Overview

Dataset statistics

Number of variables18
Number of observations2405
Missing cells11637
Missing cells (%)26.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory368.9 KiB
Average record size in memory157.1 B

Variable types

Text3
Numeric5
Categorical9
Unsupported1

Alerts

중점관리대상물질 is highly overall correlated with 작업환경유해인자여부High correlation
유독물질 is highly overall correlated with 작업환경유해인자여부High correlation
등록대상기존화학물질 is highly overall correlated with 작업환경유해인자여부High correlation
특수건강진단대상물질여부 is highly overall correlated with 노출기준(TWA_ppm) and 3 other fieldsHigh correlation
작업환경유해인자여부 is highly overall correlated with 하위규정수량(톤) and 12 other fieldsHigh correlation
배출및이동량조사대상물질여부 is highly overall correlated with 노출기준(STEL_ppm) and 2 other fieldsHigh correlation
제한물질 is highly overall correlated with 최고노출기준(C_ppm) and 1 other fieldsHigh correlation
금지물질 is highly overall correlated with 최고노출기준(C_ppm) and 1 other fieldsHigh correlation
사고대비물질 is highly overall correlated with 하위규정수량(톤) and 2 other fieldsHigh correlation
하위규정수량(톤) is highly overall correlated with 상위규정수량(톤) and 2 other fieldsHigh correlation
상위규정수량(톤) is highly overall correlated with 하위규정수량(톤) and 2 other fieldsHigh correlation
노출기준(TWA_ppm) is highly overall correlated with 노출기준(STEL_ppm) and 2 other fieldsHigh correlation
노출기준(STEL_ppm) is highly overall correlated with 노출기준(TWA_ppm) and 3 other fieldsHigh correlation
최고노출기준(C_ppm) is highly overall correlated with 특수건강진단대상물질여부 and 4 other fieldsHigh correlation
특수건강진단대상물질여부 is highly imbalanced (84.8%)Imbalance
작업환경유해인자여부 is highly imbalanced (60.0%)Imbalance
배출및이동량조사대상물질여부 is highly imbalanced (59.2%)Imbalance
제한물질 is highly imbalanced (91.7%)Imbalance
금지물질 is highly imbalanced (82.7%)Imbalance
사고대비물질 is highly imbalanced (75.6%)Imbalance
국문 has 364 (15.1%) missing valuesMissing
하위규정수량(톤) has 1165 (48.4%) missing valuesMissing
상위규정수량(톤) has 1243 (51.7%) missing valuesMissing
노출기준(TWA_ppm) has 1834 (76.3%) missing valuesMissing
노출기준(STEL_ppm) has 2256 (93.8%) missing valuesMissing
최고노출기준(C_ppm) has 2370 (98.5%) missing valuesMissing
Unnamed: 17 has 2405 (100.0%) missing valuesMissing
고유(CAS)번호 has unique valuesUnique
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 21:07:59.178417
Analysis finished2024-01-09 21:08:02.839061
Duration3.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유(CAS)번호
Text

UNIQUE 

Distinct2405
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
2024-01-10T06:08:03.068856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.13763
Min length8

Characters and Unicode

Total characters24381
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2405 ?
Unique (%)100.0%

Sample

1st row 1313-60-6
2nd row 7722-84-1
3rd row 124-43-6
4th row 13516-27-3
5th row 108173-90-6
ValueCountFrequency (%)
1313-60-6 1
 
< 0.1%
12626-81-2 1
 
< 0.1%
12737-98-3 1
 
< 0.1%
12765-51-4 1
 
< 0.1%
13010-47-4 1
 
< 0.1%
13423-61-5 1
 
< 0.1%
13446-73-6 1
 
< 0.1%
13453-15-1 1
 
< 0.1%
13453-35-5 1
 
< 0.1%
13453-66-2 1
 
< 0.1%
Other values (2395) 2395
99.6%
2024-01-10T06:08:03.474520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4810
19.7%
1 2479
10.2%
2405
9.9%
0 1776
 
7.3%
2 1748
 
7.2%
7 1681
 
6.9%
3 1676
 
6.9%
5 1649
 
6.8%
4 1609
 
6.6%
6 1571
 
6.4%
Other values (2) 2977
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17166
70.4%
Dash Punctuation 4810
 
19.7%
Space Separator 2405
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2479
14.4%
0 1776
10.3%
2 1748
10.2%
7 1681
9.8%
3 1676
9.8%
5 1649
9.6%
4 1609
9.4%
6 1571
9.2%
8 1517
8.8%
9 1460
8.5%
Dash Punctuation
ValueCountFrequency (%)
- 4810
100.0%
Space Separator
ValueCountFrequency (%)
2405
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4810
19.7%
1 2479
10.2%
2405
9.9%
0 1776
 
