Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.3 KiB
Average record size in memory95.3 B

Variable types

Categorical5
Numeric6

Alerts

제품분류 has constant value ""Constant
출처 has constant value ""Constant
평균 is highly overall correlated with 표준편차 and 4 other fieldsHigh correlation
표준편차 is highly overall correlated with 평균 and 4 other fieldsHigh correlation
50분위수 is highly overall correlated with 평균 and 4 other fieldsHigh correlation
75분위수 is highly overall correlated with 평균 and 4 other fieldsHigh correlation
85분위수 is highly overall correlated with 평균 and 4 other fieldsHigh correlation
95분위수 is highly overall correlated with 평균 and 4 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 13:15:27.468570
Analysis finished2023-12-10 13:15:33.956507
Duration6.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제품분류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
실내 살균용
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row실내 살균용
2nd row실내 살균용
3rd row실내 살균용
4th row실내 살균용
5th row실내 살균용

Common Values

ValueCountFrequency (%)
실내 살균용 100
100.0%

Length

2023-12-10T22:15:34.072885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:34.282231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 100
50.0%
살균용 100
50.0%

사용용도
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
욕실 살균용
23 
욕실 곰팡이 제거용
23 
주방 살균용
18 
배수구용
18 
변기 살균용
15 

Length

Max length10
Median length6
Mean length6.59
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주방 살균용
2nd row주방 살균용
3rd row주방 살균용
4th row주방 살균용
5th row주방 살균용

Common Values

ValueCountFrequency (%)
욕실 살균용 23
23.0%
욕실 곰팡이 제거용 23
23.0%
주방 살균용 18
18.0%
배수구용 18
18.0%
변기 살균용 15
15.0%
다용도 살균용 3
 
3.0%

Length

2023-12-10T22:15:34.462917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:34.653733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
살균용 59
28.8%
욕실 46
22.4%
곰팡이 23
 
11.2%
제거용 23
 
11.2%
주방 18
 
8.8%
배수구용 18
 
8.8%
변기 15
 
7.3%
다용도 3
 
1.5%

제품형태
Categorical

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
분사형 (트리거폼)
30 
분사형 (트리거)
24 
비분사형 (액상)
18 
분사형 (스프레이폼)
10 
분말형
6 
Other values (2)
12 

Length

Max length11
Median length10
Mean length8.72
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비분사형 (액상)
2nd row비분사형 (액상)
3rd row비분사형 (액상)
4th row분사형 (트리거)
5th row분사형 (트리거)

Common Values

ValueCountFrequency (%)
분사형 (트리거폼) 30
30.0%
분사형 (트리거) 24
24.0%
비분사형 (액상) 18
18.0%
분사형 (스프레이폼) 10
 
10.0%
분말형 6
 
6.0%
겔형 6
 
6.0%
분말형 (발포형) 6
 
6.0%

Length

2023-12-10T22:15:34.872684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:35.055493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분사형 64
34.0%
트리거폼 30
16.0%
트리거 24
 
12.8%
비분사형 18
 
9.6%
액상 18
 
9.6%
분말형 12
 
6.4%
스프레이폼 10
 
5.3%
겔형 6
 
3.2%
발포형 6
 
3.2%

노출계수
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사용시간 (min/use)
23 
회당 사용량 (g/use)
21 
사용횟수 (use/month)
19 
분사시간 (sec/use)
11 
Mass generation (g/sec)
11 
Other values (3)
15 

Length

Max length24
Median length23
Mean length16.39
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사용횟수 (use/month)
2nd row사용시간 (min/use)
3rd row회당 사용량 (g/use)
4th row사용횟수 (use/month)
5th row사용시간 (min/use)

Common Values

ValueCountFrequency (%)
사용시간 (min/use) 23
23.0%
회당 사용량 (g/use) 21
21.0%
사용횟수 (use/month) 19
19.0%
분사시간 (sec/use) 11
11.0%
Mass generation (g/sec) 11
11.0%
분사횟수 (trigger/use) 9
 
9.0%
사용횟수 (use/year) 4
 
4.0%
Mass generation (g/each) 2
 
2.0%

Length

2023-12-10T22:15:35.264224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:35.451064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용시간 23
9.8%
min/use 23
9.8%
사용횟수 23
9.8%
회당 21
9.0%
사용량 21
9.0%
g/use 21
9.0%
use/month 19
8.1%
mass 13
 
5.6%
generation 13
 
5.6%
분사시간 11
 
4.7%
Other values (6) 46
19.7%

평균
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.3238
Minimum1.82
Maximum237.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:35.699967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.82
5-th percentile2.189
Q13.775
median8.505
Q336.04
95-th percentile112.7655
Maximum237.03
Range235.21
Interquartile range (IQR)32.265

