Overview

Dataset statistics

Number of variables22
Number of observations10000
Missing cells19677
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 MiB
Average record size in memory193.0 B

Variable types

Categorical8
Text4
Numeric8
Unsupported1
Boolean1

Dataset

Description한국산업안전보건공단에서 실시 중인 민간위탁 사업 중 화학 분야(유해위험물질 취급현황)에 대한 데이터로
Author한국산업안전보건공단
URLhttps://www.data.go.kr/data/15091840/fileData.do

Alerts

대업종명 is highly imbalanced (93.1%)Imbalance
일일단위코드 is highly imbalanced (62.7%)Imbalance
최대단위코드 is highly imbalanced (55.6%)Imbalance
계산취급단위 is highly imbalanced (99.7%)Imbalance
계산저장단위 is highly imbalanced (99.7%)Imbalance
생산품 has 271 (2.7%) missing valuesMissing
물질구분코드 has 9745 (97.5%) missing valuesMissing
일일비중율 has 4809 (48.1%) missing valuesMissing
최대비중량 has 4840 (48.4%) missing valuesMissing
일일취급량 is highly skewed (γ1 = 28.7432093)Skewed
일일비중율 is highly skewed (γ1 = 68.52947484)Skewed
최대저장량 is highly skewed (γ1 = 41.55997358)Skewed
최대비중량 is highly skewed (γ1 = 49.05477191)Skewed
계산취급량 is highly skewed (γ1 = 53.97309119)Skewed
계산저장량 is highly skewed (γ1 = 37.6089604)Skewed
화학물질일련번호 has unique valuesUnique
물질구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
일일취급량 has 378 (3.8%) zerosZeros
계산취급량 has 400 (4.0%) zerosZeros
계산저장량 has 9521 (95.2%) zerosZeros

Reproduction

Analysis started2023-12-12 14:52:48.017177
Analysis finished2023-12-12 14:52:49.478696
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지원년도
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017
3962 
2016
3375 
2018
2663 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2017 3962
39.6%
2016 3375
33.8%
2018 2663
26.6%

Length

2023-12-12T23:52:49.551185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:49.665112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 3962
39.6%
2016 3375
33.8%
2018 2663
26.6%

일선기관명
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인천광역본부
1011 
부산광역본부
954 
경기서부지사
939 
충북지역본부
693 
대구서부지사
586 
Other values (22)
5817 

Length

Max length8
Median length6
Mean length6.0566
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기지역본부
2nd row대구서부지사
3rd row경기지역본부
4th row경남동부지사
5th row부산광역본부

Common Values

ValueCountFrequency (%)
인천광역본부 1011
 
10.1%
부산광역본부 954
 
9.5%
경기서부지사 939
 
9.4%
충북지역본부 693
 
6.9%
대구서부지사 586
 
5.9%
경기동부지사 558
 
5.6%
대구광역본부 522
 
5.2%
경남동부지사 495
 
5.0%
경기중부지사 469
 
4.7%
경기지역본부 463
 
4.6%
Other values (17) 3310
33.1%

Length

2023-12-12T23:52:49.790133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천광역본부 1011
 
10.1%
부산광역본부 954
 
9.5%
경기서부지사 939
 
9.4%
충북지역본부 693
 
6.9%
대구서부지사 586
 
5.9%
경기동부지사 558
 
5.6%
대구광역본부 522
 
5.2%
경남동부지사 495
 
5.0%
경기중부지사 469
 
4.7%
경기지역본부 463
 
4.6%
Other values (17) 3310
33.1%

고용노동부명
Text

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:52:50.009824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.6173
Min length2

Characters and Unicode

Total characters26173
Distinct characters53
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row대구서부
3rd row경기
4th row양산
5th row부산북부
ValueCountFrequency (%)
안산 757
 
7.6%
대구서부 584
 
5.8%
부산북부 574
 
5.7%
성남 559
 
5.6%
대구청 523
 
5.2%
중부청 506
 
5.1%
인천북부 505
 
5.1%
양산 494
 
4.9%
청주 474
 
4.7%
부천 469
 
4.7%
Other values (41) 4555
45.6%
2023-12-12T23:52:50.392454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 4014
15.3%
청 2452
 
9.4%
산 2450
 
9.4%
안 1470
 
5.6%
천 1434
 
5.5%
구 1393
 
5.3%
대 1351
 
5.2%
주 1263
 
4.8%
북 1102
 
4.2%
서 1006
 
3.8%
Other values (43) 8238
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26169
> 99.9%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 4014
15.3%
청 2452
 
9.4%
산 2450
 
9.4%
안 1470
 
5.6%
천 1434
 
5.5%
구 1393
 
5.3%
대 1351
 
5.2%
주 1263
 
4.8%
북 1102
 
4.2%
서 1006
 
3.8%
Other values (41) 8234
31.5%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26169
> 99.9%
Common 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 4014
15.3%
청 2452
 
9.4%
산 2450
 
9.4%
안 1470
 
5.6%
천 1434
 
5.5%
구 1393
 
5.3%
대 1351
 
5.2%
주 1263
 
4.8%
북 1102
 
4.2%
서 1006
 
3.8%
Other values (41) 8234
31.5%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26169
> 99.9%
ASCII 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 4014
15.3%
청 2452
 
