Overview

Dataset statistics

Number of variables12
Number of observations30
Missing cells41
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory103.4 B

Variable types

Text1
Categorical3
Numeric3
DateTime5

Dataset

Description국내에서 가동중인 원전에 대한 원전명, 노형, 용량, 공급자, 착공일, 정지일, 운영상태 등의 데이터를 제공합니다.
Author한국원자력안전기술원
URLhttps://www.data.go.kr/data/15088857/fileData.do

Alerts

총용량(MWe) is highly overall correlated with 순용량(MWe) and 3 other fieldsHigh correlation
순용량(MWe) is highly overall correlated with 총용량(MWe) and 3 other fieldsHigh correlation
최초설계 순용량(MWe) is highly overall correlated with 총용량(MWe) and 2 other fieldsHigh correlation
노형 is highly overall correlated with 총용량(MWe) and 3 other fieldsHigh correlation
원자로 공급자 is highly overall correlated with 총용량(MWe) and 2 other fieldsHigh correlation
착공일 has 2 (6.7%) missing valuesMissing
운영허가일 has 3 (10.0%) missing valuesMissing
임계일 has 4 (13.3%) missing valuesMissing
상업운전일 has 4 (13.3%) missing valuesMissing
정지일 has 28 (93.3%) missing valuesMissing
원전명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:23:32.318172
Analysis finished2023-12-12 12:23:34.447870
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

원전명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T21:23:34.624322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.9333333
Min length6

Characters and Unicode

Total characters268
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowHanbit-1
2nd rowHanbit-2
3rd rowHanbit-3
4th rowHanbit-4
5th rowHanbit-5
ValueCountFrequency (%)
hanbit-1 1
 
3.3%
hanbit-2 1
 
3.3%
wolsong-3 1
 
3.3%
wolsong-2 1
 
3.3%
wolsong-1 1
 
3.3%
shin-wolsong-2 1
 
3.3%
shin-wolsong-1 1
 
3.3%
shin-kori-6 1
 
3.3%
shin-kori-5 1
 
3.3%
shin-kori-4 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T21:23:35.134576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 40
14.9%
n 30
 
11.2%
i 26
 
9.7%
o 22
 
8.2%
H 14
 
5.2%
a 14
 
5.2%
l 14
 
5.2%
h 10
 
3.7%
S 10
 
3.7%
r 10
 
3.7%
Other values (13) 78
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 158
59.0%
Dash Punctuation 40
 
14.9%
Uppercase Letter 40
 
14.9%
Decimal Number 30
 
11.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 30
19.0%
i 26
16.5%
o 22
13.9%
a 14
8.9%
l 14
8.9%
h 10
 
6.3%
r 10
 
6.3%
u 8
 
5.1%
s 6
 
3.8%
g 6
 
3.8%
Other values (2) 12
 
7.6%
Decimal Number
ValueCountFrequency (%)
1 7
23.3%
2 7
23.3%
4 5
16.7%
3 5
16.7%
6 3
10.0%
5 3
10.0%
Uppercase Letter
ValueCountFrequency (%)
H 14
35.0%
S 10
25.0%
K 10
25.0%
W 6
15.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 198
73.9%
Common 70
 
26.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 30
15.2%
i 26
13.1%
o 22
11.1%
H 14
 
7.1%
a 14
 
7.1%
l 14
 
7.1%
h 10
 
5.1%
S 10
 
5.1%
r 10
 
5.1%
K 10
 
5.1%
Other values (6) 38
19.2%
Common
ValueCountFrequency (%)
- 40
57.1%
1 7
 
10.0%
2 7
 
10.0%
4 5
 
7.1%
3 5
 
7.1%
6 3
 
4.3%
5 3
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 40
14.9%
n 30
 
11.2%
i 26
 
9.7%
o 22
 
8.2%
H 14
 
5.2%
a 14
 
5.2%
l 14
 
5.2%
h 10
 
3.7%
S 10
 
3.7%
r 10
 
3.7%
Other values (13) 78
29.1%

노형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
PWR
26 
PHWR
4 

Length

Max length4
Median length3
Mean length3.1333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PWR 26
86.7%
PHWR 4
 
13.3%

Length

2023-12-12T21:23:35.313704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:23:35.442824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pwr 26
86.7%
phwr 4
 
13.3%

총용량(MWe)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1038.9667
Minimum608
Maximum1455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:23:35.588438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum608
5-th percentile675.45
Q11000
median1047.5
Q31052.75
95-th percentile1430.25
Maximum1455
Range847
Interquartile range (IQR)52.75

