Overview

Dataset statistics

Number of variables13
Number of observations719
Missing cells834
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.7 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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-10355/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
업종명 is highly imbalanced (52.0%)Imbalance
처분대상여부 is highly imbalanced (91.0%)Imbalance
처분대상여부 has 15 (2.1%) missing valuesMissing
점검결과 has 719 (100.0%) missing valuesMissing
소재지도로명주소 has 99 (13.8%) missing valuesMissing
점검결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 14:13:57.840016
Analysis finished2024-04-29 14:14:01.083262
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체(시설)명
Text

Distinct148
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-29T23:14:01.279055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length8.7913769
Min length3

Characters and Unicode

Total characters6321
Distinct characters236
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

Unique33 ?
Unique (%)4.6%

Sample

1st row한화역사(주)청량리점
2nd row클라쎄오토(주)
3rd row(주)대흥모터스
4th row동대문구청
5th row롯데쇼핑(주)청량리점
ValueCountFrequency (%)
주)삼천리이앤이 148
 
18.8%
주)동대문환경개발공사 27
 
3.4%
클라쎄오토(주 16
 
2.0%
장인자동차공업사 12
 
1.5%
주)대흥모터스 11
 
1.4%
서울시립대학교 11
 
1.4%
경희대학교 10
 
1.3%
세원택시(주 9
 
1.1%
흥명자동차공업사(주 9
 
1.1%
진도카공업사 8
 
1.0%
Other values (159) 525
66.8%
2024-04-29T23:14:01.725666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 430
 
6.8%
( 364
 
5.8%
) 364
 
5.8%
이 325
 
5.1%
삼 184
 
2.9%
리 181
 
2.9%
동 168
 
2.7%
사 162
 
2.6%
차 157
 
2.5%
천 157
 
2.5%
Other values (226) 3829
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5436
86.0%
Open Punctuation 364
 
5.8%
Close Punctuation 364
 
5.8%
Space Separator 67
 
1.1%
Uppercase Letter 55
 
0.9%
Decimal Number 31
 
0.5%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 430
 
7.9%
이 325
 
6.0%
삼 184
 
3.4%
리 181
 
3.3%
동 168
 
3.1%
사 162
 
3.0%
차 157
 
2.9%
천 157
 
2.9%
앤 148
 
2.7%
대 140
 
2.6%
Other values (209) 3384
62.3%
Uppercase Letter
ValueCountFrequency (%)
I 16
29.1%
T 8
14.5%
F 8
14.5%
K 6
 
10.9%
S 6
 
10.9%
G 3
 
5.5%
L 3
 
5.5%
P 3
 
5.5%
A 2
 
3.6%
Decimal Number
ValueCountFrequency (%)
2 14
45.2%
4 12
38.7%
1 5
 
16.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
k 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 364
100.0%
Close Punctuation
ValueCountFrequency (%)
) 364
100.0%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5436
86.0%
Common 826
 
13.1%
Latin 59
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 430
 
7.9%
이 325
 
6.0%
삼 184
 
3.4%
리 181
 
3.3%
동 168
 
3.1%
사 162
 
3.0%
차 157
 
2.9%
천 157
 
2.9%
앤 148
 
2.7%
대 140
 
2.6%
Other values (209) 3384
62.3%
Latin
ValueCountFrequency (%)
I 16
27.1%
T 8
13.6%
F 8
13.6%
K 6
 
10.2%
S 6
 
10.2%
G 3
 
5.1%
L 3
 
5.1%
P 3
 
5.1%
s 2
 
3.4%
k 2
 
3.4%
Common
ValueCountFrequency (%)
( 364
44.1%
) 364
44.1%
67
 
8.1%
2 14
 
1.7%
4 12
 
1.5%
1 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5436
86.0%
ASCII 885
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 430
 
7.9%
이 325
 
6.0%
삼 184
 
3.4%
리 181
 
3.3%
동 168
 
3.1%
사 162
 
3.0%
차 157
 
2.9%
천 157
 
2.9%
앤 148
 
2.7%
대 140
 
2.6%
Other values (209) 3384
62.3%
ASCII
ValueCountFrequency (%)
( 364
41.1%
) 364
41.1%
67
 