7.3%
2 1748
 
7.2%
7 1681
 
6.9%
3 1676
 
6.9%
5 1649
 
6.8%
4 1609
 
6.6%
6 1571
 
6.4%
Other values (2) 2977
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4810
19.7%
1 2479
10.2%
2405
9.9%
0 1776
 
7.3%
2 1748
 
7.2%
7 1681
 
6.9%
3 1676
 
6.9%
5 1649
 
6.8%
4 1609
 
6.6%
6 1571
 
6.4%
Other values (2) 2977
12.2%

영문
Text

Distinct2375
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
2024-01-10T06:08:03.963791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length327
Median length159
Mean length30.093971
Min length3

Characters and Unicode

Total characters72376
Distinct characters98
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2350 ?
Unique (%)97.7%

Sample

1st rowSodium,peroxide
2nd rowHydrogen,peroxide
3rd rowUrea,hydrogen,peroxide
4th rowIminoctadine
5th rowGuazatine
ValueCountFrequency (%)
acid 85
 
2.4%
1:1 70
 
2.0%
salt 68
 
1.9%
with 62
 
1.8%
phenol 24
 
0.7%
and 15
 
0.4%
ammonium 14
 
0.4%
sodium 14
 
0.4%
nickel 14
 
0.4%
chloride 13
 
0.4%
Other values (2670) 3157
89.3%
2024-01-10T06:08:04.324601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6122
 
8.5%
o 4666
 
6.4%
i 4543
 
6.3%
l 4191
 
5.8%
a 3929
 
5.4%
t 3820
 
5.3%
n 3769
 
5.2%
, 3737
 
5.2%
- 3384
 
4.7%
h 3103
 
4.3%
Other values (88) 31112
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53675
74.2%
Decimal Number 4336
 
6.0%
Other Punctuation 4169
 
5.8%
Uppercase Letter 3521
 
4.9%
Dash Punctuation 3384
 
4.7%
Space Separator 1136
 
1.6%
Open Punctuation 1048
 
1.4%
Close Punctuation 1046
 
1.4%
Math Symbol 46
 
0.1%
Other Number 8
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6122
11.4%
o 4666
 
8.7%
i 4543
 
8.5%
l 4191
 
7.8%
a 3929
 
7.3%
t 3820
 
7.1%
n 3769
 
7.0%
h 3103
 
5.8%
r 2931
 
5.5%
y 2728
 
5.1%
Other values (24) 13873
25.8%
Uppercase Letter
ValueCountFrequency (%)
N 366
10.4%
C 359
10.2%
D 355
10.1%
T 319
 
9.1%
P 247
 
7.0%
B 219
 
6.2%
M 217
 
6.2%
H 194
 
5.5%
A 194
 
5.5%
I 170
 
4.8%
Other values (16) 881
25.0%
Other Punctuation
ValueCountFrequency (%)
, 3737
89.6%
. 152
 
3.6%
: 115
 
2.8%
' 71
 
1.7%
; 66
 
1.6%
* 11
 
0.3%
/ 10
 
0.2%
& 3
 
0.1%
# 2
 
< 0.1%
′ 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1259
29.0%
2 987
22.8%
4 628
14.5%
3 592
13.7%
5 303
 
7.0%
6 259
 
6.0%
7 107
 
2.5%
8 88
 
2.0%
0 57
 
1.3%
9 56
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 24
52.2%
= 15
32.6%
~ 6
 
13.0%
∼ 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 771
73.7%
] 272
 
26.0%
} 3
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 771
73.6%
[ 274
 
26.1%
{ 3
 
0.3%
Other Number
ValueCountFrequency (%)
¹ 4
50.0%
² 2
25.0%
³ 2
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3384
100.0%
Space Separator
ValueCountFrequency (%)
1136
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 57135
78.9%
Common 15179
 
21.0%
Greek 62
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6122
 
10.7%
o 4666
 
8.2%
i 4543
 
8.0%
l 4191
 
7.3%
a 3929
 
6.9%
t 3820
 
6.7%
n 3769
 
6.6%
h 3103
 
5.4%
r 2931
 
5.1%
y 2728
 
4.8%
Other values (42) 17333
30.3%
Common
ValueCountFrequency (%)
, 3737
24.6%
- 3384
22.3%
1 1259
 
8.3%
1136
 
7.5%
2 987
 
6.5%
) 771
 
5.1%
( 771
 
5.1%
4 628
 
4.1%
3 592
 
3.9%
5 303
 
2.0%
Other values (27) 1611
10.6%
Greek
ValueCountFrequency (%)
α 26
41.9%
κ 11
17.7%
ω 9
 