9.4%
산 2450
 
9.4%
안 1470
 
5.6%
천 1434
 
5.5%
구 1393
 
5.3%
대 1351
 
5.2%
주 1263
 
4.8%
북 1102
 
4.2%
서 1006
 
3.8%
Other values (41) 8234
31.5%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

대업종명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제조업
9858 
<NA>
 
140
기타의사업
 
2

Length

Max length5
Median length3
Mean length3.0144
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제조업 9858
98.6%
<NA> 140
 
1.4%
기타의사업 2
 
< 0.1%

Length

2023-12-12T23:52:50.533396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:50.630353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조업 9858
98.6%
na 140
 
1.4%
기타의사업 2
 
< 0.1%

중업종명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
화학및고무제품제조업
3207 
기계기구제조업
796 
기계기구ㆍ금속ㆍ비금속광물제품 제조업
788 
도금업
721 
신문·화폐발행/출판업및경인쇄업
558 
Other values (21)
3930 

Length

Max length19
Median length16
Mean length10.6083
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기계기구ㆍ금속ㆍ비금속광물제품 제조업
2nd row섬유및섬유제품제조업
3rd row목재및종이제품제조업
4th row펄프및지류제조업및제본또는인쇄물가공업
5th row화학및고무제품제조업

Common Values

ValueCountFrequency (%)
화학및고무제품제조업 3207
32.1%
기계기구제조업 796
 
8.0%
기계기구ㆍ금속ㆍ비금속광물제품 제조업 788
 
7.9%
도금업 721
 
7.2%
신문·화폐발행/출판업및경인쇄업 558
 
5.6%
기타제조업 538
 
5.4%
식료품제조업 418
 
4.2%
자동차및모터사이클수리업 355
 
3.5%
전기기계기구ㆍ정밀기구ㆍ전자제품제조업 270
 
2.7%
펄프및지류제조업및제본또는인쇄물가공업 265
 
2.6%
Other values (16) 2084
20.8%

Length

2023-12-12T23:52:50.743266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화학및고무제품제조업 3207
29.4%
제조업 894
 
8.2%
기계기구제조업 796
 
7.3%
기계기구ㆍ금속ㆍ비금속광물제품 788
 
7.2%
도금업 721
 
6.6%
신문·화폐발행/출판업및경인쇄업 558
 
5.1%
기타제조업 538
 
4.9%
식료품제조업 418
 
3.8%
자동차및모터사이클수리업 355
 
3.3%
전기기계기구ㆍ정밀기구ㆍ전자제품제조업 270
 
2.5%
Other values (17) 2349
21.6%

생산품
Text

MISSING 

Distinct4825
Distinct (%)49.6%
Missing271
Missing (%)2.7%
Memory size156.2 KiB
2023-12-12T23:52:51.082614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length26
Mean length5.4781581
Min length1

Characters and Unicode

Total characters53297
Distinct characters710
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

Unique3181 ?
Unique (%)32.7%

Sample

1st row금속가공
2nd row원단가공
3rd row교회용의자
4th row박스제조
5th row자동차 광택제
ValueCountFrequency (%)
자동차 246
 
1.9%
인쇄 222
 
1.7%
자동차부품 173
 
1.4%
부품 149
 
1.2%
도장 122
 
1.0%
도금 120
 
0.9%
레미콘 116
 
0.9%
가공 94
 
0.7%
자동차정비 87
 
0.7%
분체도장 80
 
0.6%
Other values (4597) 11281
88.9%
2023-12-12T23:52:51.609012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2968
 
5.6%
품 1480
 
2.8%
제 1366
 
2.6%
자 1229
 
2.3%
기 1069
 
2.0%
스 998
 
1.9%
부 952
 
1.8%
도 951
 
1.8%
차 946
 
1.8%
장 914
 
1.7%
Other values (700) 40424
75.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46770
87.8%
Space Separator 2968
 
5.6%
Uppercase Letter 1421
 
2.7%
Other Punctuation 807
 
1.5%
Lowercase Letter 473
 
0.9%
Close Punctuation 393
 
0.7%
Open Punctuation 392
 
0.7%
Decimal Number 56
 
0.1%
Dash Punctuation 14
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 1480
 
3.2%
제 1366
 
2.9%
자 1229
 
2.6%
기 1069
 
2.3%
스 998
 
2.1%
부 952
 
2.0%
도 951
 
2.0%
차 946
 
2.0%
장 914
 
2.0%
동 908
 
1.9%
Other values (637) 35957
76.9%
Lowercase Letter
ValueCountFrequency (%)
p 104
22.0%
c 53
11.2%
e 43
 
9.1%
b 29
 
6.1%
r 22
 
4.7%
o 21
 
4.4%
t 21
 
4.4%
v 21
 
4.4%
a 18
 
3.8%
l 17
 
3.6%
Other values (14) 124
26.2%
Uppercase Letter
ValueCountFrequency (%)
P 383
27.0%
C 215
15.1%
B 126
 
8.9%
E 120
 
8.4%
V 105
 
7.4%
A 61
 
4.3%
S 58
 
4.1%
L 53
 
3.7%
T 52
 
3.7%
D 43
 
3.0%
Other values (13) 205
14.4%
Decimal Number
ValueCountFrequency (%)
4 14
25.0%
0 11
19.6%
2 9
16.1%
1 7
12.5%
3 7
12.5%
7 3
 
