Overview

Dataset statistics

Number of variables11
Number of observations778
Missing cells382
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory69.3 KiB
Average record size in memory91.2 B

Variable types

Numeric3
Categorical4
Text2
DateTime2

Dataset

Description2000년~2023년 6월 기간동안 인검증 받은 환경신기술(신기술인증, 기술검증)의 유효기간(시작일, 종료일, 심사일 등) 정보 제공
URLhttps://www.data.go.kr/data/15103097/fileData.do

Alerts

평가결과 has constant value ""Constant
세부분야 is highly overall correlated with 대분야High correlation
대분야 is highly overall correlated with 세부분야High correlation
순번 is highly overall correlated with 검증서번호 and 1 other fieldsHigh correlation
인증서번호 is highly overall correlated with 검증서번호High correlation
검증서번호 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 순번High correlation
인증서번호 has 12 (1.5%) missing valuesMissing
검증서번호 has 358 (46.0%) missing valuesMissing
기술명 has 12 (1.5%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:42:44.051143
Analysis finished2023-12-12 17:42:46.249626
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct778
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean389.5
Minimum1
Maximum778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2023-12-13T02:42:46.353455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile39.85
Q1195.25
median389.5
Q3583.75
95-th percentile739.15
Maximum778
Range777
Interquartile range (IQR)388.5

Descriptive statistics

Standard deviation224.73355
Coefficient of variation (CV)0.57697958
Kurtosis-1.2
Mean389.5
Median Absolute Deviation (MAD)194.5
Skewness0
Sum303031
Variance50505.167
MonotonicityStrictly increasing
2023-12-13T02:42:46.517319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
536 1
 
0.1%
514 1
 
0.1%
515 1
 
0.1%
516 1
 
0.1%
517 1
 
0.1%
518 1
 
0.1%
519 1
 
0.1%
520 1
 
0.1%
521 1
 
0.1%
Other values (768) 768
98.7%
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 (%)
778 1
0.1%
777 1
0.1%
776 1
0.1%
775 1
0.1%
774 1
0.1%
773 1
0.1%
772 1
0.1%
771 1
0.1%
770 1
0.1%
769 1
0.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
신기술인증
502 
기술검증
276 

Length

Max length5
Median length5
Mean length4.6452442
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신기술인증 502
64.5%
기술검증 276
35.5%

Length

2023-12-13T02:42:46.691873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:42:46.785709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신기술인증 502
64.5%
기술검증 276
35.5%

대분야
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
폐기물
310 
수질
259 
기타
160 
대기
49 

Length

Max length3
Median length2
Mean length2.3984576
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수질
2nd row폐기물
3rd row수질
4th row수질
5th row수질

Common Values

ValueCountFrequency (%)
폐기물 310
39.8%
수질 259
33.3%
기타 160
20.6%
대기 49
 
6.3%

Length

2023-12-13T02:42:46.882227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:42:46.993852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐기물 310
39.8%
수질 259
33.3%
기타 160
20.6%
대기 49
 
6.3%

세부분야
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
건설폐기물
203 
하수
177 
관거
114 
기타
63 
정수
42 
Other values (11)
179 

Length

Max length6
Median length2
Mean length3.277635
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row하수
2nd row가연성폐기물
3rd row하수
4th row하수
5th row하수

Common Values

ValueCountFrequency (%)
건설폐기물 203
26.1%
하수 177
22.8%
관거 114
14.7%
기타 63
 
8.1%
정수 42
 
5.4%
하수슬러지 38
 
4.9%
가연성폐기물 25
 
3.2%
유기성폐기물 18
 
2.3%
악취 17
 
2.2%
생태 16
 
2.1%
Other values (6) 65
 
8.4%

Length

2023-12-13T02:42:47.118169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건설폐기물 203
26.1%
하수 177
22.8%
관거 114
14.7%
기타 63
 
