Overview

Dataset statistics

Number of variables9
Number of observations778
Missing cells382
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.1 KiB
Average record size in memory75.2 B

Variable types

Numeric3
Categorical4
Text2

Dataset

Description환경신기술(신기술인증, 기술검증) 분야별 보유기업, 기술명칭, 기술보유자명, 인증번호, 검증번호 정보 제공
URLhttps://www.data.go.kr/data/15052617/fileData.do

Alerts

구분 is highly overall correlated with 상태High correlation
분야소분류 is highly overall correlated with 분야대분류High correlation
상태 is highly overall correlated with 구분High correlation
분야대분류 is highly overall correlated with 분야소분류High correlation
순번 is highly overall correlated with 인증번호 and 1 other fieldsHigh correlation
인증번호 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
검증번호 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
기술명 has 12 (1.5%) missing valuesMissing
인증번호 has 12 (1.5%) missing valuesMissing
검증번호 has 358 (46.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:13:13.904902
Analysis finished2023-12-12 20:13:16.330213
Duration2.43 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
2023-12-13T05:13:16.443042image/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
2023-12-13T05:13:16.674713image/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 row신기술인증
2nd row신기술인증
3rd row신기술인증
4th row신기술인증
5th row신기술인증

Common Values

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

Length

2023-12-13T05:13:16.903050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:17.043317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신기술인증 502
64.5%
기술검증 276
35.5%

상태
Categorical

HIGH CORRELATION 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인증서발급 502
64.5%
검증서발급 276
35.5%

Length

2023-12-13T05:13:17.165976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:17.626966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인증서발급 502
64.5%
검증서발급 276
35.5%

분야소분류
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 row기타
2nd row관거
3rd row건설폐기물
4th row관거
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

2023-12-13T05:13:17.761120image/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%

분야대분류
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 row기타
2nd row기타
3rd row폐기물
4th row기타
5th row수질

Common Values

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

Length

2023-12-13T05:13:17.906064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:18.021032image/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%

기술보유자
Text

Distinct609
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2023-12-13T05:13:18.259355image/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 row주식회사 누보켐/주식회사 유진컨스텍
2nd row주식회사 모악엔지니어링/주식회사 오성이엔씨/주식회사 한국광기술
3rd row(주)모악환경산업
4th row주식회사 엔탑이앤지
5th row경상북도 경주시/금호건설(주)
ValueCountFrequency (%)
주식회사 18
 
2.1%
산학협력단 8
 
0.9%
현대건설(주 6
 
0.7%
삼성엔지니어링(주 6
 
0.7%
주)대우건설 5
 
0.6%
㈜환경시설관리공사 5
 
0.6%
5
 
0.6%
주)한화건설 4
 
0.5%
주)뉴보텍 4
 
0.5%
주)지앤지테크놀러지 4
 
0.5%
Other values (609) 797
92.5%
2023-12-13T05:13:18.786661image/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%
t 3
10.3%
n 3
10.3%
e 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 (%)
2 1
50.0%
1 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%
L 7
 
7.0%
o 7
 
7.0%
N 7
 
7.0%
d 6
 
6.0%
T 6
 
6.0%
C 4
 
4.0%
i 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%
2 1
 
< 0.1%
1 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%
L 7
 
0.2%
o 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
2023-12-13T05:13:19.212874image/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 row고압 물 분사 장치를 이용한 폼드 배수성 아스팔트 혼합물제조 기술
2nd row화재 안전형 하수관로 비굴착 광경화 전체보수 공법(FS-UV 공법)
3rd row낙하 충격과 풍력을 이용한 순환골재의 유기이물질 제거 기술
4th row러버히터가 설치된 패커를 이용한 하수관로 비굴착 부분보수공법
5th row하수 분할유입, 조대기포 교반 및 양방향 방류장치를 이용한 연속 회분식 하수고도처리기술
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%
하수 49
 
0.7%
이용하여 49
 
0.7%
Other values (3119) 5994
82.3%
2023-12-13T05:13:19.846041image/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%
수 663
 
1.9%
술 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%
수 663
 
2.6%
술 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%
o 81
 
7.2%
t 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%
D 46
 
4.0%
F 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%
6 2
 
1.7%
5 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%
수 663
 
2.6%
술 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%
o 81
 
3.6%
t 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%
Geometric Shapes 1
 
< 0.1%
CJK 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%
수 663
 
2.6%
술 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%
γ 1
 
1.3%
₂ 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%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%
CJK
ValueCountFrequency (%)
前 1
100.0%

인증번호
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
2023-12-13T05:13:20.046426image/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
MonotonicityDecreasing
2023-12-13T05:13:20.210520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
440 2
 
0.3%
463 2
 
0.3%
460 2
 
0.3%
458 2
 
0.3%
455 2
 
0.3%
453 2
 
0.3%
448 2
 
0.3%
445 2
 
0.3%
442 2
 
0.3%
441 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%

검증번호
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
2023-12-13T05:13:20.366659image/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
MonotonicityNot monotonic
2023-12-13T05:13:20.569149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
168 2
 