14.5%
η 5
 
8.1%
β 5
 
8.1%
λ 3
 
4.8%
μ 1
 
1.6%
δ 1
 
1.6%
Ο 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72301
99.9%
None 70
 
0.1%
Punctuation 3
 
< 0.1%
Number Forms 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6122
 
8.5%
o 4666
 
6.5%
i 4543
 
6.3%
l 4191
 
5.8%
a 3929
 
5.4%
t 3820
 
5.3%
n 3769
 
5.2%
, 3737
 
5.2%
- 3384
 
4.7%
h 3103
 
4.3%
Other values (72) 31037
42.9%
None
ValueCountFrequency (%)
α 26
37.1%
κ 11
15.7%
ω 9
 
12.9%
η 5
 
7.1%
β 5
 
7.1%
¹ 4
 
5.7%
λ 3
 
4.3%
² 2
 
2.9%
³ 2
 
2.9%
μ 1
 
1.4%
Other values (2) 2
 
2.9%
Punctuation
ValueCountFrequency (%)
′ 2
66.7%
’ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

국문
Text

MISSING 

Distinct2019
Distinct (%)98.9%
Missing364
Missing (%)15.1%
Memory size18.9 KiB
2024-01-10T06:08:04.620994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length168
Median length100
Mean length14.546791
Min length1

Characters and Unicode

Total characters29690
Distinct characters409
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2005 ?
Unique (%)98.2%

Sample

1st row과산화나트륨
2nd row과산화수소
3rd row과산화,우레아
4th row이민옥타딘
5th row글루타르알데하이드
ValueCountFrequency (%)
1:1 32
 
1.3%
염 24
 
1.0%
트리페닐술포늄과 8
 
0.3%
1,1,1-트리플루오로-n-[(트리플루오로메틸)술포닐]메탄술폰아미드의 8
 
0.3%
노닐페놀류 7
 
0.3%
염화 7
 
0.3%
반응생성물 7
 
0.3%
2-프로펜산 6
 
0.3%
염(1:1 6
 
0.3%
칼륨 6
 
0.3%
Other values (2171) 2278
95.4%
2024-01-10T06:08:05.052132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 2169
 
7.3%
- 2146
 
7.2%
이 1602
 
5.4%
로 1048
 
3.5%
트 884
 
3.0%
1 728
 
2.5%
틸 705
 
2.4%
아 681
 
2.3%
2 613
 
2.1%
메 598
 
2.0%
Other values (399) 18516
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20331
68.5%
Decimal Number 2427
 
8.2%
Other Punctuation 2396
 
8.1%
Dash Punctuation 2146
 
7.2%
Close Punctuation 679
 
2.3%
Open Punctuation 677
 
2.3%
Uppercase Letter 492
 
1.7%
Space Separator 348
 
1.2%
Lowercase Letter 154
 
0.5%
Math Symbol 33
 
0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1602
 
7.9%
로 1048
 
5.2%
트 884
 
4.3%
틸 705
 
3.5%
아 681
 
3.3%
메 598
 
2.9%
드 513
 
2.5%
산 455
 
2.2%
다 414
 
2.0%
라 405
 
2.0%
Other values (322) 13026
64.1%
Lowercase Letter
ValueCountFrequency (%)
k 21
13.6%
α 18
 
11.7%
t 12
 
7.8%
a 12
 
7.8%
κ 10
 
6.5%
d 8
 
5.2%
r 8
 
5.2%
p 6
 
3.9%
e 6
 
3.9%
b 5
 
3.2%
Other values (17) 48
31.2%
Uppercase Letter
ValueCountFrequency (%)
N 194
39.4%
I 48
 
9.8%
C 46
 
9.3%
H 44
 
8.9%
O 38
 
7.7%
S 32
 
6.5%
R 17
 
3.5%
E 13
 
2.6%
P 13
 
2.6%
T 10
 
2.0%
Other values (9) 37
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 728
30.0%
2 613
25.3%
3 345
14.2%
4 344
14.2%
5 139
 
5.7%
6 86
 
3.5%
7 62
 
2.6%
8 54
 
2.2%
9 34
 
1.4%
0 22
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 2169
90.5%
. 70
 
2.9%
: 69
 
2.9%
' 56
 
2.3%
/ 10
 
0.4%
; 9
 
0.4%
* 9
 
0.4%
# 2
 
0.1%
& 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 16
48.5%
= 10
30.3%
~ 7
21.2%
Close Punctuation
ValueCountFrequency (%)
) 524
77.2%
] 155
 
22.8%
Open Punctuation
ValueCountFrequency (%)
( 521
77.0%
[ 156
 
23.0%
Dash Punctuation
ValueCountFrequency (%)
- 2146
100.0%
Space Separator
ValueCountFrequency (%)
348
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20331
68.5%
Common 8712
29.3%
Latin 601
 
