Overview

Dataset statistics

Number of variables12
Number of observations1237
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.5 KiB
Average record size in memory98.1 B

Variable types

Numeric2
Text3
Categorical6
DateTime1

Dataset

Description한국장애인고용공단에서 장애물 없는 생활환경(BF, Barrier Free)인증을 받은 건축물의 정보를 제공합니다.
Author한국장애인고용공단
URLhttps://www.data.go.kr/data/15014781/fileData.do

Alerts

인증대상 has constant value ""Constant
인증구분 is highly overall correlated with 인증만료(취소)여부High correlation
인증만료(취소)여부 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
사업장구분 is highly overall correlated with 인증만료(취소)여부High correlation
연번 is highly overall correlated with 인증번호 and 1 other fieldsHigh correlation
인증번호 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
등급 is highly imbalanced (80.3%)Imbalance
사업장구분 is highly imbalanced (65.4%)Imbalance
인증만료(취소)여부 is highly imbalanced (96.5%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:50:15.517818
Analysis finished2024-03-14 09:50:18.509495
Duration2.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1237
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean619
Minimum1
Maximum1237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-03-14T18:50:18.707352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile62.8
Q1310
median619
Q3928
95-th percentile1175.2
Maximum1237
Range1236
Interquartile range (IQR)618

Descriptive statistics

Standard deviation357.23545
Coefficient of variation (CV)0.57711704
Kurtosis-1.2
Mean619
Median Absolute Deviation (MAD)309
Skewness0
Sum765703
Variance127617.17
MonotonicityStrictly increasing
2024-03-14T18:50:19.161879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
824 1
 
0.1%
831 1
 
0.1%
830 1
 
0.1%
829 1
 
0.1%
828 1
 
0.1%
827 1
 
0.1%
826 1
 
0.1%
825 1
 
0.1%
823 1
 
0.1%
Other values (1227) 1227
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1237 1
0.1%
1236 1
0.1%
1235 1
0.1%
1234 1
0.1%
1233 1
0.1%
1232 1
0.1%
1231 1
0.1%
1230 1
0.1%
1229 1
0.1%
1228 1
0.1%

시설물명
Text

Distinct1029
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-03-14T18:50:20.349931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length33
Mean length12.037995
Min length4

Characters and Unicode

Total characters14891
Distinct characters504
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique822 ?
Unique (%)66.5%

Sample

1st row성모의지
2nd row위앤미㈜ 감귤가공공장
3rd row지에스피㈜
4th row㈜삼구팔구
5th row㈜대동소방
ValueCountFrequency (%)
공중화장실 72
 
2.5%
경로당 57
 
2.0%
및 50
 
1.8%
화장실 35
 
1.2%
공영주차장 27
 
1.0%
행정복지센터 20
 
0.7%
증축공사 15
 
0.5%
주민센터 15
 
0.5%
조성사업 15
 
0.5%
청사 11
 
0.4%
Other values (1693) 2520
88.8%
2024-03-14T18:50:21.958004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1601
 
10.8%
장 352
 
2.4%
공 349
 
2.3%
터 305
 
2.0%
화 290
 
1.9%
센 290
 
1.9%
지 278
 
1.9%
동 271
 
1.8%
원 232
 
1.6%
사 232
 
1.6%
Other values (494) 10691
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12706
85.3%
Space Separator 1601
 
10.8%
Decimal Number 240
 
1.6%
Open Punctuation 114
 
0.8%
Close Punctuation 114
 
0.8%
Uppercase Letter 42
 
0.3%
Other Punctuation 30
 
0.2%
Other Symbol 29
 
0.2%
Dash Punctuation 10
 
0.1%
Final Punctuation 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 352
 
2.8%
공 349
 
2.7%
터 305
 
2.4%
화 290
 
2.3%
센 290
 
2.3%
지 278
 
2.2%
동 271
 
2.1%
원 232
 
1.8%
사 232
 
1.8%
시 221
 
1.7%
Other values (453) 9886
77.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
 