5.4%
6 3
 
5.4%
9 1
 
1.8%
5 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 742
91.9%
. 65
 
8.1%
Space Separator
ValueCountFrequency (%)
2968
100.0%
Close Punctuation
ValueCountFrequency (%)
) 393
100.0%
Open Punctuation
ValueCountFrequency (%)
( 392
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46770
87.8%
Common 4633
 
8.7%
Latin 1894
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 1480
 
3.2%
제 1366
 
2.9%
자 1229
 
2.6%
기 1069
 
2.3%
스 998
 
2.1%
부 952
 
2.0%
도 951
 
2.0%
차 946
 
2.0%
장 914
 
2.0%
동 908
 
1.9%
Other values (637) 35957
76.9%
Latin
ValueCountFrequency (%)
P 383
20.2%
C 215
 
11.4%
B 126
 
6.7%
E 120
 
6.3%
V 105
 
5.5%
p 104
 
5.5%
A 61
 
3.2%
S 58
 
3.1%
c 53
 
2.8%
L 53
 
2.8%
Other values (37) 616
32.5%
Common
ValueCountFrequency (%)
2968
64.1%
/ 742
 
16.0%
) 393
 
8.5%
( 392
 
8.5%
. 65
 
1.4%
4 14
 
0.3%
- 14
 
0.3%
0 11
 
0.2%
2 9
 
0.2%
1 7
 
0.2%
Other values (6) 18
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46768
87.7%
ASCII 6527
 
12.2%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2968
45.5%
/ 742
 
11.4%
) 393
 
6.0%
( 392
 
6.0%
P 383
 
5.9%
C 215
 
3.3%
B 126
 
1.9%
E 120
 
1.8%
V 105
 
1.6%
p 104
 
1.6%
Other values (53) 979
 
15.0%
Hangul
ValueCountFrequency (%)
품 1480
 
3.2%
제 1366
 
2.9%
자 1229
 
2.6%
기 1069
 
2.3%
스 998
 
2.1%
부 952
 
2.0%
도 951
 
2.0%
차 946
 
2.0%
장 914
 
2.0%
동 908
 
1.9%
Other values (635) 35955
76.9%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
50.0%
ㅏ 1
50.0%

화학물질일련번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10253181
Minimum10167591
Maximum10337559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:51.797945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10167591
5-th percentile10175595
Q110205454
median10253231
Q310304819
95-th percentile10328318
Maximum10337559
Range169968
Interquartile range (IQR)99364.25

Descriptive statistics

Standard deviation50857.987
Coefficient of variation (CV)0.0049602155
Kurtosis-1.2875088
Mean10253181
Median Absolute Deviation (MAD)49960
Skewness-0.015391485
Sum1.0253181 × 1011
Variance2.5865349 × 109
MonotonicityNot monotonic
2023-12-12T23:52:51.950302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10214005 1
 
< 0.1%
10336638 1
 
< 0.1%
10330730 1
 
< 0.1%
10254035 1
 
< 0.1%
10180079 1
 
< 0.1%
10252457 1
 
< 0.1%
10306053 1
 
< 0.1%
10243490 1
 
< 0.1%
10303458 1
 
< 0.1%
10325928 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
10167591 1
< 0.1%
10167592 1
< 0.1%
10167593 1
< 0.1%
10167594 1
< 0.1%
10167595 1
< 0.1%
10167640 1
< 0.1%
10167674 1
< 0.1%
10167679 1
< 0.1%
10167693 1
< 0.1%
10167694 1
< 0.1%
ValueCountFrequency (%)
10337559 1
< 0.1%
10337556 1
< 0.1%
10337538 1
< 0.1%
10337510 1
< 0.1%
10337507 1
< 0.1%
10337495 1
< 0.1%
10337494 1
< 0.1%
10337461 1
< 0.1%
10337459 1
< 0.1%
10337451 1
< 0.1%

취급물질명
Text

Distinct1523
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:52:52.231615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length119
Median length89
Mean length20.1358
Min length1

Characters and Unicode

Total characters201358
Distinct characters476
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique878 ?
Unique (%)8.8%

Sample

1st row이산화 탄소(CARBON DIOXIDE)
2nd row지방산/ C16-18/ 2-에틸헥실 에스테르
3rd row아세톤
4th row구리 프탈로시아닌
5th row에톡실산화 노닐페놀 (EO-9)(ETHOXYLATED NONYLPHENOL (EO-9))
ValueCountFrequency (%)
petroleum 959
 
3.6%
정제유 776
 
2.9%
석유)(distillates 761
 
2.8%
수소처리된 728
 
2.7%
hydrotreated 722
 
2.7%
파라핀 602
 
2.3%
paraffinic 582
 
2.2%
중질 495
 
1.9%
heavy 481
 
1.8%
경질 394
 
1.5%
Other values (2379) 20230
75.7%
2023-12-12T23:52:52.681805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16735
 
8.3%
E 11519
 
5.7%
T 8117
 
4.0%
L 7149
 
3.6%
I 6943
 
3.4%
A 6938
 
3.4%
( 6579
 
3.3%
) 6414
 
3.2%
O 6025
 
3.0%
R 5920
 
2.9%
Other values (466) 119019
59.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 89660
44.5%
Other Letter 66965
33.3%
Space Separator 16735
 