8.1%
정수 42
 
5.4%
하수슬러지 38
 
4.9%
가연성폐기물 25
 
3.2%
유기성폐기물 18
 
2.3%
악취 17
 
2.2%
생태 16
 
2.1%
Other values (6) 65
 
8.4%

평가결과
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
합격
778 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 778
100.0%

Length

2023-12-13T02:42:47.239066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:42:47.339134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 778
100.0%

인증서번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct618
Distinct (%)80.7%
Missing12
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean337.70366
Minimum1
Maximum619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2023-12-13T02:42:47.444727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile39.25
Q1189.25
median353.5
Q3496
95-th percentile590.75
Maximum619
Range618
Interquartile range (IQR)306.75

Descriptive statistics

Standard deviation177.84783
Coefficient of variation (CV)0.52663875
Kurtosis-1.1580367
Mean337.70366
Median Absolute Deviation (MAD)152
Skewness-0.20846563
Sum258681
Variance31629.851
MonotonicityNot monotonic
2023-12-13T02:42:47.577093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
506 2
 
0.3%
440 2
 
0.3%
442 2
 
0.3%
439 2
 
0.3%
378 2
 
0.3%
441 2
 
0.3%
486 2
 
0.3%
487 2
 
0.3%
389 2
 
0.3%
455 2
 
0.3%
Other values (608) 746
95.9%
(Missing) 12
 
1.5%
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 (%)
619 1
0.1%
618 1
0.1%
617 1
0.1%
616 1
0.1%
615 2
0.3%
614 1
0.1%
613 1
0.1%
612 1
0.1%
611 1
0.1%
610 1
0.1%

검증서번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct275
Distinct (%)65.5%
Missing358
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean159.18571
Minimum1
Maximum275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2023-12-13T02:42:47.713428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.95
Q1104.75
median169.5
Q3222
95-th percentile264.05
Maximum275
Range274
Interquartile range (IQR)117.25

Descriptive statistics

Standard deviation75.43825
Coefficient of variation (CV)0.47390088
Kurtosis-0.8959933
Mean159.18571
Median Absolute Deviation (MAD)58
Skewness-0.39391296
Sum66858
Variance5690.9296
MonotonicityIncreasing
2023-12-13T02:42:47.848817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192 2
 
0.3%
178 2
 
0.3%
179 2
 
0.3%
180 2
 
0.3%
181 2
 
0.3%
182 2
 
0.3%
183 2
 
0.3%
184 2
 
0.3%
185 2
 
0.3%
186 2
 
0.3%
Other values (265) 400
51.4%
(Missing) 358
46.0%
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 (%)
275 2
0.3%
274 2
0.3%
273 2
0.3%
272 2
0.3%
271 2
0.3%
270 2
0.3%
269 2
0.3%
268 2
0.3%
267 1
0.1%
266 2
0.3%

기술보유자
Text

Distinct609
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-13T02:42:48.027353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length44
Mean length15.697943
Min length2

Characters and Unicode

Total characters12213
Distinct characters355
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique451 ?
Unique (%)58.0%

Sample

1st row㈜화인프로텍
2nd row㈜고려소각로공업
3rd row㈜제오텍/(주)태영건설
4th row에이치투엘㈜
5th row삼성물산㈜
ValueCountFrequency (%)
주식회사 18
 
2.1%
산학협력단 8
 
0.9%
현대건설(주 6
 
0.7%
삼성엔지니어링(주 6
 
0.7%
㈜환경시설관리공사 5
 
0.6%
5
 
0.6%
주)대우건설 5
 
0.6%
주)대진환경산업 4
 
0.5%
주)지앤지테크놀러지 4
 
0.5%
주)그린텍아이엔씨 4
 
0.5%
Other values (609) 797
92.5%
2023-12-13T02:42:48.712276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 840
 