Descriptive statistics

Standard deviation42.443274
Coefficient of variation (CV)1.4985021
Kurtosis7.0134972
Mean28.3238
Median Absolute Deviation (MAD)5.615
Skewness2.4763829
Sum2832.38
Variance1801.4315
MonotonicityNot monotonic
2023-12-10T22:15:35.931961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.24 2
 
2.0%
7.69 2
 
2.0%
36.04 2
 
2.0%
2.35 2
 
2.0%
8.86 2
 
2.0%
57.88 2
 
2.0%
7.18 2
 
2.0%
11.28 2
 
2.0%
6.69 2
 
2.0%
20.6 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
1.82 1
1.0%
1.89 1
1.0%
1.92 1
1.0%
1.98 1
1.0%
2.17 1
1.0%
2.19 1
1.0%
2.29 1
1.0%
2.35 2
2.0%
2.6 1
1.0%
2.73 1
1.0%
ValueCountFrequency (%)
237.03 1
1.0%
181.62 1
1.0%
141.53 1
1.0%
137.15 1
1.0%
128.26 1
1.0%
111.95 1
1.0%
110.9 1
1.0%
93.56 1
1.0%
92.05 1
1.0%
91.42 1
1.0%

표준편차
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.9693
Minimum0.01
Maximum1639.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:36.166559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1585
Q15.8675
median12.935
Q359.3075
95-th percentile231.261
Maximum1639.36
Range1639.35
Interquartile range (IQR)53.44

Descriptive statistics

Standard deviation203.87048
Coefficient of variation (CV)2.7193862
Kurtosis41.48714
Mean74.9693
Median Absolute Deviation (MAD)9.545
Skewness6.0709518
Sum7496.93
Variance41563.171
MonotonicityNot monotonic
2023-12-10T22:15:36.706190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.04 2
 
2.0%
21.19 2
 
2.0%
8.29 2
 
2.0%
0.01 2
 
2.0%
8.6 2
 
2.0%
136.58 2
 
2.0%
55.99 2
 
2.0%
17.48 1
 
1.0%
50.77 1
 
1.0%
36.39 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
0.01 2
2.0%
0.1 1
1.0%
0.12 1
1.0%
0.13 1
1.0%
0.16 1
1.0%
0.38 1
1.0%
0.51 1
1.0%
0.62 1
1.0%
0.74 1
1.0%
0.84 1
1.0%
ValueCountFrequency (%)
1639.36 1
1.0%
1115.52 1
1.0%
361.35 1
1.0%
324.63 1
1.0%
233.75 1
1.0%
231.13 1
1.0%
210.4 1
1.0%
199.61 1
1.0%
189.48 1
1.0%
151.29 1
1.0%

50분위수
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.0545
Minimum1
Maximum135.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:36.937752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.6365
Q12.22
median5
Q320
95-th percentile63.3645
Maximum135.68
Range134.68
Interquartile range (IQR)17.78

Descriptive statistics

Standard deviation21.107627
Coefficient of variation (CV)1.5018412
Kurtosis11.665215
Mean14.0545
Median Absolute Deviation (MAD)3
Skewness3.00935
Sum1405.45
Variance445.53192
MonotonicityNot monotonic
2023-12-10T22:15:37.287700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 11
 
11.0%
2.0 8
 
8.0%
20.0 6
 
6.0%
10.0 6
 
6.0%
30.0 5
 
5.0%
1.0 5
 
5.0%
4.0 3
 
3.0%
2.36 2
 
2.0%
24.0 2
 
2.0%
15.0 2
 
2.0%
Other values (48) 50
50.0%
ValueCountFrequency (%)
1.0 5
5.0%
1.67 1
 
1.0%
1.77 1
 
1.0%
1.87 1
 
1.0%
1.88 1
 
1.0%
1.97 1
 
1.0%
1.98 1
 
1.0%
2.0 8
8.0%
2.08 1
 
1.0%
2.11 1
 
1.0%
ValueCountFrequency (%)
135.68 1
1.0%
75.16 1
1.0%
71.28 1
1.0%
67.27 1
1.0%
65.92 1
1.0%
63.23 1
1.0%
60.0 1
1.0%
50.75 1
1.0%
41.07 1
1.0%
31.87 1
1.0%

75분위수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.7515
Minimum1.89
Maximum271.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:37.572919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.89
5-th percentile2.4115
Q14
median10
Q344.79
95-th percentile120.3235
Maximum271.37
Range269.48
Interquartile range (IQR)40.79

Descriptive statistics

Standard deviation42.587941
Coefficient of variation (CV)1.4314553
Kurtosis10.369617
Mean29.7515
Median Absolute Deviation (MAD)6.795
Skewness2.7571656
Sum2975.15
Variance1813.7327
MonotonicityNot monotonic
2023-12-10T22:15:37.821394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 13
 