9.5%
M 4
 
9.5%
A 4
 
9.5%
T 3
 
7.1%
E 3
 
7.1%
C 3
 
7.1%
S 3
 
7.1%
R 2
 
4.8%
O 2
 
4.8%
D 2
 
4.8%
Other values (8) 12
28.6%
Decimal Number
ValueCountFrequency (%)
1 66
27.5%
2 56
23.3%
3 49
20.4%
0 14
 
5.8%
7 11
 
4.6%
5 10
 
4.2%
4 10
 
4.2%
8 9
 
3.8%
6 9
 
3.8%
9 6
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 23
76.7%
· 4
 
13.3%
: 1
 
3.3%
. 1
 
3.3%
& 1
 
3.3%
Space Separator
ValueCountFrequency (%)
1601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Final Punctuation
ValueCountFrequency (%)
” 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12735
85.5%
Common 2114
 
14.2%
Latin 42
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 352
 
2.8%
공 349
 
2.7%
터 305
 
2.4%
화 290
 
2.3%
센 290
 
2.3%
지 278
 
2.2%
동 271
 
2.1%
원 232
 
1.8%
사 232
 
1.8%
시 221
 
1.7%
Other values (454) 9915
77.9%
Common
ValueCountFrequency (%)
1601
75.7%
( 114
 
5.4%
) 114
 
5.4%
1 66
 
3.1%
2 56
 
2.6%
3 49
 
2.3%
, 23
 
1.1%
0 14
 
0.7%
7 11
 
0.5%
5 10
 
0.5%
Other values (12) 56
 
2.6%
Latin
ValueCountFrequency (%)
B 4
 
9.5%
M 4
 
9.5%
A 4
 
9.5%
T 3
 
7.1%
E 3
 
7.1%
C 3
 
7.1%
S 3
 
7.1%
R 2
 
4.8%
O 2
 
4.8%
D 2
 
4.8%
Other values (8) 12
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12706
85.3%
ASCII 2148
 
14.4%
None 33
 
0.2%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1601
74.5%
( 114
 
5.3%
) 114
 
5.3%
1 66
 
3.1%
2 56
 
2.6%
3 49
 
2.3%
, 23
 
1.1%
0 14
 
0.7%
7 11
 
0.5%
5 10
 
0.5%
Other values (27) 90
 
4.2%
Hangul
ValueCountFrequency (%)
장 352
 
2.8%
공 349
 
2.7%
터 305
 
2.4%
화 290
 
2.3%
센 290
 
2.3%
지 278
 
2.2%
동 271
 
2.1%
원 232
 
1.8%
사 232
 
1.8%
시 221
 
1.7%
Other values (453) 9886
77.8%
None
ValueCountFrequency (%)
㈜ 29
87.9%
· 4
 
12.1%
Punctuation
ValueCountFrequency (%)
” 2
50.0%
“ 2
50.0%

인증대상
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
건축물
1237 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건축물 1237
100.0%

Length

2024-03-14T18:50:22.371153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:50:22.678799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물 1237
100.0%

인증구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
예비
777 
본
460 

Length

Max length2
Median length2
Mean length1.6281326
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
예비 777
62.8%
본 460
37.2%

Length

2024-03-14T18:50:23.007474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:50:23.319819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예비 777
62.8%
본 460
37.2%

등급
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
우수
1177 
일반
 
50
최우수
 
10

Length

Max length3
Median length2
Mean length2.0080841
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row최우수
2nd row우수
3rd row우수
4th row우수
5th row우수

Common Values

ValueCountFrequency (%)
우수 1177
95.1%
일반 50
 
4.0%
최우수 10
 
0.8%

Length

2024-03-14T18:50:23.671471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:50:23.997692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우수 1177
95.1%
일반 50
 
4.0%
최우수 10
 
0.8%

인증번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1202
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3739.0057
Minimum176
Maximum9591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-03-14T18:50:24.358466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176
5-th percentile573.8
Q11799
median3463
Q35129
95-th percentile8568.8
Maximum9591
Range9415
Interquartile range (IQR)3330

Descriptive statistics

Standard deviation2374.5595
Coefficient of variation (CV)0.63507782
Kurtosis-0.38249485
Mean3739.0057
Median Absolute Deviation (MAD)1666
Skewness0.63055456
Sum4625150
Variance5638533
MonotonicityNot monotonic
2024-03-14T18:50:24.801842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
601 2
 