2.0%
Greek 46
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1602
 
7.9%
로 1048
 
5.2%
트 884
 
4.3%
틸 705
 
3.5%
아 681
 
3.3%
메 598
 
2.9%
드 513
 
2.5%
산 455
 
2.2%
다 414
 
2.0%
라 405
 
2.0%
Other values (322) 13026
64.1%
Latin
ValueCountFrequency (%)
N 194
32.3%
I 48
 
8.0%
C 46
 
7.7%
H 44
 
7.3%
O 38
 
6.3%
S 32
 
5.3%
k 21
 
3.5%
R 17
 
2.8%
E 13
 
2.2%
P 13
 
2.2%
Other values (29) 135
22.5%
Common
ValueCountFrequency (%)
, 2169
24.9%
- 2146
24.6%
1 728
 
8.4%
2 613
 
7.0%
) 524
 
6.0%
( 521
 
6.0%
348
 
4.0%
3 345
 
4.0%
4 344
 
3.9%
[ 156
 
1.8%
Other values (20) 818
 
9.4%
Greek
ValueCountFrequency (%)
α 18
39.1%
κ 10
21.7%
η 5
 
10.9%
β 5
 
10.9%
ω 3
 
6.5%
λ 3
 
6.5%
μ 1
 
2.2%
Ο 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20331
68.5%
ASCII 9310
31.4%
None 46
 
0.2%
Punctuation 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 2169
23.3%
- 2146
23.1%
1 728
 
7.8%
2 613
 
6.6%
) 524
 
5.6%
( 521
 
5.6%
348
 
3.7%
3 345
 
3.7%
4 344
 
3.7%
N 194
 
2.1%
Other values (57) 1378
14.8%
Hangul
ValueCountFrequency (%)
이 1602
 
7.9%
로 1048
 
5.2%
트 884
 
4.3%
틸 705
 
3.5%
아 681
 
3.3%
메 598
 
2.9%
드 513
 
2.5%
산 455
 
2.2%
다 414
 
2.0%
라 405
 
2.0%
Other values (322) 13026
64.1%
None
ValueCountFrequency (%)
α 18
39.1%
κ 10
21.7%
η 5
 
10.9%
β 5
 
10.9%
ω 3
 
6.5%
λ 3
 
6.5%
μ 1
 
2.2%
Ο 1
 
2.2%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

하위규정수량(톤)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)1.0%
Missing1165
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean14.901129
Minimum0.2
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.3 KiB
2024-01-10T06:08:05.166846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1
Q15
median20
Q320
95-th percentile40
Maximum40
Range39.8
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.9735776
Coefficient of variation (CV)0.66931691
Kurtosis0.010582272
Mean14.901129
Median Absolute Deviation (MAD)0
Skewness0.36713963
Sum18477.4
Variance99.472251
MonotonicityNot monotonic
2024-01-10T06:08:05.275645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20.0 701
29.1%
5.0 280
 
11.6%
2.0 93
 
3.9%
40.0 69
 
2.9%
1.0 53
 
2.2%
0.3 20
 
0.8%
0.2 11
 
0.5%
4.0 5
 
0.2%
0.4 4
 
0.2%
8.0 2
 
0.1%
Other values (2) 2
 
0.1%
(Missing) 1165
48.4%
ValueCountFrequency (%)
0.2 11
 
0.5%
0.3 20
 
0.8%
0.4 4
 
0.2%
0.6 1
 
< 0.1%
1.0 53
 
2.2%
2.0 93
 
3.9%
4.0 5
 
0.2%
5.0 280
11.6%
8.0 2
 
0.1%
12.0 1
 
< 0.1%
ValueCountFrequency (%)
40.0 69
 
2.9%
20.0 701
29.1%
12.0 1
 
< 0.1%
8.0 2
 
0.1%
5.0 280
 
11.6%
4.0 5
 
0.2%
2.0 93
 
3.9%
1.0 53
 
2.2%
0.6 1
 
< 0.1%
0.4 4
 
0.2%

상위규정수량(톤)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)1.1%
Missing1243
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean315.87952
Minimum1
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.3 KiB
2024-01-10T06:08:05.380805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20
Q1200
median400
Q3400
95-th percentile500
Maximum500
Range499
Interquartile range (IQR)200

Descriptive statistics

Standard deviation158.92043
Coefficient of variation (CV)0.50310458
Kurtosis-0.96836735
Mean315.87952
Median Absolute Deviation (MAD)100
Skewness-0.58074447
Sum367052
Variance25255.704
MonotonicityNot monotonic
2024-01-10T06:08:05.478174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
400.0 465
 