7.6%
I 16
 
1.8%
2 14
 
1.6%
4 12
 
1.4%
T 8
 
0.9%
F 8
 
0.9%
K 6
 
0.7%
S 6
 
0.7%
Other values (7) 20
 
2.3%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct156
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0500002 × 1017
Minimum3.0500002 × 1017
Maximum3.0500006 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-04-29T23:14:01.869389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0500002 × 1017
5-th percentile3.0500002 × 1017
Q13.0500002 × 1017
median3.0500002 × 1017
Q33.0500002 × 1017
95-th percentile3.0500002 × 1017
Maximum3.0500006 × 1017
Range4.00024 × 1010
Interquartile range (IQR)9.9909997 × 108

Descriptive statistics

Standard deviation4.1692036 × 109
Coefficient of variation (CV)1.3669519 × 10-8
Kurtosis81.18043
Mean3.0500002 × 1017
Median Absolute Deviation (MAD)899840
Skewness8.9974342
Sum-2.0659128 × 1018
Variance1.7382258 × 1019
MonotonicityNot monotonic
2024-04-29T23:14:02.012609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
305000021199700010 74
 
10.3%
305000022200600002 72
 
10.0%
305000022200700002 19
 
2.6%
305000022200400002 10
 
1.4%
305000022199600096 9
 
1.3%
305000022200700007 8
 
1.1%
305000022200200425 8
 
1.1%
305000022199700016 8
 
1.1%
305000022199700015 8
 
1.1%
305000022200700006 8
 
1.1%
Other values (146) 495
68.8%
ValueCountFrequency (%)
305000021199200004 7
 
1.0%
305000021199600001 7
 
1.0%
305000021199700002 5
 
0.7%
305000021199700010 74
10.3%
305000021199700011 8
 
1.1%
305000021199700014 8
 
1.1%
305000021199700015 1
 
0.1%
305000021199700175 1
 
0.1%
305000021199800018 5
 
0.7%
305000021199900019 6
 
0.8%
ValueCountFrequency (%)
305000061201600006 2
0.3%
305000061201600004 1
0.1%
305000061201000005 1
0.1%
305000061201000004 1
0.1%
305000061201000003 1
0.1%
305000061201000002 1
0.1%
305000061201000001 1
0.1%
305000025200700276 1
0.1%
305000025200700271 1
0.1%
305000025200600255 1
0.1%

업종코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
22
488 
21
214 
25
 
15
23
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
22 488
67.9%
21 214
29.8%
25 15
 
2.1%
23 2
 
0.3%

Length

2024-04-29T23:14:02.148122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T23:14:02.250806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22 488
67.9%
21 214
29.8%
25 15
 
2.1%
23 2
 
0.3%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
폐수배출업소관리
485 
대기배출업소관리
209 
기타수질오염원관리
 
15
<NA>
 
8
소음진동관리
 
2

Length

Max length9
Median length8
Mean length7.9707928
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐수배출업소관리 485
67.5%
대기배출업소관리 209
29.1%
기타수질오염원관리 15
 
2.1%
<NA> 8
 
1.1%
소음진동관리 2
 
0.3%

Length

2024-04-29T23:14:02.374014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T23:14:02.480306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐수배출업소관리 485
67.5%
대기배출업소관리 209
29.1%
기타수질오염원관리 15
 
2.1%
na 8
 
1.1%
소음진동관리 2
 
0.3%

지도점검일자
Real number (ℝ)

Distinct281
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20128269
Minimum20100112
Maximum20171129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-04-29T23:14:02.612485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100112
5-th percentile20100517
Q120110418
median20120925
Q320150352
95-th percentile20170904
Maximum20171129
Range71017
Interquartile range (IQR)39935

Descriptive statistics

Standard deviation23101.703
Coefficient of variation (CV)0.0011477243
Kurtosis-1.0065257
Mean20128269
Median Absolute Deviation (MAD)19710
Skewness0.51789941
Sum1.4472225 × 1010
Variance5.3368866 × 108
MonotonicityDecreasing
2024-04-29T23:14:02.759908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110310 12
 
1.7%
20100806 10
 
1.4%
20100910 10
 
1.4%
20100722 9
 
1.3%
20120418 8
 
1.1%
20171129 7
 
1.0%
20121121 7
 
1.0%
20110520 6
 
0.8%
20120111 6
 
0.8%
20161020 6
 
0.8%
Other values (271) 638
88.7%
ValueCountFrequency (%)
20100112 1
 
0.1%
20100209 3
0.4%
20100223 3
0.4%
20100224 2
 
0.3%
20100319 3
0.4%
20100329 6
0.8%
20100330 3
0.4%
20100415 3
0.4%
20100429 3
0.4%
20100430 2
 