Descriptive statistics

Standard deviation241.82118
Coefficient of variation (CV)0.23275162
Kurtosis-0.32518824
Mean1038.9667
Median Absolute Deviation (MAD)46
Skewness0.068416023
Sum31169
Variance58477.482
MonotonicityNot monotonic
2023-12-12T21:23:35.753781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1400 4
 
13.3%
1000 2
 
6.7%
1455 2
 
6.7%
1050 2
 
6.7%
1049 2
 
6.7%
1053 2
 
6.7%
1051 2
 
6.7%
691 1
 
3.3%
688 1
 
3.3%
675 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
608 1
3.3%
675 1
3.3%
676 1
3.3%
685 1
3.3%
688 1
3.3%
691 1
3.3%
993 1
3.3%
1000 2
6.7%
1003 1
3.3%
1008 1
3.3%
ValueCountFrequency (%)
1455 2
6.7%
1400 4
13.3%
1053 2
6.7%
1052 1
 
3.3%
1051 2
6.7%
1050 2
6.7%
1049 2
6.7%
1046 1
 
3.3%
1045 1
 
3.3%
1042 1
 
3.3%

순용량(MWe)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean994.56667
Minimum576
Maximum1400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:23:35.906071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum576
5-th percentile644.5
Q1961.5
median997.5
Q31007.5
95-th percentile1373
Maximum1400
Range824
Interquartile range (IQR)46

Descriptive statistics

Standard deviation231.88934
Coefficient of variation (CV)0.23315616
Kurtosis-0.2916151
Mean994.56667
Median Absolute Deviation (MAD)33.5
Skewness0.090198212
Sum29837
Variance53772.668
MonotonicityNot monotonic
2023-12-12T21:23:36.091177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1340 4
 
13.3%
998 3
 
10.0%
1000 2
 
6.7%
997 2
 
6.7%
999 2
 
6.7%
1400 2
 
6.7%
961 1
 
3.3%
1010 1
 
3.3%
669 1
 
3.3%
665 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
576 1
3.3%
640 1
3.3%
650 1
3.3%
657 1
3.3%
665 1
3.3%
669 1
3.3%
960 1
3.3%
961 1
3.3%
963 1
3.3%
965 1
3.3%
ValueCountFrequency (%)
1400 2
6.7%
1340 4
13.3%
1011 1
 
3.3%
1010 1
 
3.3%
1000 2
6.7%
999 2
6.7%
998 3
10.0%
997 2
6.7%
994 1
 
3.3%
993 1
 
3.3%

최초설계 순용량(MWe)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean973.8
Minimum558
Maximum1400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:23:36.241635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum558
5-th percentile629.25
Q1903
median950
Q3997.25
95-th percentile1400
Maximum1400
Range842
Interquartile range (IQR)94.25

Descriptive statistics

Standard deviation250.73057
Coefficient of variation (CV)0.25747646
Kurtosis-0.2842994
Mean973.8
Median Absolute Deviation (MAD)47
Skewness0.51197136
Sum29214
Variance62865.821
MonotonicityNot monotonic
2023-12-12T21:23:36.380854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
950 10
33.3%
1400 6
20.0%
903 5
16.7%
558 1
 
3.3%
618 1
 
3.3%
1001 1
 
3.3%
998 1
 
3.3%
995 1
 
3.3%
643 1
 
3.3%
652 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
558 1
 
3.3%
618 1
 
3.3%
643 1
 
3.3%
652 1
 
3.3%
665 1
 
3.3%
669 1
 
3.3%
903 5
16.7%
950 10
33.3%
995 1
 
3.3%
998 1
 
3.3%
ValueCountFrequency (%)
1400 6
20.0%
1001 1
 
3.3%
998 1
 
3.3%
995 1
 
3.3%
950 10
33.3%
903 5
16.7%
669 1
 
3.3%
665 1
 
3.3%
652 1
 
3.3%
643 1
 
3.3%

원자로 공급자
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
DOOSAN
12 
West
6 
Hanjung
2 
Hanjung;West
2 
Fram
2 
Other values (4)
6 

Length

Max length15
Median length12
Mean length6.4333333
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st rowWest
2nd rowWest
3rd rowHanjung
4th rowHanjung
5th rowHanjung;West