0.2%
4788 2
 
0.2%
586 2
 
0.2%
2798 2
 
0.2%
4006 2
 
0.2%
1893 2
 
0.2%
5242 2
 
0.2%
5379 2
 
0.2%
5253 2
 
0.2%
7394 2
 
0.2%
Other values (1192) 1217
98.4%
ValueCountFrequency (%)
176 1
0.1%
206 1
0.1%
208 1
0.1%
216 1
0.1%
217 1
0.1%
254 1
0.1%
291 1
0.1%
316 1
0.1%
324 1
0.1%
335 1
0.1%
ValueCountFrequency (%)
9591 1
0.1%
9578 1
0.1%
9554 1
0.1%
9511 1
0.1%
9494 1
0.1%
9481 1
0.1%
9463 1
0.1%
9420 1
0.1%
9404 1
0.1%
9401 1
0.1%

지역코드
Categorical

Distinct18
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
경기도
216 
충청남도
139 
경상남도
132 
경상북도
106 
전라남도
90 
Other values (13)
554 

Length

Max length7
Median length5
Mean length4.214228
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시
2nd row제주특별자치도
3rd row경기도
4th row광주광역시
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 216
17.5%
충청남도 139
11.2%
경상남도 132
10.7%
경상북도 106
8.6%
전라남도 90
7.3%
서울특별시 79
 
6.4%
부산광역시 79
 
6.4%
강원도 69
 
5.6%
제주특별자치도 64
 
5.2%
전라북도 62
 
5.0%
Other values (8) 201
16.2%

Length

2024-03-14T18:50:25.252743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 216
17.5%
충청남도 139
11.2%
경상남도 132
10.7%
경상북도 106
8.6%
전라남도 90
7.3%
서울특별시 79
 
6.4%
부산광역시 79
 
6.4%
강원도 69
 
5.6%
제주특별자치도 64
 
5.2%
전라북도 62
 
5.0%
Other values (8) 201
16.2%

시군구
Text

Distinct199
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-03-14T18:50:26.608695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0226354
Min length2

Characters and Unicode

Total characters3739
Distinct characters138
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)2.2%

Sample

1st row동구
2nd row서귀포시
3rd row안양시
4th row광산구
5th row김포시
ValueCountFrequency (%)
서귀포시 38
 
3.1%
제주시 24
 
1.9%
화성시 23
 
1.9%
여수시 22
 
1.8%
해운대구 21
 
1.7%
수원시 20
 
1.6%
김해시 20
 
1.6%
금산군 19
 
1.5%
북구 19
 
1.5%
서구 19
 
1.5%
Other values (189) 1012
81.8%
2024-03-14T18:50:28.358200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 588
 
15.7%
군 386
 
10.3%
구 288
 
7.7%
주 145
 
3.9%
양 124
 
3.3%
산 116
 
3.1%
서 104
 
2.8%
포 96
 
2.6%
성 95
 
2.5%
남 72
 
1.9%
Other values (128) 1725
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3739
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 588
 
15.7%
군 386
 
10.3%
구 288
 
7.7%
주 145
 
3.9%
양 124
 
3.3%
산 116
 
3.1%
서 104
 
2.8%
포 96
 
2.6%
성 95
 
2.5%
남 72
 
1.9%
Other values (128) 1725
46.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3739
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 588
 
15.7%
군 386
 
10.3%
구 288
 
7.7%
주 145
 
3.9%
양 124
 
3.3%
산 116
 
3.1%
서 104
 
2.8%
포 96
 
2.6%
성 95
 
2.5%
남 72
 
1.9%
Other values (128) 1725
46.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3739
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 588
 
15.7%
군 386
 
10.3%
구 288
 
7.7%
주 145
 
3.9%
양 124
 
3.3%
산 116
 
3.1%
서 104
 
2.8%
포 96
 
2.6%
성 95
 
2.5%
남 72
 
1.9%
Other values (128) 1725
46.1%

인증발급일
Date

Distinct621
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
Minimum2014-08-22 00:00:00
Maximum2023-12-22 00:00:00
2024-03-14T18:50:28.762962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:50:29.390837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인증만료일
Text