8.3%
Lowercase Letter 7097
 
3.5%
Open Punctuation 6601
 
3.3%
Close Punctuation 6436
 
3.2%
Other Punctuation 3260
 
1.6%
Dash Punctuation 2391
 
1.2%
Decimal Number 2182
 
1.1%
Math Symbol 21
 
< 0.1%
Other values (3) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2893
 
4.3%
유 2504
 
3.7%
리 2265
 
3.4%
이 2037
 
3.0%
틸 2019
 
3.0%
소 1903
 
2.8%
트 1770
 
2.6%
화 1745
 
2.6%
아 1685
 
2.5%
석 1671
 
2.5%
Other values (383) 46473
69.4%
Uppercase Letter
ValueCountFrequency (%)
E 11519
12.8%
T 8117
 
9.1%
L 7149
 
8.0%
I 6943
 
7.7%
A 6938
 
7.7%
O 6025
 
6.7%
R 5920
 
6.6%
D 4684
 
5.2%
H 4096
 
4.6%
Y 3946
 
4.4%
Other values (16) 24323
27.1%
Lowercase Letter
ValueCountFrequency (%)
e 891
12.6%
l 662
 
9.3%
i 548
 
7.7%
a 511
 
7.2%
o 503
 
7.1%
t 473
 
6.7%
n 445
 
6.3%
y 369
 
5.2%
r 368
 
5.2%
c 310
 
4.4%
Other values (16) 2017
28.4%
Decimal Number
ValueCountFrequency (%)
1 599
27.5%
2 522
23.9%
4 233
 
10.7%
3 197
 
9.0%
0 143
 
6.6%
6 135
 
6.2%
5 135
 
6.2%
9 102
 
4.7%
8 65
 
3.0%
7 51
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 2391
73.3%
. 742
 
22.8%
' 41
 
1.3%
; 35
 
1.1%
& 24
 
0.7%
# 18
 
0.6%
% 5
 
0.2%
: 3
 
0.1%
" 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 18
85.7%
> 2
 
9.5%
+ 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 6579
99.7%
[ 22
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 6414
99.7%
] 22
 
0.3%
Space Separator
ValueCountFrequency (%)
16735
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2391
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅳ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 96758
48.1%
Hangul 66965
33.3%
Common 37635
 
18.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2893
 
4.3%
유 2504
 
3.7%
리 2265
 
3.4%
이 2037
 
3.0%
틸 2019
 
3.0%
소 1903
 
2.8%
트 1770
 
2.6%
화 1745
 
2.6%
아 1685
 
2.5%
석 1671
 
2.5%
Other values (383) 46473
69.4%
Latin
ValueCountFrequency (%)
E 11519
 
11.9%
T 8117
 
8.4%
L 7149
 
7.4%
I 6943
 
7.2%
A 6938
 
7.2%
O 6025
 
6.2%
R 5920
 
6.1%
D 4684
 
4.8%
H 4096
 
4.2%
Y 3946
 
4.1%
Other values (43) 31421
32.5%
Common
ValueCountFrequency (%)
16735
44.5%
( 6579
 
17.5%
) 6414
 
17.0%
/ 2391
 
6.4%
- 2391
 
6.4%
. 742
 
2.0%
1 599
 
1.6%
2 522
 
1.4%
4 233
 
0.6%
3 197
 
0.5%
Other values (20) 832
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134392
66.7%
Hangul 66964
33.3%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16735
 
12.5%
E 11519
 
8.6%
T 8117
 
6.0%
L 7149
 
5.3%
I 6943
 
5.2%
A 6938
 
5.2%
( 6579
 
4.9%
) 6414
 
4.8%
O 6025
 
4.5%
R 5920
 
4.4%
Other values (72) 52053
38.7%
Hangul
ValueCountFrequency (%)
산 2893
 
4.3%
유 2504
 
3.7%
리 2265
 
3.4%
이 2037
 
3.0%
틸 2019
 
3.0%
소 1903
 
2.8%
트 1770
 
2.6%
화 1745
 
2.6%
아 1685
 
2.5%
석 1671
 
2.5%
Other values (382) 46472
69.4%
Number Forms
ValueCountFrequency (%)
Ⅳ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

물질구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9745
Missing (%)97.5%
Memory size156.2 KiB

카스번호
Text

Distinct1335
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:52:53.088987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.8965
Min length1

Characters and Unicode

Total characters88965
Distinct characters35
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique713 ?
Unique (%)7.1%

Sample

1st row124-38-9
2nd row91031-48-0
3rd row67-64-1
4th row147-14-8
5th row9016-45-9
ValueCountFrequency (%)
108-88-3 363
 
3.6%
64742-54-7 360
 
3.6%
1330-20-7 288
 
2.9%
68476-85-7 269
 
2.7%
64-17-5 218
 
2.2%
7782-44-7 214
 
2.1%
13463-67-7 208
 
2.1%
1310-73-2 204
 
2.0%
64742-55-8 163
 
1.6%
9002-88-4 155
 
1.6%
Other values (1323) 7558
75.6%
2023-12-12T23:52:53.694885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 19906
22.4%
7 9600
10.8%
4 8522
9.6%
1 7856
 
8.8%
6 7741
 
8.7%
0 7306
 
8.2%
8 6864
 
7.7%
3 6455
 
7.3%
2 5594
 
6.3%
5 4661
 
5.2%
Other values (25) 4460
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68986
77.5%
Dash Punctuation 19906
 