19.3%
200.0 267
 
11.1%
500.0 238
 
9.9%
20.0 66
 
2.7%
100.0 60
 
2.5%
1.5 20
 
0.8%
40.0 14
 
0.6%
1.0 11
 
0.5%
50.0 9
 
0.4%
2.0 4
 
0.2%
Other values (3) 8
 
0.3%
(Missing) 1243
51.7%
ValueCountFrequency (%)
1.0 11
 
0.5%
1.5 20
 
0.8%
2.0 4
 
0.2%
3.0 1
 
< 0.1%
10.0 3
 
0.1%
20.0 66
2.7%
40.0 14
 
0.6%
50.0 9
 
0.4%
60.0 4
 
0.2%
100.0 60
2.5%
ValueCountFrequency (%)
500.0 238
9.9%
400.0 465
19.3%
200.0 267
11.1%
100.0 60
 
2.5%
60.0 4
 
0.2%
50.0 9
 
0.4%
40.0 14
 
0.6%
20.0 66
 
2.7%
10.0 3
 
0.1%
3.0 1
 
< 0.1%

특수건강진단대상물질여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
<NA>
2235 
6개월 이내
 
162
3개월 이내
 
4
1개월 이내
 
2
2개월 이내
 
1

Length

Max length7
Median length4
Mean length4.1417879
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2235
92.9%
6개월 이내 162
 
6.7%
3개월 이내 4
 
0.2%
1개월 이내 2
 
0.1%
2개월 이내 1
 
< 0.1%
12개월 이내 1
 
< 0.1%

Length

2024-01-10T06:08:05.587416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:05.731242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2235
86.8%
이내 170
 
6.6%
6개월 162
 
6.3%
3개월 4
 
0.2%
1개월 2
 
0.1%
2개월 1
 
< 0.1%
12개월 1
 
< 0.1%

작업환경유해인자여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
<NA>
2214 
1
 
191

Length

Max length4
Median length4
Mean length3.7617464
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2214
92.1%
1 191
 
7.9%

Length

2024-01-10T06:08:05.830538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:05.914153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2214
92.1%
1 191
 
7.9%

배출및이동량조사대상물질여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
<NA>
2017 
1.0이상 - 2
246 
0.1이상 - 2
 
129
0.1이상 - 1
 
13

Length

Max length9
Median length4
Mean length4.8066528
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0이상 - 2
2nd row1.0이상 - 2
3rd row<NA>
4th row1.0이상 - 2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2017
83.9%
1.0이상 - 2 246
 
10.2%
0.1이상 - 2 129
 
5.4%
0.1이상 - 1 13
 
0.5%

Length

2024-01-10T06:08:06.001134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:06.115179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2017
63.4%
388
 
12.2%
2 375
 
11.8%
1.0이상 246
 
7.7%
0.1이상 142
 
4.5%
1 13
 
0.4%

등록대상기존화학물질
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
1887 
1
518 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 1887
78.5%
1 518
 
21.5%

Length

2024-01-10T06:08:06.225267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:06.305260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1887
78.5%
1 518
 
21.5%

노출기준(TWA_ppm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct197
Distinct (%)34.5%
Missing1834
Missing (%)76.3%
Infinite0
Infinite (%)0.0%
Mean66.021837
Minimum0.001
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.3 KiB
2024-01-10T06:08:06.407459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.005
Q10.0905
median1
Q310
95-th percentile400
Maximum5000
Range4999.999
Interquartile range (IQR)9.9095

Descriptive statistics

Standard deviation273.02811
Coefficient of variation (CV)4.1354213
Kurtosis189.63453
Mean66.021837
Median Absolute Deviation (MAD)0.993
Skewness11.499822
Sum37698.469
Variance74544.35
MonotonicityNot monotonic
2024-01-10T06:08:06.540313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 31
 
1.3%
2.0 31
 
1.3%
50.0 30
 
1.2%
5.0 28
 
1.2%
1.0 25
 
1.0%
0.1 24
 
1.0%
0.5 21
 
0.9%
100.0 17
 
0.7%
200.0 15
 
0.6%
25.0 13
 
0.5%
Other values (187) 336
 
14.0%
(Missing) 1834
76.3%
ValueCountFrequency (%)
0.001 10
0.4%
0.002 4
 
0.2%
0.003 3
 
0.1%
0.004 3
 
0.1%
0.005 13
0.5%
0.006 5
 
0.2%
0.007 6
0.2%
0.008 6
0.2%
0.009 2
 
0.1%
0.01 9
0.4%
ValueCountFrequency (%)
5000.0 1
 
< 0.1%
1000.0 13
0.5%
800.0 2
 
0.1%
600.0 4
 
0.2%
500.0 8
0.3%
400.0 5
 
0.2%
350.0 1
 
< 0.1%
300.0 4
 
0.2%
250.0 1
 
< 0.1%
200.0 15
0.6%

노출기준(STEL_ppm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)45.0%
Missing2256
Missing (%)93.8%
Infinite0
Infinite (%)0.0%
Mean346.07978
Minimum0.001
Maximum30000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.3 KiB
2024-01-10T06:08:06.655742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.0422
Q11.5
median15
Q3150
95-th percentile1000
Maximum30000
Range29999.999
Interquartile range (IQR)148.5