6.9%
( 836
 
6.8%
) 836
 
6.8%
/ 710
 
5.8%
589
 
4.8%
㈜ 437
 
3.6%
경 312
 
2.6%
환 302
 
2.5%
이 270
 
2.2%
산 246
 
2.0%
Other values (345) 6835
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8676
71.0%
Open Punctuation 836
 
6.8%
Close Punctuation 836
 
6.8%
Other Punctuation 735
 
6.0%
Space Separator 589
 
4.8%
Other Symbol 437
 
3.6%
Uppercase Letter 71
 
0.6%
Lowercase Letter 29
 
0.2%
Math Symbol 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 840
 
9.7%
경 312
 
3.6%
환 302
 
3.5%
이 270
 
3.1%
산 246
 
2.8%
업 234
 
2.7%
건 224
 
2.6%
설 208
 
2.4%
한 185
 
2.1%
엔 181
 
2.1%
Other values (315) 5674
65.4%
Uppercase Letter
ValueCountFrequency (%)
G 17
23.9%
S 13
18.3%
E 9
12.7%
L 7
9.9%
N 7
9.9%
T 6
 
8.5%
C 4
 
5.6%
K 3
 
4.2%
Y 3
 
4.2%
I 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
o 7
24.1%
d 6
20.7%
i 4
13.8%
e 3
10.3%
t 3
10.3%
n 3
10.3%
v 2
 
6.9%
x 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/ 710
96.6%
, 17
 
2.3%
. 7
 
1.0%
& 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 836
100.0%
Close Punctuation
ValueCountFrequency (%)
) 836
100.0%
Space Separator
ValueCountFrequency (%)
589
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 437
100.0%
Math Symbol
ValueCountFrequency (%)
| 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9113
74.6%
Common 3000
 
24.6%
Latin 100
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 840
 
9.2%
㈜ 437
 
4.8%
경 312
 
3.4%
환 302
 
3.3%
이 270
 
3.0%
산 246
 
2.7%
업 234
 
2.6%
건 224
 
2.5%
설 208
 
2.3%
한 185
 
2.0%
Other values (316) 5855
64.2%
Latin
ValueCountFrequency (%)
G 17
17.0%
S 13
13.0%
E 9
9.0%
o 7
 
7.0%
L 7
 
7.0%
N 7
 
7.0%
d 6
 
6.0%
T 6
 
6.0%
i 4
 
4.0%
C 4
 
4.0%
Other values (9) 20
20.0%
Common
ValueCountFrequency (%)
( 836
27.9%
) 836
27.9%
/ 710
23.7%
589
19.6%
, 17
 
0.6%
. 7
 
0.2%
| 2
 
0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
& 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8676
71.0%
ASCII 3100
 
25.4%
None 437
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 840
 
9.7%
경 312
 
3.6%
환 302
 
3.5%
이 270
 
3.1%
산 246
 
2.8%
업 234
 
2.7%
건 224
 
2.6%
설 208
 
2.4%
한 185
 
2.1%
엔 181
 
2.1%
Other values (315) 5674
65.4%
ASCII
ValueCountFrequency (%)
( 836
27.0%
) 836
27.0%
/ 710
22.9%
589
19.0%
, 17
 
0.5%
G 17
 
0.5%
S 13
 
0.4%
E 9
 
0.3%
o 7
 
0.2%
L 7
 
0.2%
Other values (19) 59
 
1.9%
None
ValueCountFrequency (%)
㈜ 437
100.0%

기술명
Text

MISSING 

Distinct627
Distinct (%)81.9%
Missing12
Missing (%)1.5%
Memory size6.2 KiB
2023-12-13T02:42:49.024758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length127
Median length76
Mean length46.322454
Min length17

Characters and Unicode

Total characters35483
Distinct characters594
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique488 ?
Unique (%)63.7%