13.0%
10.0 9
 
9.0%
60.0 9
 
9.0%
20.0 5
 
5.0%
30.0 3
 
3.0%
8.0 3
 
3.0%
120.0 2
 
2.0%
48.0 2
 
2.0%
24.0 2
 
2.0%
1.89 2
 
2.0%
Other values (49) 50
50.0%
ValueCountFrequency (%)
1.89 2
2.0%
2.0 1
1.0%
2.17 1
1.0%
2.25 1
1.0%
2.42 1
1.0%
2.71 1
1.0%
2.77 1
1.0%
2.78 1
1.0%
3.0 1
1.0%
3.08 1
1.0%
ValueCountFrequency (%)
271.37 1
1.0%
142.56 1
1.0%
134.53 1
1.0%
131.85 1
1.0%
126.47 1
1.0%
120.0 2
2.0%
112.75 1
1.0%
100.0 1
1.0%
71.87 1
1.0%
63.74 1
1.0%

85분위수
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.1387
Minimum1.9
Maximum407.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:38.068616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile2.7445
Q14.9325
median16.09
Q360
95-th percentile151.8135
Maximum407.05
Range405.15
Interquartile range (IQR)55.0675

Descriptive statistics

Standard deviation63.462553
Coefficient of variation (CV)1.5060397
Kurtosis11.567618
Mean42.1387
Median Absolute Deviation (MAD)12.145
Skewness2.948764
Sum4213.87
Variance4027.4957
MonotonicityNot monotonic
2023-12-10T22:15:38.308921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 9
 
9.0%
4.0 8
 
8.0%
20.0 5
 
5.0%
10.0 5
 
5.0%
60.0 4
 
4.0%
90.0 3
 
3.0%
61.02 3
 
3.0%
8.0 3
 
3.0%
12.0 3
 
3.0%
5.0 3
 
3.0%
Other values (47) 54
54.0%
ValueCountFrequency (%)
1.9 2
2.0%
2.17 1
1.0%
2.25 1
1.0%
2.45 1
1.0%
2.76 1
1.0%
2.84 1
1.0%
2.96 1
1.0%
3.37 1
1.0%
3.38 1
1.0%
3.93 1
1.0%
ValueCountFrequency (%)
407.05 1
1.0%
240.0 2
2.0%
180.0 2
2.0%
150.33 1
1.0%
142.56 1
1.0%
134.53 1
1.0%
131.85 1
1.0%
126.47 1
1.0%
120.0 2
2.0%
107.8 1
1.0%

95분위수
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.8979
Minimum1.9
Maximum1200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:38.566006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile2.774
Q112
median24.135
Q3120
95-th percentile360.305
Maximum1200
Range1198.1
Interquartile range (IQR)108

Descriptive statistics

Standard deviation168.3828
Coefficient of variation (CV)1.8125577
Kurtosis20.047444
Mean92.8979
Median Absolute Deviation (MAD)17.16
Skewness3.9051768
Sum9289.79
Variance28352.768
MonotonicityNot monotonic
2023-12-10T22:15:38.798334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.0 11
 
11.0%
60.0 9
 
9.0%
20.0 8
 
8.0%
30.0 6
 
6.0%
120.0 3
 
3.0%
180.0 2
 
2.0%
10.0 2
 
2.0%
360.0 2
 
2.0%
678.42 1
 
1.0%
480.0 1
 
1.0%
Other values (55) 55
55.0%
ValueCountFrequency (%)
1.9 1
1.0%
1.91 1
1.0%
2.18 1
1.0%
2.26 1
1.0%
2.47 1
1.0%
2.79 1
1.0%
3.01 1
1.0%
3.05 1
1.0%
3.38 1
1.0%
3.52 1
1.0%
ValueCountFrequency (%)
1200.0 1
1.0%
678.42 1
1.0%
600.0 1
1.0%
480.0 1
1.0%
366.1 1
1.0%
360.0 2
2.0%
356.39 1
1.0%
240.0 1
1.0%
230.75 1
1.0%
215.6 1
1.0%

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
100 

Length

Max length40
Median length40
Mean length40
Min length40

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
2nd row국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
3rd row국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
4th row국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
5th row국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집

Common Values

ValueCountFrequency (%)
국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집 100
100.0%

Length

2023-12-10T22:15:39.048953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:39.232271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국립환경과학원 100
33.3%
2018 100
33.3%
살생물제품노출평가및위해성평가를위한노출계수자료집 100
33.3%