Descriptive statistics

Standard deviation2461.9274
Coefficient of variation (CV)7.1137569
Kurtosis145.04529
Mean346.07978
Median Absolute Deviation (MAD)14.941
Skewness11.96839
Sum51565.887
Variance6061086.5
MonotonicityNot monotonic
2024-01-10T06:08:06.779031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.0 12
 
0.5%
150.0 11
 
0.5%
100.0 8
 
0.3%
10.0 7
 
0.3%
250.0 6
 
0.2%
0.3 5
 
0.2%
75.0 5
 
0.2%
750.0 4
 
0.2%
4.0 4
 
0.2%
1000.0 4
 
0.2%
Other values (57) 83
 
3.5%
(Missing) 2256
93.8%
ValueCountFrequency (%)
0.001 1
< 0.1%
0.015 1
< 0.1%
0.018 1
< 0.1%
0.02 2
0.1%
0.027 1
< 0.1%
0.03 1
< 0.1%
0.037 1
< 0.1%
0.05 1
< 0.1%
0.059 1
< 0.1%
0.062 1
< 0.1%
ValueCountFrequency (%)
30000.0 1
 
< 0.1%
1250.0 4
0.2%
1000.0 4
0.2%
750.0 4
0.2%
500.0 3
0.1%
450.0 1
 
< 0.1%
400.0 1
 
< 0.1%
375.0 1
 
< 0.1%
310.0 1
 
< 0.1%
300.0 1
 
< 0.1%

최고노출기준(C_ppm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)57.1%
Missing2370
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean31.667571
Minimum0.01
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.3 KiB
2024-01-10T06:08:06.891353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.0159
Q10.1
median0.872
Q33.85
95-th percentile29.3173
Maximum1000
Range999.99
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation168.66628
Coefficient of variation (CV)5.3261513
Kurtosis34.842343
Mean31.667571
Median Absolute Deviation (MAD)0.822
Skewness5.8970359
Sum1108.365
Variance28448.312
MonotonicityNot monotonic
2024-01-10T06:08:06.999381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1.0 5
 
0.2%
5.0 4
 
0.2%
0.05 4
 
0.2%
0.1 4
 
0.2%
0.2 2
 
0.1%
4.7 2
 
0.1%
0.018 1
 
< 0.1%
25.0 1
 
< 0.1%
1000.0 1
 
< 0.1%
0.531 1
 
< 0.1%
Other values (10) 10
 
0.4%
(Missing) 2370
98.5%
ValueCountFrequency (%)
0.01 1
 
< 0.1%
0.011 1
 
< 0.1%
0.018 1
 
< 0.1%
0.05 4
0.2%
0.1 4
0.2%
0.109 1
 
< 0.1%
0.2 2
0.1%
0.3 1
 
< 0.1%
0.5 1
 
< 0.1%
0.531 1
 
< 0.1%
ValueCountFrequency (%)
1000.0 1
 
< 0.1%
39.391 1
 
< 0.1%
25.0 1
 
< 0.1%
5.0 4
0.2%
4.7 2
 
0.1%
3.0 1
 
< 0.1%
2.0 1
 
< 0.1%
1.223 1
 
< 0.1%
1.0 5
0.2%
0.872 1
 
< 0.1%

유독물질
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
1224 
1
1181 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 1224
50.9%
1 1181
49.1%

Length

2024-01-10T06:08:07.103646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:07.196162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1224
50.9%
1 1181
49.1%

제한물질
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
2380 
1
 
25

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2380
99.0%
1 25
 
1.0%

Length

2024-01-10T06:08:07.305250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:07.388281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2380
99.0%
1 25
 
1.0%

금지물질
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
2343 
1
 
62

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2343
97.4%
1 62
 
2.6%

Length

2024-01-10T06:08:07.469526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:07.550900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2343
97.4%
1 62
 
2.6%

사고대비물질
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
2308 
1
 
97

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2308
96.0%
1 97
 
4.0%

Length

2024-01-10T06:08:07.657683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:07.737537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2308
96.0%
1 97
 
4.0%

중점관리대상물질
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.9 KiB
0
1574 
1
831 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1574
65.4%
1 831
34.6%

Length

2024-01-10T06:08:07.819140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:07.903791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1574
65.4%
1 831
34.6%

Unnamed: 17
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2405
Missing (%)100.0%
Memory size21.3 KiB