Distinct334
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-03-14T18:50:30.563906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length18.793856
Min length10

Characters and Unicode

Total characters23248
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)19.5%

Sample

1st row본인증 교부 전 또는 사용승인 후 1년 이내
2nd row본인증 교부 전 또는 사용승인 후 1년 이내
3rd row본인증 교부 전 또는 사용승인 후 1년 이내
4th row본인증 교부 전 또는 사용승인 후 1년 이내
5th row본인증 교부 전 또는 사용승인 후 1년 이내
ValueCountFrequency (%)
본인증 777
11.6%
후 777
11.6%
이내 777
11.6%
1년 777
11.6%
교부 777
11.6%
사용승인 777
11.6%
전 777
11.6%
또는 777
11.6%
2031-02-09 6
 
0.1%
2027-11-29 5
 
0.1%
Other values (331) 449
6.7%
2024-03-14T18:50:32.189080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5439
23.4%
인 1554
 
6.7%
1 1304
 
5.6%
0 1051
 
4.5%
2 1002
 
4.3%
- 920
 
4.0%
승 777
 
3.3%
내 777
 
3.3%
이 777
 
3.3%
년 777
 
3.3%
Other values (17) 8870
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12432
53.5%
Space Separator 5439
23.4%
Decimal Number 4457
 
19.2%
Dash Punctuation 920
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 1554
 
12.5%
승 777
 
6.2%
내 777
 
6.2%
이 777
 
6.2%
년 777
 
6.2%
후 777
 
6.2%
본 777
 
6.2%
용 777
 
6.2%
사 777
 
6.2%
는 777
 
6.2%
Other values (5) 3885
31.2%
Decimal Number
ValueCountFrequency (%)
1 1304
29.3%
0 1051
23.6%
2 1002
22.5%
3 442
 
9.9%
9 156
 
3.5%
8 152
 
3.4%
7 117
 
2.6%
5 79
 
1.8%
4 77
 
1.7%
6 77
 
1.7%
Space Separator
ValueCountFrequency (%)
5439
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12432
53.5%
Common 10816
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 1554
 
12.5%
승 777
 
6.2%
내 777
 
6.2%
이 777
 
6.2%
년 777
 
6.2%
후 777
 
6.2%
본 777
 
6.2%
용 777
 
6.2%
사 777
 
6.2%
는 777
 
6.2%
Other values (5) 3885
31.2%
Common
ValueCountFrequency (%)
5439
50.3%
1 1304
 
12.1%
0 1051
 
9.7%
2 1002
 
9.3%
- 920
 
8.5%
3 442
 
4.1%
9 156
 
1.4%
8 152
 
1.4%
7 117
 
1.1%
5 79
 
0.7%
Other values (2) 154
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12432
53.5%
ASCII 10816
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5439
50.3%
1 1304
 
12.1%
0 1051
 
9.7%
2 1002
 
9.3%
- 920
 
8.5%
3 442
 
4.1%
9 156
 
1.4%
8 152
 
1.4%
7 117
 
1.1%
5 79
 
0.7%
Other values (2) 154
 
1.4%
Hangul
ValueCountFrequency (%)
인 1554
 
12.5%
승 777
 
6.2%
내 777
 
6.2%
이 777
 
6.2%
년 777
 
6.2%
후 777
 
6.2%
본 777
 
6.2%
용 777
 
6.2%
사 777
 
6.2%
는 777
 
6.2%
Other values (5) 3885
31.2%

사업장구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
공공
1157 
민간
 
80

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공 1157
93.5%
민간 80
 
6.5%

Length

2024-03-14T18:50:32.522785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:50:32.759953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 1157
93.5%
민간 80
 
6.5%

인증만료(취소)여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
1230 
만료
 
4
취소
 
3

Length

Max length4
Median length4
Mean length3.9886823
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1230
99.4%
만료 4
 
0.3%
취소 3
 
0.2%

Length

2024-03-14T18:50:33.132563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:50:33.479819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1230
99.4%
만료 4
 