0.3%
ValueCountFrequency (%)
20171129 7
1.0%
20171128 2
 
0.3%
20171127 1
 
0.1%
20171123 1
 
0.1%
20171031 3
0.4%
20171026 3
0.4%
20171025 3
0.4%
20171020 2
 
0.3%
20171016 2
 
0.3%
20171013 2
 
0.3%

점검기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
3050000
719 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 719
100.0%

Length

2024-04-29T23:14:02.893479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T23:14:03.001335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 719
100.0%

점검기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
서울특별시 동대문구
719 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 동대문구 719
100.0%

Length

2024-04-29T23:14:03.094799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T23:14:03.177769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 719
50.0%
동대문구 719
50.0%

지도점검구분
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
정기
441 
수시
220 
기타
 
32
합동
 
26

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 441
61.3%
수시 220
30.6%
기타 32
 
4.5%
합동 26
 
3.6%

Length

2024-04-29T23:14:03.274072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T23:14:03.373554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 441
61.3%
수시 220
30.6%
기타 32
 
4.5%
합동 26
 
3.6%

처분대상여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing15
Missing (%)2.1%
Memory size1.5 KiB
False
696 
True
 
8
(Missing)
 
15
ValueCountFrequency (%)
False 696
96.8%
True 8
 
1.1%
(Missing) 15
 
2.1%
2024-04-29T23:14:03.461105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점검사항
Text

Distinct207
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-29T23:14:03.654655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length16.732962
Min length4

Characters and Unicode

Total characters12031
Distinct characters154
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)21.4%

Sample

1st row대기배출시설 적정 운영 여부
2nd row배출시설 및 방지시설 적정 운영중
3rd row배출시설 및 방지시설 적정 운영중
4th row대기배출시설 적정 운영 여부
5th row대기배출시설 폐쇄여부 확인
ValueCountFrequency (%)
및 394
13.0%
배출시설 326
10.8%
방지시설 320
10.6%
여부 295
9.8%
적정 275
 
9.1%
운영 205
 
6.8%
점검 161
 
5.3%
대기배출시설 130
 
4.3%
폐수배출시설 111
 
3.7%
운영여부 76
 
2.5%
Other values (191) 731
24.2%
2024-04-29T23:14:04.052342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2307
19.2%
시 1022
 
8.5%
설 1012
 
8.4%
출 632
 
5.3%
배 628
 
5.2%
지 444
 
3.7%
정 417
 
3.5%
부 410
 
3.4%
여 408
 
3.4%
및 395
 
3.3%
Other values (144) 4356
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9638
80.1%
Space Separator 2307
 
19.2%
Other Punctuation 42
 
0.3%
Close Punctuation 16
 
0.1%
Open Punctuation 16
 
0.1%
Decimal Number 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1022
 
10.6%
설 1012
 
10.5%
출 632
 
6.6%
배 628
 
6.5%
지 444
 
4.6%
정 417
 
4.3%
부 410
 
4.3%
여 408
 
4.2%
및 395
 
4.1%
운 379
 
3.9%
Other values (134) 3891
40.4%
Decimal Number
ValueCountFrequency (%)
0 3
25.0%
1 3
25.0%
2 2
16.7%
7 2
16.7%
4 2
16.7%
Other Punctuation
ValueCountFrequency (%)
, 39
92.9%
. 3
 
7.1%
Space Separator
ValueCountFrequency (%)
2307
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9638
80.1%
Common 2393
 
19.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1022
 
10.6%
설 1012
 
10.5%
출 632
 
6.6%
배 628
 
6.5%
지 444
 
4.6%
정 417
 
4.3%
부 410
 
4.3%
여 408
 
4.2%
및 395
 
4.1%
운 379
 
3.9%
Other values (134) 3891
40.4%
Common
ValueCountFrequency (%)
2307
96.4%
, 39
 
1.6%
) 16
 
0.7%
( 16
 
0.7%
0 3
 
0.1%
1 3
 
0.1%
. 3
 
0.1%
2 2
 
0.1%
7 2
 
0.1%
4 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9637
80.1%
ASCII 2393
 