Interactions

2024-01-10T06:08:01.780816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.210798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.615503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.997517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.382044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.879117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.301274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.703666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.082912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.471420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.971515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.383267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.783118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.158606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.542984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:02.070463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.460247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.854242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.232050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.617543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:02.151425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.537090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:00.928655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.307389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:01.699422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:08:07.969063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하위규정수량(톤)상위규정수량(톤)특수건강진단대상물질여부배출및이동량조사대상물질여부등록대상기존화학물질노출기준(TWA_ppm)노출기준(STEL_ppm)최고노출기준(C_ppm)유독물질제한물질금지물질사고대비물질중점관리대상물질
하위규정수량(톤)1.0000.9500.1440.2050.1370.000NaNNaN0.2380.0520.0820.4310.203
상위규정수량(톤)0.9501.0000.0000.0000.1410.000NaNNaN0.2980.0750.0500.5360.059
특수건강진단대상물질여부0.1440.0001.0000.3490.145NaNNaNNaN0.0780.0000.0000.1320.192
배출및이동량조사대상물질여부0.2050.0000.3491.0000.0180.000NaNNaN0.2210.1400.0000.0680.274
등록대상기존화학물질0.1370.1410.1450.0181.0000.0450.0000.0000.2310.0730.1250.3130.036
노출기준(TWA_ppm)0.0000.000NaN0.0000.0451.0001.000NaN0.0670.0000.0000.0170.000
노출기준(STEL_ppm)NaNNaNNaNNaN0.0001.0001.000NaN0.0000.0000.0000.0000.000
최고노출기준(C_ppm)NaNNaNNaNNaN0.000NaNNaN1.0000.000NaNNaN0.0000.000
유독물질0.2380.2980.0780.2210.2310.0670.0000.0001.0000.0000.1620.0720.607
제한물질0.0520.0750.0000.1400.0730.0000.000NaN0.0001.0000.0000.0000.129
금지물질0.0820.0500.0000.0000.1250.0000.000NaN0.1620.0001.0000.0000.178
사고대비물질0.4310.5360.1320.0680.3130.0170.0000.0000.0720.0000.0001.0000.107
중점관리대상물질0.2030.0590.1920.2740.0360.0000.0000.0000.6070.1290.1780.1071.000
2024-01-10T06:08:08.119728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중점관리대상물질유독물질등록대상기존화학물질특수건강진단대상물질여부작업환경유해인자여부배출및이동량조사대상물질여부제한물질금지물질사고대비물질
중점관리대상물질1.0000.4150.0230.2331.0000.4440.0830.1140.068
유독물질0.4151.0000.1490.0941.0000.3620.0000.1030.046
등록대상기존화학물질0.0230.1491.0000.1751.0000.0290.0470.0790.203
특수건강진단대상물질여부0.2330.0940.1751.0001.0000.2760.0000.0000.159
작업환경유해인자여부1.0001.0001.0001.0001.0001.0001.0001.0001.000
배출및이동량조사대상물질여부0.4440.3620.0290.2761.0001.0000.2310.0000.112
제한물질0.0830.0000.0470.0001.0000.2311.0000.0000.000
금지물질0.1140.1030.0790.0001.0000.0000.0001.0000.000
사고대비물질0.0680.0460.2030.1591.0000.1120.0000.0001.000
2024-01-10T06:08:08.281978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하위규정수량(톤)상위규정수량(톤)노출기준(TWA_ppm)노출기준(STEL_ppm)최고노출기준(C_ppm)특수건강진단대상물질여부작업환경유해인자여부배출및이동량조사대상물질여부등록대상기존화학물질유독물질제한물질금지물질사고대비물질중점관리대상물질
하위규정수량(톤)1.0000.9010.1270.211-0.0140.0541.0000.1940.1680.2900.0630.1000.5240.248
상위규정수량(톤)0.9011.0000.1600.3380.0230.0001.0000.0000.1720.3630.0920.0610.6490.072
노출기준(TWA_ppm)0.1270.1601.0000.993NaN1.0001.0000.0000.0750.1100.0000.0000.0270.000
노출기준(STEL_ppm)0.2110.3380.9931.000NaN1.0001.0001.0000.0000.0000.0000.0000.0000.000
최고노출기준(C_ppm)-0.0140.023NaNNaN1.0001.0001.0001.0000.0000.0001.0001.0000.0000.000
특수건강진단대상물질여부0.0540.0001.0001.0001.0001.0001.0000.2760.1750.0940.0000.0000.1590.233
작업환경유해인자여부1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
배출및이동량조사대상물질여부0.1940.0000.0001.0001.0000.2761.0001.0000.0290.3620.2310.0000.1120.444
등록대상기존화학물질0.1680.1720.0750.0000.0000.1751.0000.0291.0000.1490.0470.0790.2030.023
유독물질0.2900.3630.1100.0000.0000.0941.0000.3620.1491.0000.0000.1030.0460.415
제한물질0.0630.0920.0000.0001.0000.0001.0000.2310.0470.0001.0000.0000.0000.083
금지물질0.1000.0610.0000.0001.0000.0001.0000.0000.0790.1030.0001.0000.0000.114
사고대비물질0.5240.6490.0270.0000.0000.1591.0000.1120.2030.0460.0000.0001.0000.068
중점관리대상물질0.2480.0720.0000.0000.0000.2331.0000.4440.0230.4150.0830.1140.0681.000