Sample

1st row응집침전 및 입상황을 이용한 생물막여과 하수처리기술
2nd row하향통풍식 화염건류실을 설치한 이동화상식 소각로
3rd row음식물쓰레기 산발효액을 이용한 하수 고도처리기술
4th row섬모상 담체를 이용한 하수의 유기물 및 질소·인 고도처리기술(CNR Process)
5th row전무산소, 혐기, 간헐포기를 이용한 하수처리기술(Star공법)
ValueCountFrequency (%)
이용한 462
 
6.3%
기술 245
 
3.4%
및 184
 
2.5%
생산기술 74
 
1.0%
순환골재 61
 
0.8%
비굴착 57
 
0.8%
의한 56
 
0.8%
콘크리트용 54
 
0.7%
이용하여 49
 
0.7%
하수 49
 
0.7%
Other values (3119) 5994
82.3%
2023-12-13T02:42:49.520745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7015
 
19.8%
기 1112
 
3.1%
이 854
 
2.4%
용 807
 
2.3%
한 696
 
2.0%
술 663
 
1.9%
수 663
 
1.9%
리 535
 
1.5%
를 491
 
1.4%
하 484
 
1.4%
Other values (584) 22163
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25385
71.5%
Space Separator 7015
 
19.8%
Uppercase Letter 1136
 
3.2%
Lowercase Letter 1123
 
3.2%
Other Punctuation 203
 
0.6%
Open Punctuation 200
 
0.6%
Close Punctuation 200
 
0.6%
Decimal Number 120
 
0.3%
Dash Punctuation 87
 
0.2%
Other Symbol 7
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1112
 
4.4%
이 854
 
3.4%
용 807
 
3.2%
한 696
 
2.7%
술 663
 
2.6%
수 663
 
2.6%
리 535
 
2.1%
를 491
 
1.9%
하 484
 
1.9%
형 349
 
1.4%
Other values (502) 18731
73.8%
Lowercase Letter
ValueCountFrequency (%)
e 159
14.2%
i 97
 
8.6%
r 94
 
8.4%
s 89
 
7.9%
t 81
 
7.2%
o 81
 
7.2%
a 73
 
6.5%
l 66
 
5.9%
n 62
 
5.5%
c 51
 
4.5%
Other values (17) 270
24.0%
Uppercase Letter
ValueCountFrequency (%)
S 173
15.2%
B 124
10.9%
P 109
 
9.6%
R 107
 
9.4%
M 76
 
6.7%
C 72
 
6.3%
A 52
 
4.6%
O 50
 
4.4%
F 46
 
4.0%
D 46
 
4.0%
Other values (16) 281
24.7%
Other Punctuation
ValueCountFrequency (%)
· 72
35.5%
, 63
31.0%
/ 49
24.1%
: 7
 
3.4%
. 6
 
3.0%
; 3
 
1.5%
% 2
 
1.0%
' 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 59
49.2%
3 21
 
17.5%
1 11
 
9.2%
4 11
 
9.2%
0 10
 
8.3%
8 4
 
3.3%
5 2
 
1.7%
6 2
 
1.7%
Other Symbol
ValueCountFrequency (%)
® 3
42.9%
ⓢ 2
28.6%
ⓜ 1
 
14.3%
○ 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 199
99.5%
[ 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 199
99.5%
] 1
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
66.7%
Ⅰ 2
33.3%
Space Separator
ValueCountFrequency (%)
7015
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25384
71.5%
Common 7833
 
22.1%
Latin 2264
 
6.4%
Greek 1
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1112
 
4.4%
이 854
 
3.4%
용 807
 
3.2%
한 696
 
2.7%
술 663
 
2.6%
수 663
 
2.6%
리 535
 
2.1%
를 491
 
1.9%
하 484
 
1.9%
형 349
 
1.4%
Other values (501) 18730
73.8%
Latin
ValueCountFrequency (%)
S 173
 
7.6%
e 159
 
7.0%
B 124
 
5.5%
P 109
 
4.8%
R 107
 
4.7%
i 97
 
4.3%
r 94
 
4.2%
s 89
 
3.9%
t 81
 
3.6%
o 81
 
3.6%
Other values (44) 1150
50.8%
Common
ValueCountFrequency (%)
7015
89.6%
( 199
 