19.9%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2307
96.4%
, 39
 
1.6%
) 16
 
0.7%
( 16
 
0.7%
0 3
 
0.1%
1 3
 
0.1%
. 3
 
0.1%
2 2
 
0.1%
7 2
 
0.1%
4 2
 
0.1%
Hangul
ValueCountFrequency (%)
시 1022
 
10.6%
설 1012
 
10.5%
출 632
 
6.6%
배 628
 
6.5%
지 444
 
4.6%
정 417
 
4.3%
부 410
 
4.3%
여 408
 
4.2%
및 395
 
4.1%
운 379
 
3.9%
Other values (133) 3890
40.4%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

점검결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing719
Missing (%)100.0%
Memory size6.4 KiB

소재지도로명주소
Text

MISSING 

Distinct122
Distinct (%)19.7%
Missing99
Missing (%)13.8%
Memory size5.7 KiB
2024-04-29T23:14:04.325492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length37
Mean length25.733871
Min length23

Characters and Unicode

Total characters15955
Distinct characters123
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

Unique19 ?
Unique (%)3.1%

Sample

1st row서울특별시 동대문구 왕산로 214 (전농동, 청량리역)
2nd row서울특별시 동대문구 천호대로 361 (장안동)
3rd row서울특별시 동대문구 고산자로 568 (제기동)
4th row서울특별시 동대문구 천호대로 145 (용두동, 동대문구청)
5th row서울특별시 동대문구 왕산로 214 (전농동, 롯데백화점)
ValueCountFrequency (%)
서울특별시 620
19.7%
동대문구 620
19.7%
이문동 143
 
4.5%
장안동 139
 
4.4%
209 98
 
3.1%
한천로58길 98
 
3.1%
전농동 82
 
2.6%
용두동 69
 
2.2%
한천로 55
 
1.7%
왕산로 52
 
1.7%
Other values (164) 1174
37.3%
2024-04-29T23:14:04.748169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2530
 
15.9%
동 1258
 
7.9%
문 788
 
4.9%
대 712
 
4.5%
시 666
 
4.2%
서 651
 
4.1%
울 651
 
4.1%
구 623
 
3.9%
( 622
 
3.9%
) 622
 
3.9%
Other values (113) 6832
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10128
63.5%
Space Separator 2530
 
15.9%
Decimal Number 1962
 
12.3%
Open Punctuation 622
 
3.9%
Close Punctuation 622
 
3.9%
Other Punctuation 49
 
0.3%
Dash Punctuation 42
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1258
12.4%
문 788
 
7.8%
대 712
 
7.0%
시 666
 
6.6%
서 651
 
6.4%
울 651
 
6.4%
구 623
 
6.2%
특 620
 
6.1%
별 620
 
6.1%
로 617
 
6.1%
Other values (98) 2922
28.9%
Decimal Number
ValueCountFrequency (%)
2 333
17.0%
1 322
16.4%
5 231
11.8%
8 226
11.5%
0 206
10.5%
9 180
9.2%
3 158
8.1%
6 129
 
6.6%
4 97
 
4.9%
7 80
 
4.1%
Space Separator
ValueCountFrequency (%)
2530
100.0%
Open Punctuation
ValueCountFrequency (%)
( 622
100.0%
Close Punctuation
ValueCountFrequency (%)
) 622
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10128
63.5%
Common 5827
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1258
12.4%
문 788
 
7.8%
대 712
 
7.0%
시 666
 
6.6%
서 651
 
6.4%
울 651
 
6.4%
구 623
 
6.2%
특 620
 
6.1%
별 620
 
6.1%
로 617
 
6.1%
Other values (98) 2922
28.9%
Common
ValueCountFrequency (%)
2530
43.4%
( 622
 
10.7%
) 622
 
10.7%
2 333
 
5.7%
1 322
 
5.5%
5 231
 
4.0%
8 226
 
3.9%
0 206
 
3.5%
9 180
 
3.1%
3 158
 
2.7%
Other values (5) 397
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10128
63.5%
ASCII 5827
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2530
43.4%
( 622
 