Missing values

2024-01-10T06:08:02.290851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:08:02.547491image/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.
2024-01-10T06:08:02.741531image/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

고유(CAS)번호영문국문하위규정수량(톤)상위규정수량(톤)특수건강진단대상물질여부작업환경유해인자여부배출및이동량조사대상물질여부등록대상기존화학물질노출기준(TWA_ppm)노출기준(STEL_ppm)최고노출기준(C_ppm)유독물질제한물질금지물질사고대비물질중점관리대상물질Unnamed: 17
01313-60-6Sodium,peroxide과산화나트륨5.0200.0<NA><NA>1.0이상 - 20<NA><NA><NA>10000<NA>
17722-84-1Hydrogen,peroxide과산화수소5.0200.0<NA>11.0이상 - 211.0<NA><NA>10010<NA>
2124-43-6Urea,hydrogen,peroxide과산화,우레아5.0200.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
313516-27-3Iminoctadine이민옥타딘5.0200.0<NA><NA>1.0이상 - 21<NA><NA><NA>10000<NA>
4108173-90-6Guazatine<NA>5.0200.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
5111-30-8Glutaraldehyde글루타르알데하이드5.0200.06개월 이내11.0이상 - 21<NA><NA>0.0510000<NA>
6106-90-1Glycidyl,acrylate글리시딜아크릴산20.0500.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
77440-23-5SODIUM나트륨0.42.0<NA><NA>1.0이상 - 21<NA><NA><NA>10010<NA>
8300-76-5Naled날레드20.0400.0<NA><NA>1.0이상 - 200.193<NA><NA>10000<NA>
91335-32-6Lead acetate<NA>20.0400.0<NA><NA><NA>0<NA><NA><NA>10001<NA>
고유(CAS)번호영문국문하위규정수량(톤)상위규정수량(톤)특수건강진단대상물질여부작업환경유해인자여부배출및이동량조사대상물질여부등록대상기존화학물질노출기준(TWA_ppm)노출기준(STEL_ppm)최고노출기준(C_ppm)유독물질제한물질금지물질사고대비물질중점관리대상물질Unnamed: 17
23951400865-78-2[(1,2,3,4,5-η)-N-Methyl-2,4-cyclopentadiene-1-ethanaminato(2-)-κN]bis(N-methylethanaminato)hafnium[(1,2,3,4,5-η)-N-메틸-2,4-사이클로펜다디엔-1-에탄아미나토(2-)-κN]비스(N-메틸에탄아미나토)하프늄20.0500.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
2396109-28-4(9Z)-N-[3-(Dimethylamino)propyl]-9-octadecenamide(9Z)-N-[3-(디메틸아미노)프로필]-9-옥타데센아미드20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
23971449104-34-0(4E)-5-Cyclohexyl-2,4-dimethyl-4-pentenal(4E)-5-사이클로헥실-2,4-디메틸-4-펜테날20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
239827607-77-8Trimethylsilyl trifluoromethanesulfonate트리플루오로메탄술폰산 트리메틸실릴20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
23991217886-69-5N-(Difluorophosphinyl)sulfamoyl fluoride, lithium salt (1:1)플루오르화 N-(디플루오로포스피닐)술파모일의 리튬염 (1:1)2.0100.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
2400802333-90-01-Decyl-4-methylpyridinium salt with 1,1,1-trifluoro-N-[(trifluoromethyl)sulfonyl]methanesulfonamide (1:1)1-데실-4-메틸피리디늄과 1,1,1-트리플루오로-N-[(트리플루오로메틸)술포닐]메탄술폰아미드의 염 (1:1)20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
240124948-66-11-Decen-4-yne1-데센-4-인20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
2402120307-06-4N,N,N-Tributyl-1-butanaminium, (T-4)-butyltriphenylborate(1-) (1:1)(T-4)-부틸트리페닐붕산(1-) N,N,N-트리부틸-1-부탄아미늄20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
2403219125-19-6N,N,N-Tributyl-1-butanaminium, (T-4)-butyltri-1-naphthalenylborate(1-) (1:1)(T-4)-부틸트리-1-나프탈레닐붕산(1-) N,N,N-트리부틸-1-부틸아미늄 (1:1)20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>
24041592-20-71-(Chloromethyl)-4-ethenylbenzene1-(클로로메틸)-4-에테닐벤젠20.0400.0<NA><NA><NA>0<NA><NA><NA>10000<NA>