2.5%
) 199
 
2.5%
- 87
 
1.1%
· 72
 
0.9%
, 63
 
0.8%
2 59
 
0.8%
/ 49
 
0.6%
3 21
 
0.3%
1 11
 
0.1%
Other values (17) 58
 
0.7%
Greek
ValueCountFrequency (%)
γ 1
100.0%
Han
ValueCountFrequency (%)
前 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25382
71.5%
ASCII 10011
 
28.2%
None 77
 
0.2%
Number Forms 6
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK 1
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7015
70.1%
( 199
 
2.0%
) 199
 
2.0%
S 173
 
1.7%
e 159
 
1.6%
B 124
 
1.2%
P 109
 
1.1%
R 107
 
1.1%
i 97
 
1.0%
r 94
 
0.9%
Other values (63) 1735
 
17.3%
Hangul
ValueCountFrequency (%)
기 1112
 
4.4%
이 854
 
3.4%
용 807
 
3.2%
한 696
 
2.7%
술 663
 
2.6%
수 663
 
2.6%
리 535
 
2.1%
를 491
 
1.9%
하 484
 
1.9%
형 349
 
1.4%
Other values (500) 18728
73.8%
None
ValueCountFrequency (%)
· 72
93.5%
® 3
 
3.9%
₂ 1
 
1.3%
γ 1
 
1.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
66.7%
Ⅰ 2
33.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓢ 2
66.7%
ⓜ 1
33.3%
CJK
ValueCountFrequency (%)
前 1
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

유효기간시작일(최초)
Date

Distinct479
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2000-12-18 00:00:00
Maximum2023-06-05 00:00:00
2023-12-13T02:42:49.665465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:49.810110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

유효기간최종종료일
Date

Distinct554
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2004-02-25 00:00:00
Maximum2031-11-16 00:00:00
2023-12-13T02:42:49.964541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:50.089621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T02:42:45.613799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:44.914374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.262804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.712878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.060456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.401391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.802090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.175919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:45.515836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:42:50.180374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분대분야세부분야인증서번호검증서번호
순번1.0000.8890.4560.5120.9220.953
구분0.8891.0000.3860.3870.2300.529
대분야0.4560.3861.0000.9980.3320.444
세부분야0.5120.3870.9981.0000.4050.522
인증서번호0.9220.2300.3320.4051.0000.969
검증서번호0.9530.5290.4440.5220.9691.000
2023-12-13T02:42:50.300761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분세부분야대분야
구분1.0000.3020.258
세부분야0.3021.0000.936
대분야0.2580.9361.000
2023-12-13T02:42:50.418429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번인증서번호검증서번호구분대분야세부분야
순번1.0000.3561.0000.7210.2880.227
인증서번호0.3561.0000.9870.1750.2030.170
검증서번호1.0000.9871.0000.4040.2780.246
구분0.7210.1750.4041.0000.2580.302
대분야0.2880.2030.2780.2581.0000.936
세부분야0.2270.1700.2460.3020.9361.000

Missing values

2023-12-13T02:42:45.927514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:42:46.080182image/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.
2023-12-13T02:42:46.184422image/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