22.4%
Other Letter 57
 
0.1%
Lowercase Letter 13
 
< 0.1%
Space Separator 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 10
17.5%
업 10
17.5%
밀 10
17.5%
비 7
12.3%
없 4
 
7.0%
음 4
 
7.0%
기 3
 
5.3%
물 1
 
1.8%
우 1
 
1.8%
파 1
 
1.8%
Other values (6) 6
10.5%
Decimal Number
ValueCountFrequency (%)
7 9600
13.9%
4 8522
12.4%
1 7856
11.4%
6 7741
11.2%
0 7306
10.6%
8 6864
9.9%
3 6455
9.4%
2 5594
8.1%
5 4661
6.8%
9 4387
6.4%
Lowercase Letter
ValueCountFrequency (%)
p 3
23.1%
o 2
15.4%
l 2
15.4%
y 2
15.4%
e 2
15.4%
n 1
 
7.7%
r 1
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 19906
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88895
99.9%
Hangul 57
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 10
17.5%
업 10
17.5%
밀 10
17.5%
비 7
12.3%
없 4
 
7.0%
음 4
 
7.0%
기 3
 
5.3%
물 1
 
1.8%
우 1
 
1.8%
파 1
 
1.8%
Other values (6) 6
10.5%
Common
ValueCountFrequency (%)
- 19906
22.4%
7 9600
10.8%
4 8522
9.6%
1 7856
 
8.8%
6 7741
 
8.7%
0 7306
 
8.2%
8 6864
 
7.7%
3 6455
 
7.3%
2 5594
 
6.3%
5 4661
 
5.2%
Other values (2) 4390
 
4.9%
Latin
ValueCountFrequency (%)
p 3
23.1%
o 2
15.4%
l 2
15.4%
y 2
15.4%
e 2
15.4%
n 1
 
7.7%
r 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88908
99.9%
Hangul 57
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 19906
22.4%
7 9600
10.8%
4 8522
9.6%
1 7856
 
8.8%
6 7741
 
8.7%
0 7306
 
8.2%
8 6864
 
7.7%
3 6455
 
7.3%
2 5594
 
6.3%
5 4661
 
5.2%
Other values (9) 4403
 
5.0%
Hangul
ValueCountFrequency (%)
영 10
17.5%
업 10
17.5%
밀 10
17.5%
비 7
12.3%
없 4
 
7.0%
음 4
 
7.0%
기 3
 
5.3%
물 1
 
1.8%
우 1
 
1.8%
파 1
 
1.8%
Other values (6) 6
10.5%

함유량
Real number (ℝ)

Distinct202
Distinct (%)2.0%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean63.794509
Minimum0
Maximum1001
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:53.888768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q125
median80
Q3100
95-th percentile100
Maximum1001
Range1001
Interquartile range (IQR)75

Descriptive statistics

Standard deviation39.305789
Coefficient of variation (CV)0.61613123
Kurtosis30.62907
Mean63.794509
Median Absolute Deviation (MAD)20
Skewness1.0080444
Sum637817.5
Variance1544.9451
MonotonicityNot monotonic
2023-12-12T23:52:54.046358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 3576
35.8%
10.0 451
 
4.5%
30.0 431
 
4.3%
20.0 427
 
4.3%
99.0 398
 
4.0%
5.0 336
 
3.4%
50.0 326
 
3.3%
15.0 284
 
2.8%
40.0 269
 
2.7%
35.0 241
 
2.4%
Other values (192) 3259
32.6%
ValueCountFrequency (%)
0.0 13
0.1%
0.01 1
 
< 0.1%
0.05 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.1 16
0.2%
0.2 4
 
< 0.1%
0.3 4
 
< 0.1%
0.4 4
 
< 0.1%
0.5 21
0.2%
ValueCountFrequency (%)
1001.0 1
 
< 0.1%
100.0 3576
35.8%
99.99 1
 
< 0.1%
99.95 1
 
< 0.1%
99.9 20
 
0.2%
99.8 56
 
0.6%
99.7 13
 
0.1%
99.6 5
 
0.1%
99.5 43
 
0.4%
99.3 2
 
< 0.1%

물질안전보건자료보유여부
Boolean

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size97.7 KiB
True
7935 
False
2063 
(Missing)
 
2
ValueCountFrequency (%)
True 7935
79.3%
False 2063
 
20.6%
(Missing) 2
 
< 0.1%
2023-12-12T23:52:54.172895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

일일취급량
Real number (ℝ)

SKEWED  ZEROS 

Distinct551
Distinct (%)5.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean429.69698
Minimum0
Maximum300000
Zeros378
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:54.282576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.3
median2
Q320
95-th percentile500
Maximum300000
Range300000
Interquartile range (IQR)19.7

Descriptive statistics

Standard deviation6773.2108
Coefficient of variation (CV)15.762761
Kurtosis958.82987
Mean429.69698
Median Absolute Deviation (MAD)1.98
Skewness28.743209
Sum4296110.4
Variance45876384
MonotonicityNot monotonic
2023-12-12T23:52:54.788460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 912
 
9.1%
0.1 696
 
7.0%
2.0 471
 
4.7%
0.5 462
 
4.6%
10.0 445
 
4.5%
5.0 404
 
4.0%
0.0 378
 
3.8%
20.0 331
 
3.3%
0.01 316
 
3.2%
0.2 252
 
2.5%
Other values (541) 5331
53.3%
ValueCountFrequency (%)
0.0 378
3.8%
0.01 316
3.2%
0.02 141
 