0.3%
180 2
 
0.3%
170 2
 
0.3%
174 2
 
0.3%
198 2
 
0.3%
165 2
 
0.3%
172 2
 
0.3%
195 2
 
0.3%
192 2
 
0.3%
171 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%

Interactions

2023-12-13T05:13:15.517379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:14.784272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.157623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.646155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:14.915633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.285699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.757658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.035465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:15.405934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:13:20.703859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분상태분야소분류분야대분류인증번호검증번호
순번1.0000.2880.2880.4150.3260.9810.971
구분0.2881.0001.0000.3870.3860.2300.529
상태0.2881.0001.0000.3870.3860.2300.529
분야소분류0.4150.3870.3871.0000.9980.4050.522
분야대분류0.3260.3860.3860.9981.0000.3320.444
인증번호0.9810.2300.2300.4050.3321.0000.969
검증번호0.9710.5290.5290.5220.4440.9691.000
2023-12-13T05:13:20.859749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분분야소분류상태분야대분류
구분1.0000.3020.9970.258
분야소분류0.3021.0000.3020.936
상태0.9970.3021.0000.258
분야대분류0.2580.9360.2581.000
2023-12-13T05:13:21.006383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번인증번호검증번호구분상태분야소분류분야대분류
순번1.000-1.000-0.9860.2200.2200.1750.199
인증번호-1.0001.0000.9870.1750.1750.1700.203
검증번호-0.9860.9871.0000.4040.4040.2460.278
구분0.2200.1750.4041.0000.9970.3020.258
상태0.2200.1750.4040.9971.0000.3020.258
분야소분류0.1750.1700.2460.3020.3021.0000.936
분야대분류0.1990.2030.2780.2580.2580.9361.000

Missing values

2023-12-13T05:13:15.911576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:13:16.084749image/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.
2023-12-13T05:13:16.250850image/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

순번구분상태분야소분류분야대분류기술보유자기술명인증번호검증번호
01신기술인증인증서발급기타기타주식회사 누보켐/주식회사 유진컨스텍고압 물 분사 장치를 이용한 폼드 배수성 아스팔트 혼합물제조 기술619<NA>
12신기술인증인증서발급관거기타주식회사 모악엔지니어링/주식회사 오성이엔씨/주식회사 한국광기술화재 안전형 하수관로 비굴착 광경화 전체보수 공법(FS-UV 공법)618<NA>
23신기술인증인증서발급건설폐기물폐기물(주)모악환경산업낙하 충격과 풍력을 이용한 순환골재의 유기이물질 제거 기술617<NA>
34신기술인증인증서발급관거기타주식회사 엔탑이앤지러버히터가 설치된 패커를 이용한 하수관로 비굴착 부분보수공법616<NA>
45신기술인증인증서발급하수수질경상북도 경주시/금호건설(주)하수 분할유입, 조대기포 교반 및 양방향 방류장치를 이용한 연속 회분식 하수고도처리기술615269
56기술검증검증서발급하수수질경상북도 경주시/금호건설(주)하수 분할유입, 조대기포 교반 및 양방향 방류장치를 이용한 연속 회분식 하수고도처리기술615269
67신기술인증인증서발급건설폐기물폐기물(주)홍명산업/(주)두승/성산환경(주)다수의 교차 회전 날개가 장착된 8각 2축 박리크러셔를 건설폐기물 중간처리 공정에 적용하여 콘크리트용 골재의 품질향상 기술614<NA>
78신기술인증인증서발급건설폐기물폐기물(주)씨.에스/류기남/(주)부호산업개발/신구대학교 산학협력단균등량 공급제어 장치를 이용하여 도로 입도조정 기층용 순환골재를 생산하는 기술613<NA>
89신기술인증인증서발급가연성폐기물폐기물아세아시멘트(주)시멘트 하소 공정 중 폐플라스틱류 보조연료 풍력 선별 전처리 기술612<NA>
910신기술인증인증서발급건설폐기물폐기물㈜글로벌환경/신구대학교 산학협력단/자원개발㈜/(유)전일환경전기 전도도 센서와 진동 주파수 제어시스템이 적용된 선별 스크린을 이용한 성토용 순환토사 생산기술611<NA>
순번구분상태분야소분류분야대분류기술보유자기술명인증번호검증번호
768769기술검증검증서발급가연성폐기물폐기물(주)콘테크<NA><NA>13
769770기술검증검증서발급하수수질(주)퍼텍코리아<NA><NA>21
770771기술검증검증서발급기타폐기물(주)그린랜드환경<NA><NA>27
771772기술검증검증서발급가연성폐기물폐기물(주)켄텍오파스<NA><NA>41
772773기술검증검증서발급기타폐기물GS건설(주)<NA><NA>42
773774기술검증검증서발급하수수질(주)대우건설<NA><NA>47
774775기술검증검증서발급기타수질(주)보고환경<NA><NA>49
775776기술검증검증서발급하수수질(주)태영건설/씨아이바이오텍(주)<NA><NA>55
776777기술검증검증서발급하수수질(주)한미엔텍<NA><NA>67
777778기술검증검증서발급가연성폐기물폐기물바이오컨(주)<NA><NA>72