Overview

Dataset statistics

Number of variables5
Number of observations113
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory45.2 B

Variable types

Numeric4
Categorical1

Dataset

Description업종별 방사선작업종사자 평균 피폭선량 데이터입니다.원자력발전소 뿐만아니라 병원, 반도체공장 등에서 연간 피폭되는 선량을 데이터로 표시했습니다.(외부)피폭선량이란?원자력안전법에 따라 개인이 신체의 외부에 받은 피폭방사선량으로 원자력안전법 시행령에서 허용하는 선량은 연간 유효선량으로 직무피폭의 경우(작업종사) 연간 20mSv, 일반인의 경우 연간 1mSv이다.
Author원자력안전위원회
URLhttps://www.data.go.kr/data/15123546/fileData.do

Alerts

번호 is highly overall correlated with 발표연도 and 1 other fieldsHigh correlation
발표연도 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
기준연도 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
피폭선량(mcsv) is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 피폭선량(mcsv)High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:39:25.595172
Analysis finished2023-12-12 12:39:27.949512
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57
Minimum1
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:39:28.044324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q129
median57
Q385
95-th percentile107.4
Maximum113
Range112
Interquartile range (IQR)56

Descriptive statistics

Standard deviation32.76431
Coefficient of variation (CV)0.57481245
Kurtosis-1.2
Mean57
Median Absolute Deviation (MAD)28
Skewness0
Sum6441
Variance1073.5
MonotonicityStrictly increasing
2023-12-12T21:39:28.245964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
86 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%

발표연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.6018
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:39:28.402693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12020
median2021
Q32022
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6286488
Coefficient of variation (CV)0.00080602165
Kurtosis-0.18975082
Mean2020.6018
Median Absolute Deviation (MAD)1
Skewness-1.0371796
Sum228328
Variance2.6524968
MonotonicityDecreasing
2023-12-12T21:39:28.554794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 45
39.8%
2021 32
28.3%
2020 9
 
8.0%
2019 9
 
8.0%
2018 9
 
8.0%
2017 9
 
8.0%
ValueCountFrequency (%)
2017 9
 
8.0%
2018 9
 
8.0%
2019 9
 
8.0%
2020 9
 
8.0%
2021 32
28.3%
2022 45
39.8%
ValueCountFrequency (%)
2022 45
39.8%
2021 32
28.3%
2020 9
 
8.0%
2019 9
 
8.0%
2018 9
 
8.0%
2017 9
 
8.0%

기준연도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5044
Minimum2012
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:39:28.694302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12015
median2018
Q32020
95-th percentile2022
Maximum2022
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0825659
Coefficient of variation (CV)0.0015279103
Kurtosis-1.0534676
Mean2017.5044
Median Absolute Deviation (MAD)2
Skewness-0.4120967
Sum227978
Variance9.5022124
MonotonicityNot monotonic
2023-12-12T21:39:28.866768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2018 17
15.0%
2019 17
15.0%
2020 17
15.0%
2021 9
8.0%
2022 9
8.0%
2015 9
8.0%
2014 9
8.0%
2013 9
8.0%
2012 9
8.0%
2017 8
7.1%
ValueCountFrequency (%)
2012 9
8.0%
2013 9
8.0%
2014 9
8.0%
2015 9
8.0%
2017 8
7.1%
2018 17
15.0%
2019 17
15.0%
2020 17
15.0%
2021 9
8.0%
2022 9
8.0%
ValueCountFrequency (%)
2022 9
8.0%
2021 9
8.0%
2020 17
15.0%
2019 17
15.0%
2018 17
15.0%
2017 8
7.1%
2015 9
8.0%
2014 9
8.0%
2013 9
8.0%
2012 9
8.0%

업종
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
원자력발전소
13 
일반산업체
13 
의료기관
13 
연구기관
13 
교육기관
13 
Other values (6)
48 

Length

Max length9
Median length4
Mean length4.5929204
Min length4

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row원자력발전소
2nd row일반산업체
3rd rowNDT업체
4th row의료기관
5th row연구기관