1.4%
0.03 71
 
0.7%
0.04 56
 
0.6%
0.05 153
1.5%
0.06 33
 
0.3%
0.07 24
 
0.2%
0.08 37
 
0.4%
0.09 11
 
0.1%
ValueCountFrequency (%)
300000.0 1
< 0.1%
250000.0 1
< 0.1%
227200.0 1
< 0.1%
200000.0 2
< 0.1%
165000.0 1
< 0.1%
150000.0 2
< 0.1%
120000.0 1
< 0.1%
100000.0 2
< 0.1%
96624.0 1
< 0.1%
90000.0 1
< 0.1%

일일단위코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
8477 
L
1114 
ton
 
407
<NA>
 
2

Length

Max length4
Median length2
Mean length1.9297
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kg 8477
84.8%
L 1114
 
11.1%
ton 407
 
4.1%
<NA> 2
 
< 0.1%

Length

2023-12-12T23:52:54.941806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:55.069336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 8477
84.8%
l 1114
 
11.1%
ton 407
 
4.1%
na 2
 
< 0.1%

일일비중율
Real number (ℝ)

MISSING  SKEWED 

Distinct496
Distinct (%)9.6%
Missing4809
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean6.8647295
Minimum0
Maximum8636
Zeros35
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:55.212364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q10.86
median1
Q31.4
95-th percentile10
Maximum8636
Range8636
Interquartile range (IQR)0.54

Descriptive statistics

Standard deviation121.87478
Coefficient of variation (CV)17.753763
Kurtosis4845.6361
Mean6.8647295
Median Absolute Deviation (MAD)0.18
Skewness68.529475
Sum35634.811
Variance14853.462
MonotonicityNot monotonic
2023-12-12T23:52:55.382006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 727
 
7.3%
0.8 295
 
2.9%
0.9 235
 
2.4%
0.86 176
 
1.8%
100.0 158
 
1.6%
0.79 141
 
1.4%
0.84 136
 
1.4%
1.1 111
 
1.1%
2.1 98
 
1.0%
1.4 93
 
0.9%
Other values (486) 3021
30.2%
(Missing) 4809
48.1%
ValueCountFrequency (%)
0.0 35
0.4%
0.03 1
 
< 0.1%
0.04 1
 
< 0.1%
0.051 1
 
< 0.1%
0.053 1
 
< 0.1%
0.056 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.075 1
 
< 0.1%
0.09 1
 
< 0.1%
ValueCountFrequency (%)
8636.0 1
 
< 0.1%
980.0 1
 
< 0.1%
182.6 1
 
< 0.1%
104.8 1
 
< 0.1%
100.0 158
1.6%
99.5 1
 
< 0.1%
90.0 1
 
< 0.1%
85.0 5
 
0.1%
80.0 2
 
< 0.1%
75.0 1
 
< 0.1%

최대저장량
Real number (ℝ)

SKEWED 

Distinct612
Distinct (%)6.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean6467.3258
Minimum0
Maximum9000000
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:55.579539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q110
median36
Q3200
95-th percentile5000
Maximum9000000
Range9000000
Interquartile range (IQR)190

Descriptive statistics

Standard deviation140063.85
Coefficient of variation (CV)21.65715
Kurtosis2140.6887
Mean6467.3258
Median Absolute Deviation (MAD)34
Skewness41.559974
Sum64660324
Variance1.9617881 × 1010
MonotonicityNot monotonic
2023-12-12T23:52:55.785331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 1308
 
13.1%
100.0 611
 
6.1%
10.0 510
 
5.1%
200.0 501
 
5.0%
40.0 500
 
5.0%
1.0 364
 
3.6%
50.0 290
 
2.9%
1000.0 287
 
2.9%
500.0 265
 
2.6%
5.0 260
 
2.6%
Other values (602) 5102
51.0%
ValueCountFrequency (%)
0.0 25
0.2%
0.01 16
 
0.2%
0.02 7
 
0.1%
0.03 7
 
0.1%
0.04 5
 
0.1%
0.05 11
 
0.1%
0.06 6
 
0.1%
0.07 1
 
< 0.1%
0.09 4
 
< 0.1%
0.1 55
0.5%
ValueCountFrequency (%)
9000000.0 1
< 0.1%
5000000.0 2
< 0.1%
3330000.0 1
< 0.1%
3000000.0 2
< 0.1%
2684000.0 2
< 0.1%
2400000.0 1
< 0.1%
2000000.0 2
< 0.1%
1500000.0 1
< 0.1%
1005000.0 1
< 0.1%
761000.0 1
< 0.1%

최대단위코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
8101 
L
1122 
ton
 
775
<NA>
 
2

Length

Max length4
Median length2
Mean length1.9657
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kg 8101
81.0%
L 1122
 
11.2%
ton 775
 
7.8%
<NA> 2
 
< 0.1%

Length

2023-12-12T23:52:55.955225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:56.084721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 8101
81.0%
l 1122
 
11.2%
ton 775
 
7.8%
na 2
 
< 0.1%

최대비중량
Real number (ℝ)