Interactions

2023-12-10T22:15:32.442076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.071913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.962805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.781474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.627586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.523029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.562753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.193753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.085452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.926102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.796603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.644697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.704660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.407711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.222454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.080439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.931174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.808018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.849627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.548440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.367398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.226276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.128953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.960925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.998765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.676604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.493721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.356812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.257107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.128685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:33.153142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:28.837123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:29.638682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:30.493615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:31.386467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:32.293594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:15:39.356377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용용도제품형태노출계수평균표준편차50분위수75분위수85분위수95분위수
사용용도1.0000.4180.0000.1920.0000.2800.1690.3010.126
제품형태0.4181.0000.3590.2470.1720.5260.5270.6760.612
노출계수0.0000.3591.0000.5360.0000.5930.4380.4370.220
평균0.1920.2470.5361.0000.8940.8470.8980.8700.860
표준편차0.0000.1720.0000.8941.0000.7580.7430.7980.779
50분위수0.2800.5260.5930.8470.7581.0000.9680.9620.921
75분위수0.1690.5270.4380.8980.7430.9681.0000.9730.943
85분위수0.3010.6760.4370.8700.7980.9620.9731.0000.967
95분위수0.1260.6120.2200.8600.7790.9210.9430.9671.000
2023-12-10T22:15:39.546575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제품형태사용용도노출계수
제품형태1.0000.2620.199
사용용도0.2621.0000.000
노출계수0.1990.0001.000
2023-12-10T22:15:39.699714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평균표준편차50분위수75분위수85분위수95분위수사용용도제품형태노출계수
평균1.0000.9190.9420.9740.9850.9810.1030.1310.203
표준편차0.9191.0000.8010.8750.9130.9270.0000.1060.000
50분위수0.9420.8011.0000.9600.9410.9220.1680.2050.366
75분위수0.9740.8750.9601.0000.9790.9700.0970.2050.249
85분위수0.9850.9130.9410.9791.0000.9900.1820.2910.249
95분위수0.9810.9270.9220.9700.9901.0000.0700.2510.115
사용용도0.1030.0000.1680.0970.1820.0701.0000.2620.000
제품형태0.1310.1060.2050.2050.2910.2510.2621.0000.199
노출계수0.2030.0000.3660.2490.2490.1150.0000.1991.000

Missing values

2023-12-10T22:15:33.394666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:15:33.813731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

제품분류사용용도제품형태노출계수평균표준편차50분위수75분위수85분위수95분위수출처
0실내 살균용주방 살균용비분사형 (액상)사용횟수 (use/month)9.4417.484.010.020.030.42국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
1실내 살균용주방 살균용비분사형 (액상)사용시간 (min/use)16.6233.5210.020.030.060.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
2실내 살균용주방 살균용비분사형 (액상)회당 사용량 (g/use)92.05131.8275.16112.75150.33187.91국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
3실내 살균용주방 살균용분사형 (트리거)사용횟수 (use/month)6.6916.044.08.012.020.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
4실내 살균용주방 살균용분사형 (트리거)사용시간 (min/use)11.2821.195.010.1720.2530.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
5실내 살균용주방 살균용분사형 (트리거)분사횟수 (trigger/use)7.188.295.010.010.020.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
6실내 살균용주방 살균용분사형 (트리거)회당 사용량 (g/use)6.547.554.559.19.118.21국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
7실내 살균용주방 살균용분사형 (트리거)분사시간 (sec/use)2.993.452.084.164.168.33국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
8실내 살균용주방 살균용분사형 (트리거)Mass generation (g/sec)2.190.12.232.252.252.26국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
9실내 살균용주방 살균용분말형사용횟수 (use/month)5.6611.053.338.012.020.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
제품분류사용용도제품형태노출계수평균표준편차50분위수75분위수85분위수95분위수출처
90실내 살균용변기 살균용분사형 (트리거폼)Mass generation (g/sec)1.820.121.871.891.91.91국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
91실내 살균용변기 살균용겔형사용횟수 (use/month)7.2169.262.04.05.012.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
92실내 살균용변기 살균용겔형사용시간 (min/use)88.35233.7520.060.0120.0366.1국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
93실내 살균용변기 살균용겔형회당 사용량 (g/use)15.75151.2931.563.078.75189.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
94실내 살균용변기 살균용분말형 (발포형)사용횟수 (use/month)3.6110.671.03.04.012.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
95실내 살균용변기 살균용분말형 (발포형)사용시간 (min/use)137.15324.6320.060.0180.01200.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
96실내 살균용변기 살균용분말형 (발포형)Mass generation (g/each)50.5410.8550.7560.4360.4860.51국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
97실내 살균용다용도 살균용비분사형 (액상)사용횟수 (use/month)4.268.262.04.08.012.0국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
98실내 살균용다용도 살균용비분사형 (액상)사용시간 (min/use)60.63137.2530.060.090.0230.75국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집
99실내 살균용다용도 살균용비분사형 (액상)회당 사용량 (g/use)93.56102.5865.92131.85131.85164.81국립환경과학원. 2018. 살생물제품노출평가및위해성평가를위한노출계수자료집