순번구분대분야세부분야평가결과인증서번호검증서번호기술보유자기술명유효기간시작일(최초)유효기간최종종료일
01기술검증수질하수합격11㈜화인프로텍응집침전 및 입상황을 이용한 생물막여과 하수처리기술2000-12-182005-12-17
12기술검증폐기물가연성폐기물합격22㈜고려소각로공업하향통풍식 화염건류실을 설치한 이동화상식 소각로2001-01-302007-01-29
23기술검증수질하수합격33㈜제오텍/(주)태영건설음식물쓰레기 산발효액을 이용한 하수 고도처리기술2001-02-052007-02-04
34기술검증수질하수합격44에이치투엘㈜섬모상 담체를 이용한 하수의 유기물 및 질소·인 고도처리기술(CNR Process)2001-02-062007-02-05
45기술검증수질하수합격55삼성물산㈜전무산소, 혐기, 간헐포기를 이용한 하수처리기술(Star공법)2001-02-142007-02-13
56기술검증폐기물유기성폐기물합격<NA>6(주)한국삼록환경<NA>2001-02-262004-02-25
67기술검증수질하수합격67한화석유화학㈜/(주)한화건설유로변경형 질소·인 하수 고도처리기술(HDF Process)2001-02-262007-02-25
78기술검증수질하수합격78금호산업(주)단일반응조 간헐방류식 장기포기 공정에 의한 하수고도처리 기술(KIDEA Process)2001-02-262007-02-25
89기술검증폐기물하수슬러지합격89㈜한틀산업파쇄 및 다단건조상을 이용한 하수슬러지 건조기술2001-02-262004-02-25
910기술검증폐기물유기성폐기물합격910㈜정한그린테크생석회를 이용한 유기성폐기물의 토지개량제 제조기술2001-02-262006-02-25
순번구분대분야세부분야평가결과인증서번호검증서번호기술보유자기술명유효기간시작일(최초)유효기간최종종료일
768769신기술인증폐기물건설폐기물합격609<NA>(재)한국화학융합시험연구원/주식회사 오성개발/주식회사 대림환경/(주)성철환경개발임팩트패널, 회전해머 및 그라인더를 조합하여 부착모르타르 제거효율을 향상시킨 콘크리트용 순환굵은골재 생산기술2022-05-312030-05-30
769770신기술인증기타관거합격610<NA>부성산업기술(주)/우람건설(주)/(주)구마이엔씨워터젯 노면절삭장치와 맨홀철개 높이조절장치를 이용한 맨홀보수기술2022-06-272030-06-26
770771신기술인증폐기물건설폐기물합격611<NA>㈜글로벌환경/신구대학교 산학협력단/자원개발㈜/(유)전일환경전기 전도도 센서와 진동 주파수 제어시스템이 적용된 선별 스크린을 이용한 성토용 순환토사 생산기술2022-07-122030-07-11
771772신기술인증폐기물가연성폐기물합격612<NA>아세아시멘트(주)시멘트 하소 공정 중 폐플라스틱류 보조연료 풍력 선별 전처리 기술2022-08-162030-08-15
772773신기술인증폐기물건설폐기물합격613<NA>(주)씨.에스/류기남/(주)부호산업개발/신구대학교 산학협력단균등량 공급제어 장치를 이용하여 도로 입도조정 기층용 순환골재를 생산하는 기술2022-09-062030-09-05
773774신기술인증폐기물건설폐기물합격614<NA>(주)홍명산업/(주)두승/성산환경(주)다수의 교차 회전 날개가 장착된 8각 2축 박리크러셔를 건설폐기물 중간처리 공정에 적용하여 콘크리트용 골재의 품질향상 기술2022-09-302030-09-29
774775신기술인증기타관거합격616<NA>주식회사 엔탑이앤지러버히터가 설치된 패커를 이용한 하수관로 비굴착 부분보수공법2023-04-242031-04-23
775776신기술인증폐기물건설폐기물합격617<NA>(주)모악환경산업낙하 충격과 풍력을 이용한 순환골재의 유기이물질 제거 기술2023-04-242031-04-23
776777신기술인증기타관거합격618<NA>주식회사 모악엔지니어링/주식회사 오성이엔씨/주식회사 한국광기술화재 안전형 하수관로 비굴착 광경화 전체보수 공법(FS-UV 공법)2023-04-252031-04-24
777778신기술인증기타기타합격619<NA>주식회사 누보켐/주식회사 유진컨스텍고압 물 분사 장치를 이용한 폼드 배수성 아스팔트 혼합물제조 기술2023-06-052031-06-04