10.7%
) 622
 
10.7%
2 333
 
5.7%
1 322
 
5.5%
5 231
 
4.0%
8 226
 
3.9%
0 206
 
3.5%
9 180
 
3.1%
3 158
 
2.7%
Other values (5) 397
 
6.8%
Hangul
ValueCountFrequency (%)
동 1258
12.4%
문 788
 
7.8%
대 712
 
7.0%
시 666
 
6.6%
서 651
 
6.4%
울 651
 
6.4%
구 623
 
6.2%
특 620
 
6.1%
별 620
 
6.1%
로 617
 
6.1%
Other values (98) 2922
28.9%

소재지주소
Text

Distinct133
Distinct (%)18.5%
Missing1
Missing (%)0.1%
Memory size5.7 KiB
2024-04-29T23:14:05.016880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length23.090529
Min length19

Characters and Unicode

Total characters16579
Distinct characters46
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

Unique23 ?
Unique (%)3.2%

Sample

1st row서울특별시 동대문구 전농동 591-53번지
2nd row서울특별시 동대문구 장안동 413-4번지
3rd row서울특별시 동대문구 제기동 136-3번지
4th row서울특별시 동대문구 용두동 39-9번지
5th row서울특별시 동대문구 전농동 591-53번지
ValueCountFrequency (%)
서울특별시 718
24.8%
동대문구 718
24.8%
이문동 195
 
6.7%
장안동 152
 
5.2%
22-2번지 148
 
5.1%
전농동 82
 
2.8%
용두동 75
 
2.6%
제기동 60
 
2.1%
답십리동 54
 
1.9%
청량리동 46
 
1.6%
Other values (135) 649
22.4%
2024-04-29T23:14:05.642963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2897
17.5%
동 1436
 
8.7%
문 913
 
5.5%
2 823
 
5.0%
번 726
 
4.4%
지 726
 
4.4%
울 718
 
4.3%
구 718
 
4.3%
서 718
 
4.3%
대 718
 
4.3%
Other values (36) 6186
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10183
61.4%
Space Separator 2897
 
17.5%
Decimal Number 2806
 
16.9%
Dash Punctuation 676
 
4.1%
Other Punctuation 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1436
14.1%
문 913
9.0%
번 726
 
7.1%
지 726
 
7.1%
울 718
 
7.1%
구 718
 
7.1%
서 718
 
7.1%
대 718
 
7.1%
시 718
 
7.1%
특 718
 
7.1%
Other values (23) 2074
20.4%
Decimal Number
ValueCountFrequency (%)
2 823
29.3%
1 391
13.9%
4 331
11.8%
6 242
 
8.6%
5 238
 
8.5%
3 227
 
8.1%
9 148
 
5.3%
8 145
 
5.2%
7 135
 
4.8%
0 126
 
4.5%
Space Separator
ValueCountFrequency (%)
2897
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 676
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10183
61.4%
Common 6396
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1436
14.1%
문 913
9.0%
번 726
 
7.1%
지 726
 
7.1%
울 718
 
7.1%
구 718
 
7.1%
서 718
 
7.1%
대 718
 
7.1%
시 718
 
7.1%
특 718
 
7.1%
Other values (23) 2074
20.4%
Common
ValueCountFrequency (%)
2897
45.3%
2 823
 
12.9%
- 676
 
10.6%
1 391
 
6.1%
4 331
 
5.2%
6 242
 
3.8%
5 238
 
3.7%
3 227
 
3.5%
9 148
 
2.3%
8 145
 
2.3%
Other values (3) 278
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10183
61.4%
ASCII 6396
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2897
45.3%
2 823
 