MISSING  SKEWED 

Distinct509
Distinct (%)9.9%
Missing4840
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean8.8545583
Minimum0
Maximum8636
Zeros34
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:56.241782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q10.86
median1
Q31.4
95-th percentile10
Maximum8636
Range8636
Interquartile range (IQR)0.54

Descriptive statistics

Standard deviation168.97509
Coefficient of variation (CV)19.083401
Kurtosis2458.8227
Mean8.8545583
Median Absolute Deviation (MAD)0.18
Skewness49.054772
Sum45689.521
Variance28552.581
MonotonicityNot monotonic
2023-12-12T23:52:56.392291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 729
 
7.3%
0.8 294
 
2.9%
0.9 236
 
2.4%
0.86 175
 
1.8%
100.0 157
 
1.6%
0.79 140
 
1.4%
0.84 132
 
1.3%
1.1 112
 
1.1%
2.1 97
 
1.0%
1.4 91
 
0.9%
Other values (499) 2997
30.0%
(Missing) 4840
48.4%
ValueCountFrequency (%)
0.0 34
0.3%
0.04 1
 
< 0.1%
0.05 1
 
< 0.1%
0.051 1
 
< 0.1%
0.056 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.075 1
 
< 0.1%
0.09 1
 
< 0.1%
0.1 3
 
< 0.1%
ValueCountFrequency (%)
8636.0 1
 
< 0.1%
8333.0 1
 
< 0.1%
980.0 1
 
< 0.1%
786.6 1
 
< 0.1%
465.1 1
 
< 0.1%
300.0 1
 
< 0.1%
144.5 1
 
< 0.1%
112.5 1
 
< 0.1%
104.0 1
 
< 0.1%
100.0 157
1.6%

계산취급량
Real number (ℝ)

SKEWED  ZEROS 

Distinct586
Distinct (%)5.9%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2183.3716
Minimum0
Maximum3000000
Zeros400
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:56.552344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.35
median2
Q325
95-th percentile1500
Maximum3000000
Range3000000
Interquartile range (IQR)24.65

Descriptive statistics

Standard deviation42841.177
Coefficient of variation (CV)19.621569
Kurtosis3409.909
Mean2183.3716
Median Absolute Deviation (MAD)1.99
Skewness53.973091
Sum21829349
Variance1.8353665 × 109
MonotonicityNot monotonic
2023-12-12T23:52:56.718752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 840
 
8.4%
0.1 657
 
6.6%
10.0 451
 
4.5%
2.0 444
 
4.4%
0.5 432
 
4.3%
0.0 400
 
4.0%
5.0 379
 
3.8%
20.0 324
 
3.2%
0.01 298
 
3.0%
100.0 242
 
2.4%
Other values (576) 5531
55.3%
ValueCountFrequency (%)
0.0 400
4.0%
0.01 298
3.0%
0.02 145
 
1.5%
0.03 69
 
0.7%
0.04 56
 
0.6%
0.05 149
 
1.5%
0.06 31
 
0.3%
0.07 23
 
0.2%
0.08 37
 
0.4%
0.09 10
 
0.1%
ValueCountFrequency (%)
3000000.0 1
 
< 0.1%
2400000.0 1
 
< 0.1%
750000.0 1
 
< 0.1%
700000.0 1
 
< 0.1%
680000.0 2
< 0.1%
320000.0 1
 
< 0.1%
300000.0 2
< 0.1%
250000.0 4
< 0.1%
240000.0 1
 
< 0.1%
227200.0 1
 
< 0.1%

계산취급단위
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
9998 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.0004
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kg 9998
> 99.9%
<NA> 2
 
< 0.1%

Length

2023-12-12T23:52:56.876814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:57.001318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 9998
> 99.9%
na 2
 
< 0.1%

계산저장량
Real number (ℝ)

SKEWED  ZEROS 

Distinct155
Distinct (%)1.6%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean428.17742
Minimum0
Maximum600000
Zeros9521
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:52:57.103339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum600000
Range600000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11557.949
Coefficient of variation (CV)26.993363
Kurtosis1555.342
Mean428.17742
Median Absolute Deviation (MAD)0
Skewness37.60896
Sum4280917.8
Variance1.3358617 × 108
MonotonicityNot monotonic
2023-12-12T23:52:57.242192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9521
95.2%
20.0 45
 
0.4%
100.0 29
 
0.3%
1000.0 28
 
0.3%
10.0 26
 
0.3%
50.0 17
 
0.2%
40.0 16
 
0.2%
500.0 15
 
0.1%
200.0 14
 
0.1%
60.0 12
 
0.1%
Other values (145) 275
 
2.8%
ValueCountFrequency (%)
0.0 9521
95.2%
0.01 1
 
< 0.1%
0.1 3
 
< 0.1%
0.2 1
 
< 0.1%
0.3 1
 
< 0.1%
0.39 1
 
< 0.1%
0.5 8
 
0.1%
0.58 1
 
< 0.1%
0.6 2
 
< 0.1%
0.67 1
 
< 0.1%
ValueCountFrequency (%)
600000.0 1
< 0.1%
500000.0 1
< 0.1%
400000.0 2
< 0.1%
373000.0 1
< 0.1%
327000.0 1
< 0.1%
200000.0 2
< 0.1%
174000.0 1
< 0.1%
150000.0 1
< 0.1%
100000.0 1
< 0.1%
50000.0 1
< 0.1%

계산저장단위
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
9998 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.0004
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kg 9998
> 99.9%
<NA> 2
 
