395
 
7.5%
Other values (39) 1236
23.6%
Decimal Number
ValueCountFrequency (%)
2 312
20.4%
1 277
18.1%
4 180
11.8%
3 164
10.7%
5 154
10.1%
6 120
 
7.8%
7 110
 
7.2%
8 100
 
6.5%
9 69
 
4.5%
0 44
 
2.9%
Space Separator
ValueCountFrequency (%)
1624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 361
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5248
59.9%
Common 3520
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 417
 
7.9%
구 411
 
7.8%
은 402
 
7.7%
평 402
 
7.7%
시 400
 
7.6%
동 400
 
7.6%
별 395
 
7.5%
특 395
 
7.5%
울 395
 
7.5%
서 395
 
7.5%
Other values (39) 1236
23.6%
Common
ValueCountFrequency (%)
1624
46.1%
- 361
 
10.3%
2 312
 
8.9%
1 277
 
7.9%
4 180
 
5.1%
3 164
 
4.7%
5 154
 
4.4%
6 120
 
3.4%
7 110
 
3.1%
8 100
 
2.8%
Other values (3) 118
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5248
59.9%
ASCII 3520
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1624
46.1%
- 361
 
10.3%
2 312
 
8.9%
1 277
 
7.9%
4 180
 
5.1%
3 164
 
4.7%
5 154
 
4.4%
6 120
 
3.4%
7 110
 
3.1%
8 100
 
2.8%
Other values (3) 118
 
3.4%
Hangul
ValueCountFrequency (%)
번 417
 
7.9%
구 411
 
7.8%
은 402
 
7.7%
평 402
 
7.7%
시 400
 
7.6%
동 400
 
7.6%
별 395
 
7.5%
특 395
 
7.5%
울 395
 
7.5%
서 395
 
7.5%
Other values (39) 1236
23.6%

Interactions

2024-04-14T11:50:20.952590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T11:50:20.417908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T11:50:21.219377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T11:50:20.682585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T11:50:37.295620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분점검사항소재지주소
인허가번호1.0001.0000.9990.3830.0590.9920.921
업종코드1.0001.0001.0000.3390.1290.9980.914
업종명0.9991.0001.0000.4250.0700.9960.842
지도점검일자0.3830.3390.4251.0000.5620.9480.000
지도점검구분0.0590.1290.0700.5621.0000.7080.000
점검사항0.9920.9980.9960.9480.7081.0000.890
소재지주소0.9210.9140.8420.0000.0000.8901.000
2024-04-14T11:50:37.574571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드지도점검구분업종명
업종코드1.0000.0850.985
지도점검구분0.0851.0000.046
업종명0.9850.0461.000
2024-04-14T11:50:37.827051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호지도점검일자업종코드업종명지도점검구분
인허가번호1.0000.0470.9910.9850.085
지도점검일자0.0471.0000.2560.3180.268
업종코드0.9910.2561.0000.9850.085
업종명0.9850.3180.9851.0000.046
지도점검구분0.0850.2680.0850.0461.000

Missing values

2024-04-14T11:50:21.614501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T11:50:22.178798image/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.
2024-04-14T11:50:22.577696image/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
0(주)은평자동차공업사31100002120000001021<NA>201711303110000서울특별시 은평구정기<NA>대기배출시설(도장시설) 적정 운영여부<NA>서울특별시 은평구 서오릉로 250 (갈현동)서울특별시 은평구 갈현동 326-14번지
1경부교통(주)31100002120000000721<NA>201711303110000서울특별시 은평구정기<NA>대기 배출시설 및 방지시설 적정 운영 여부<NA>서울특별시 은평구 증산서길 20-6 (증산동)서울특별시 은평구 증산동 221-3번지
2상록교통(주)31100002120000000921<NA>201711303110000서울특별시 은평구정기<NA>대기배출시설 및 방지시설 적정 운영 여부<NA><NA>서울특별시 은평구 신사동 142-1번지
3(재)마리아수녀회 도티기념병원31100002120150000721<NA>201711133110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 백련산로14길 20-11 (응암동)서울특별시 은평구 응암동 42-5번지
4서울특별시 서북병원31100002120150000621<NA>201711103110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 갈현로7길 49 (역촌동, 시립서북병원)<NA>
5(주)팜스개발31100002120150000521<NA>201711103110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 불광로 20 (대조동, NC백화점)<NA>
6삼부건강랜드 보석사우나31100002120150001121<NA>201711103110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 증산로21길 11 (신사동, 신흥상가삼부아파트)<NA>
7서울시립은평청소년수련관31100002120150000421<NA>201711103110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 백련산로4길 16 (응암동, 은평청소년수련관)서울특별시 은평구 응암동 산 6-46번지
8서울특별시 은평병원31100002120150000821<NA>201711093110000서울특별시 은평구정기<NA>대기배출시설 정적 운영 여부<NA>서울특별시 은평구 백련산로 90 (응암동, 은평병원)<NA>
9한국여성정책연구원31100002120150000221<NA>201711093110000서울특별시 은평구정기<NA>배출시설 및 방지시설 적정 운영 여부<NA>서울특별시 은평구 진흥로 225 (불광동, 한국여성정책연구원)서울특별시 은평구 불광동 1-363번지
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
421우남교통(주)31100002220000003522폐수배출업소관리201004303110000서울특별시 은평구정기N폐수배출시설전반사항<NA><NA>서울특별시 은평구 신사동 8-5번지
422(주)에스지주유소31100002220070000222폐수배출업소관리201003173110000서울특별시 은평구정기N폐수배출시설 전반사항<NA>서울특별시 은평구 증산로 371 (신사동)서울특별시 은평구 신사동 338-4번지
423(주)안국상사역촌동주유소31100002220020000722폐수배출업소관리201003173110000서울특별시 은평구정기N폐수배출시설 전반사항<NA>서울특별시 은평구 연서로 68 (역촌동)서울특별시 은평구 역촌동 22-12번지
424현재오토카31100002220000005522폐수배출업소관리201003173110000서울특별시 은평구정기N폐수배출업소 전반사항<NA>서울특별시 은평구 연서로 42 (역촌동)서울특별시 은평구 역촌동 35-27번지
425지에스칼텍스(주)직영신사제일점31100002220000018822폐수배출업소관리201002253110000서울특별시 은평구정기N폐수배출시설 전반사항<NA>서울특별시 은평구 증산로 423 (신사동,및 50호)서울특별시 은평구 신사동 35-11번지 및 50호
426현대화카월드31100002220000001822폐수배출업소관리201002253110000서울특별시 은평구정기N폐수배출시설 전반사항<NA><NA>서울특별시 은평구 역촌동 68-56번지
427식품의약품안전본부31100002220000000422폐수배출업소관리201001273110000서울특별시 은평구정기N배출업소 전반사항<NA><NA>서울특별시 은평구 녹번동 5번지
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