12.9%
- 676
 
10.6%
1 391
 
6.1%
4 331
 
5.2%
6 242
 
3.8%
5 238
 
3.7%
3 227
 
3.5%
9 148
 
2.3%
8 145
 
2.3%
Other values (3) 278
 
4.3%
Hangul
ValueCountFrequency (%)
동 1436
14.1%
문 913
9.0%
번 726
 
7.1%
지 726
 
7.1%
울 718
 
7.1%
구 718
 
7.1%
서 718
 
7.1%
대 718
 
7.1%
시 718
 
7.1%
특 718
 
7.1%
Other values (23) 2074
20.4%

Interactions

2024-04-29T23:14:00.446647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T23:14:00.158350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T23:14:00.559573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T23:14:00.342578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T23:14:05.738222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업종코드업종명지도점검일자지도점검구분처분대상여부
인허가번호1.0000.5990.5990.3360.2590.154
업종코드0.5991.0001.0000.4100.5320.132
업종명0.5991.0001.0000.4110.5360.132
지도점검일자0.3360.4100.4111.0000.6350.105
지도점검구분0.2590.5320.5360.6351.0000.256
처분대상여부0.1540.1320.1320.1050.2561.000
2024-04-29T23:14:05.838788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분대상여부지도점검구분업종명업종코드
처분대상여부1.0000.1700.0870.087
지도점검구분0.1701.0000.2330.230
업종명0.0870.2331.0001.000
업종코드0.0870.2301.0001.000
2024-04-29T23:14:05.944714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호지도점검일자업종코드업종명지도점검구분처분대상여부
인허가번호1.000-0.0580.6120.6120.2420.236
지도점검일자-0.0581.0000.1910.1910.3250.079
업종코드0.6120.1911.0001.0000.2300.087
업종명0.6120.1911.0001.0000.2330.087
지도점검구분0.2420.3250.2300.2331.0000.170
처분대상여부0.2360.0790.0870.0870.1701.000

Missing values

2024-04-29T23:14:00.704805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T23:14:00.879638image/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.
2024-04-29T23:14:01.022928image/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
0한화역사(주)청량리점30500002120150001221대기배출업소관리201711293050000서울특별시 동대문구정기N대기배출시설 적정 운영 여부<NA>서울특별시 동대문구 왕산로 214 (전농동, 청량리역)서울특별시 동대문구 전농동 591-53번지
1클라쎄오토(주)30500002220070000622폐수배출업소관리201711293050000서울특별시 동대문구정기N배출시설 및 방지시설 적정 운영중<NA>서울특별시 동대문구 천호대로 361 (장안동)서울특별시 동대문구 장안동 413-4번지
2(주)대흥모터스30500002220130000222폐수배출업소관리201711293050000서울특별시 동대문구정기N배출시설 및 방지시설 적정 운영중<NA>서울특별시 동대문구 고산자로 568 (제기동)서울특별시 동대문구 제기동 136-3번지
3동대문구청30500002120160000121대기배출업소관리201711293050000서울특별시 동대문구정기N대기배출시설 적정 운영 여부<NA>서울특별시 동대문구 천호대로 145 (용두동, 동대문구청)서울특별시 동대문구 용두동 39-9번지
4롯데쇼핑(주)청량리점30500002120150000921대기배출업소관리201711293050000서울특별시 동대문구정기N대기배출시설 폐쇄여부 확인<NA>서울특별시 동대문구 왕산로 214 (전농동, 롯데백화점)서울특별시 동대문구 전농동 591-53번지
5(주)대흥모터스30500002119990001921대기배출업소관리201711293050000서울특별시 동대문구정기Y대기배출시설 적정 운영 여부<NA>서울특별시 동대문구 고산자로 568 (제기동)서울특별시 동대문구 제기동 136-3번지
6클라쎄오토(주)30500002120080000121대기배출업소관리201711293050000서울특별시 동대문구정기N대기배출시설 적정 운영 여부<NA>서울특별시 동대문구 천호대로 361 (장안동)서울특별시 동대문구 장안동 413-4번지
7주식회사 선진모터스30500002220160000122폐수배출업소관리201711283050000서울특별시 동대문구정기N배출시설 및 방지시설 적정 운영중<NA>서울특별시 동대문구 천호대로 445 (장안동, (주)선진모터스)서울특별시 동대문구 장안동 466-11번지
8수도에너지(주) 동서울충전소30500002220150000422폐수배출업소관리201711283050000서울특별시 동대문구정기N배출시설 및 방지시설 적정 운영중<NA>서울특별시 동대문구 망우로 57 (휘경동)서울특별시 동대문구 휘경동 267-10번지
9한국외국어대학교30500002120150001121대기배출업소관리201711273050000서울특별시 동대문구정기N대기배출시설 적정 운영 여부<NA>서울특별시 동대문구 이문로 107 (이문동, 한국외국어대학교)서울특별시 동대문구 이문동 270-1번지
업체(시설)명인허가번호업종코드업종명지도점검일자점검기관점검기관명지도점검구분처분대상여부점검사항점검결과소재지도로명주소소재지주소
709진도카공업사30500002220040000522폐수배출업소관리201003193050000서울특별시 동대문구정기N배출시설 및 방지시설 지도점검<NA>서울특별시 동대문구 황물로 9-2 (전농동)서울특별시 동대문구 전농동 644-31번지
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