0.3%
취소 3
 
0.2%

Interactions

2024-03-14T18:50:17.119697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:50:16.588662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:50:17.383354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:50:16.855979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:50:33.684268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번인증구분등급인증번호지역코드사업장구분인증만료(취소)여부
연번1.0000.2710.1750.9200.2530.329NaN
인증구분0.2711.0000.0000.5160.0000.000NaN
등급0.1750.0001.0000.0390.1640.1160.000
인증번호0.9200.5160.0391.0000.2410.287NaN
지역코드0.2530.0000.1640.2411.0000.2390.000
사업장구분0.3290.0000.1160.2870.2391.000NaN
인증만료(취소)여부NaNNaN0.000NaN0.000NaN1.000
2024-03-14T18:50:33.982833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역코드인증구분인증만료(취소)여부사업장구분등급
지역코드1.0000.0000.0000.1870.075
인증구분0.0001.0001.0000.0000.000
인증만료(취소)여부0.0001.0001.0001.0000.000
사업장구분0.1870.0001.0001.0000.192
등급0.0750.0000.0000.1921.000
2024-03-14T18:50:34.257745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번인증번호인증구분등급지역코드사업장구분인증만료(취소)여부
연번1.0000.8770.2070.1050.0990.2521.000
인증번호0.8771.0000.3970.0390.0950.2241.000
인증구분0.2070.3971.0000.0000.0000.0001.000
등급0.1050.0390.0001.0000.0750.1920.000
지역코드0.0990.0950.0000.0751.0000.1870.000
사업장구분0.2520.2240.0000.1920.1871.0001.000
인증만료(취소)여부1.0001.0001.0000.0000.0001.0001.000

Missing values

2024-03-14T18:50:17.756473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:50:18.293328image/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.

Sample

연번시설물명인증대상인증구분등급인증번호지역코드시군구인증발급일인증만료일사업장구분인증만료(취소)여부
01성모의지건축물예비최우수360대구광역시동구2014-08-22본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
12위앤미㈜ 감귤가공공장건축물예비우수373제주특별자치도서귀포시2014-10-13본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
23지에스피㈜건축물예비우수395경기도안양시2014-12-12본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
34㈜삼구팔구건축물예비우수396광주광역시광산구2014-12-12본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
45㈜대동소방건축물예비우수403경기도김포시2014-12-29본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
56㈜내일식품 음성공장건축물예비우수404충청북도음성군2014-12-29본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
67(가칭)THE VERSI(벗이) 미술관건축물예비우수440경기도용인시2015-05-06본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
78성모의지건축물본최우수176대구광역시동구2015-07-012020-06-30민간만료
89(사)화순사랑건축물예비우수465전라남도화순군2015-07-31본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
910㈜유진택시건축물예비우수470대전광역시서구2015-09-03본인증 교부 전 또는 사용승인 후 1년 이내민간<NA>
연번시설물명인증대상인증구분등급인증번호지역코드시군구인증발급일인증만료일사업장구분인증만료(취소)여부
12271228도계 복합체육문화센터건축물예비우수9463강원특별자치도삼척시2023-11-24본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12281229도시재생 터미널지구 숲정이마을공유마당+온가족센터 건립사업건축물예비우수9481전라북도남원시2023-11-27본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12291230음성군청 통합별관건축물예비우수9494충청북도음성군2023-11-29본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12301231산안2리 다목적센터건축물본우수5297충청남도금산군2023-12-052033-12-04공공<NA>
12311232경찰악대 신축공사건축물예비우수9511서울특별시마포구2023-12-05본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12321233산성동 장수경로당건축물본우수5298경기도성남시2023-12-052033-12-04공공<NA>
12331234대림3동 공공복합청사건축물예비우수9554서울특별시영등포구2023-12-13본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12341235외포초 본관동 개축공사건축물예비우수9578경상남도거제시2023-12-18본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12351236영주시 더이음 어울림센터건축물예비우수9591경상북도영주시2023-12-20본인증 교부 전 또는 사용승인 후 1년 이내공공<NA>
12361237양평동초등학교 증축공사건축물본우수5379경기도양평군2023-12-222033-12-04공공<NA>