Common Values

ValueCountFrequency (%)
원자력발전소 13
11.5%
일반산업체 13
11.5%
의료기관 13
11.5%
연구기관 13
11.5%
교육기관 13
11.5%
공공기관 13
11.5%
군사기관 13
11.5%
NDT업체 11
9.7%
전체 평균 9
8.0%
방사선투과검사업체 1
 
0.9%

Length

2023-12-12T21:39:29.035004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원자력발전소 13
10.7%
일반산업체 13
10.7%
의료기관 13
10.7%
연구기관 13
10.7%
교육기관 13
10.7%
공공기관 13
10.7%
군사기관 13
10.7%
ndt업체 11
9.0%
전체 9
7.4%
평균 9
7.4%
Other values (2) 2
 
1.6%

피폭선량(mcsv)
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.37256637
Minimum0.01
Maximum3.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:39:29.187337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.02
Q10.05
median0.22
Q30.52
95-th percentile0.906
Maximum3.87
Range3.86
Interquartile range (IQR)0.47

Descriptive statistics

Standard deviation0.56459495
Coefficient of variation (CV)1.5154211
Kurtosis20.826152
Mean0.37256637
Median Absolute Deviation (MAD)0.19
Skewness4.1155725
Sum42.1
Variance0.31876746
MonotonicityNot monotonic
2023-12-12T21:39:29.366649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 11
 
9.7%
0.04 10
 
8.8%
0.03 6
 
5.3%
0.41 6
 
5.3%
0.06 4
 
3.5%
0.09 4
 
3.5%
0.08 4
 
3.5%
0.1 4
 
3.5%
0.57 3
 
2.7%
0.58 3
 
2.7%
Other values (41) 58
51.3%
ValueCountFrequency (%)
0.01 1
 
0.9%
0.02 11
9.7%
0.03 6
5.3%
0.04 10
8.8%
0.05 2
 
1.8%
0.06 4
 
3.5%
0.07 2
 
1.8%
0.08 4
 
3.5%
0.09 4
 
3.5%
0.1 4
 
3.5%
ValueCountFrequency (%)
3.87 1
0.9%
3.43 1
0.9%
2.37 1
0.9%
1.77 1
0.9%
1.07 1
0.9%
0.96 1
0.9%
0.87 1
0.9%
0.84 1
0.9%
0.82 1
0.9%
0.73 1
0.9%

Interactions

2023-12-12T21:39:27.299650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:25.829128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.186313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.885007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:27.409029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:25.925378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.280358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.982395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:27.534186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.011207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.697760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:27.069767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:27.619690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.092277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:26.782492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:39:27.159824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:39:29.496097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발표연도기준연도업종피폭선량(mcsv)
번호1.0000.9770.9010.0000.298
발표연도0.9771.0000.9520.0000.376
기준연도0.9010.9521.0000.0000.312
업종0.0000.0000.0001.0000.858
피폭선량(mcsv)0.2980.3760.3120.8581.000
2023-12-12T21:39:29.635894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발표연도기준연도피폭선량(mcsv)업종
번호1.000-0.955-0.6760.1390.000
발표연도-0.9551.0000.852-0.1730.000
기준연도-0.6760.8521.000-0.1790.000
피폭선량(mcsv)0.139-0.173-0.1791.0000.645
업종0.0000.0000.0000.6451.000

Missing values

2023-12-12T21:39:27.771914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:39:27.895418image/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

번호발표연도기준연도업종피폭선량(mcsv)
0120222018원자력발전소0.57
1220222018일반산업체0.08
2320222018NDT업체0.7
3420222018의료기관0.38
4520222018연구기관0.04
5620222018교육기관0.02
6720222018공공기관0.24
7820222018군사기관0.09
8920222018전체 평균0.36
91020222019원자력발전소0.43
번호발표연도기준연도업종피폭선량(mcsv)
10310420182013전체 평균1.07
10410520172012일반산업체0.22
10510620172012NDT업체3.43
10610720172012의료기관0.87
10710820172012연구기관0.03
10810920172012교육기관0.04
10911020172012공공기관0.57
11011120172012군사기관0.02
11111220172012원자력발전소0.71
11211320172012전체 평균0.96