< 0.1%

Length

2023-12-12T23:52:57.395404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:52:57.506726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 9998
> 99.9%
na 2
 
< 0.1%

Sample

지원년도일선기관명고용노동부명대업종명중업종명생산품화학물질일련번호취급물질명물질구분코드카스번호함유량물질안전보건자료보유여부일일취급량일일단위코드일일비중율최대저장량최대단위코드최대비중량계산취급량계산취급단위계산저장량계산저장단위
202482016경기지역본부경기제조업기계기구ㆍ금속ㆍ비금속광물제품 제조업금속가공10214005이산화 탄소(CARBON DIOXIDE)NaN124-38-9100.0Y20.0kg<NA>80.0kg<NA>20.0kg0.0kg
655532018대구서부지사대구서부제조업섬유및섬유제품제조업원단가공10305071지방산/ C16-18/ 2-에틸헥실 에스테르NaN91031-48-025.0Y7.5kg<NA>25.0kg<NA>7.5kg0.0kg
619642018경기지역본부경기제조업목재및종이제품제조업교회용의자10335757아세톤NaN67-64-135.0Y6.0kg<NA>126.0kg<NA>6.0kg0.0kg
623402018경남동부지사양산제조업펄프및지류제조업및제본또는인쇄물가공업박스제조10330012구리 프탈로시아닌NaN147-14-810.0Y0.8kg<NA>17.0kg<NA>0.8kg0.0kg
657722018부산광역본부부산북부제조업화학및고무제품제조업자동차 광택제10314077에톡실산화 노닐페놀 (EO-9)(ETHOXYLATED NONYLPHENOL (EO-9))NaN9016-45-9100.0Y0.5kg<NA>10.0kg<NA>0.5kg0.0kg
351642017경기중부지사부천제조업화학및고무제품제조업MMA수지10254223탄산 칼슘NaN471-34-1100.0Y450.0kg2.910.0ton2.9450.0kg0.0kg
52272016인천광역본부인천북부제조업전자제품제조업전자부품10182057L-글루타민 산/ 염산NaN138-15-8100.0Y20.0kg<NA>500.0kg<NA>20.0kg0.0kg
383182017광주광역본부광주청제조업기타제조업간판10273858아세톤NaN67-64-1100.0Y0.1kg0.84.5kg0.80.1kg0.0kg
352522017충남지역본부천안제조업식료품제조업한과 제조10271799파마자 기름(CASTOR OIL)NaN8001-79-4100.0Y0.01kg<NA>20.0kg<NA>0.01kg0.0kg
463872017인천광역본부인천북부제조업기계기구ㆍ금속ㆍ비금속광물제품 제조업세면기/샤워기10255073스테이산NaN0000-00-0100.0Y0.83kg<NA>50.0kg<NA>0.83kg0.0kg
지원년도일선기관명고용노동부명대업종명중업종명생산품화학물질일련번호취급물질명물질구분코드카스번호함유량물질안전보건자료보유여부일일취급량일일단위코드일일비중율최대저장량최대단위코드최대비중량계산취급량계산취급단위계산저장량계산저장단위
214562016경남지역본부창원제조업기계기구제조업엔진도장 공장청소10209952m-자일렌NaN108-38-310.0Y800.0kg1.2515.0ton1.251800.0kg0.0kg
314592017경남동부지사양산제조업섬유또는섬유제품제조업(을)탄소섬유10248733아황산 나트륨(SODIUM SULFITE)NaN7757-83-720.1Y60.0kg1.12460.0kg1.12460.0kg0.0kg
128342016경기지역본부경기제조업화학및고무제품제조업PP/PE 압출10214001폴리에틸렌(POLYETHYLENE)NaN9002-88-4100.0Y100.0kg<NA>500.0kg<NA>100.0kg0.0kg
502016전북지역본부전주제조업자동차및모터사이클수리업자동차수리업10168412톨루엔NaN108-88-3100.0Y1.0kg0.86200.0kg0.861.0kg0.0kg
356192017충북지역본부청주제조업기계기구ㆍ금속ㆍ비금속광물제품 제조업H-Beam철골제작10261880액화석유가스NaN68476-85-7100.0N4.0kg0.580.0kg0.54.0kg0.0kg
660812018경기서부지사안산제조업화학및고무제품제조업사출성형(LED케이스)10314559삼산화 안티모니NaN1309-64-45.0Y4.0kg5.250.0kg5.24.0kg0.0kg
615542018대구광역본부대구청<NA><NA>정제연료유103086982/6-디-제3-부틸-p-크레졸NaN128-37-00.1Y0.0kg1.0481.0kg1.0480.0kg0.0kg
539992018충남지역본부천안제조업기계기구ㆍ금속ㆍ비금속광물제품 제조업구조금속제품10328252망가니즈NaN7439-96-55.0Y1.36kg0.1830.0kg4.01.36kg0.0kg
338322017전남동부지사여수제조업화학및고무제품제조업성형부자생산10236195액화석유가스NaN68476-85-7100.0Y0.3kg<NA>20.0kg<NA>0.3kg0.0kg
398142017경기서부지사안산제조업섬유또는섬유제품제조업(을)염색가공10257621수산화 나트륨(SODIUM HYDROXIDE)NaN1310-73-23.0Y20.0kg2.1500.0kg2.120.0kg0.0kg