Common Values

ValueCountFrequency (%)
DOOSAN 12
40.0%
West 6
20.0%
Hanjung 2
 
6.7%
Hanjung;West 2
 
6.7%
Fram 2
 
6.7%
KHIC 2
 
6.7%
AECL;Hanjung 2
 
6.7%
AECL 1
 
3.3%
AECL;KHIC;KAERI 1
 
3.3%

Length

2023-12-12T21:23:36.554148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:23:36.706834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
doosan 12
40.0%
west 6
20.0%
hanjung 2
 
6.7%
hanjung;west 2
 
6.7%
fram 2
 
6.7%
khic 2
 
6.7%
aecl;hanjung 2
 
6.7%
aecl 1
 
3.3%
aecl;khic;kaeri 1
 
3.3%

착공일
Date

MISSING 

Distinct28
Distinct (%)100.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
Minimum1972-04-27 00:00:00
Maximum2013-06-19 00:00:00
2023-12-12T21:23:36.857475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:36.994147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

운영허가일
Date

MISSING 

Distinct26
Distinct (%)96.3%
Missing3
Missing (%)10.0%
Memory size372.0 B
Minimum1972-05-31 00:00:00
Maximum2021-07-09 00:00:00
2023-12-12T21:23:37.126837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:37.299540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

임계일
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing4
Missing (%)13.3%
Memory size372.0 B
Minimum1977-06-19 00:00:00
Maximum2019-04-08 00:00:00
2023-12-12T21:23:37.439497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:37.576269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

상업운전일
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing4
Missing (%)13.3%
Memory size372.0 B
Minimum1978-04-29 00:00:00
Maximum2019-08-29 00:00:00
2023-12-12T21:23:37.715568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:37.863686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

정지일
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing28
Missing (%)93.3%
Memory size372.0 B
Minimum2017-06-18 00:00:00
Maximum2019-12-24 00:00:00
2023-12-12T21:23:37.987989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:38.099140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

운영상태
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
운영
24 
건설
3 
정지
 
2
시운전
 
1

Length

Max length3
Median length2
Mean length2.0333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
운영 24
80.0%
건설 3
 
10.0%
정지 2
 
6.7%
시운전 1
 
3.3%

Length

2023-12-12T21:23:38.235816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:23:38.368086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 24
80.0%
건설 3
 
10.0%
정지 2
 
6.7%
시운전 1
 
3.3%

Interactions

2023-12-12T21:23:33.530289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:32.867004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.209146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.629860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:32.984534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.329589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.758197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.085998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:33.425776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:23:38.460244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
원전명노형총용량(MWe)순용량(MWe)최초설계 순용량(MWe)원자로 공급자착공일운영허가일임계일상업운전일정지일운영상태
원전명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
노형1.0001.0000.9760.7461.0001.0001.0001.0001.0001.0000.0000.000
총용량(MWe)1.0000.9761.0001.0000.8310.7521.0001.0001.0001.000NaN0.779
순용량(MWe)1.0000.7461.0001.0000.9550.8441.0001.0001.0001.000NaN0.513
최초설계 순용량(MWe)1.0001.0000.8310.9551.0000.6231.0000.8781.0001.000NaN0.471
원자로 공급자1.0001.0000.7520.8440.6231.0001.0001.0001.0001.0000.0000.000
착공일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
운영허가일1.0001.0001.0001.0000.8781.0001.0001.0001.0001.0000.0001.000
임계일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
상업운전일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
정지일0.0000.000NaNNaNNaN0.0000.0000.0000.0000.0001.000NaN
운영상태1.0000.0000.7790.5130.4710.0001.0001.0001.0001.000NaN1.000
2023-12-12T21:23:39.013047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노형원자로 공급자운영상태
노형1.0000.8660.000
원자로 공급자0.8661.0000.000
운영상태0.0000.0001.000
2023-12-12T21:23:39.124732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총용량(MWe)순용량(MWe)최초설계 순용량(MWe)노형원자로 공급자운영상태
총용량(MWe)1.0000.8590.8890.7280.5000.464
순용량(MWe)0.8591.0000.8990.7710.6110.494
최초설계 순용량(MWe)0.8890.8991.0000.9450.4240.440
노형0.7280.7710.9451.0000.8660.000
원자로 공급자0.5000.6110.4240.8661.0000.000
운영상태0.4640.4940.4400.0000.0001.000

Missing values

2023-12-12T21:23:33.937825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:23:34.169018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T21:23:34.345829image/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

원전명노형총용량(MWe)순용량(MWe)최초설계 순용량(MWe)원자로 공급자착공일운영허가일임계일상업운전일정지일운영상태
0Hanbit-1PWR1000961903West1981-06-041985-12-231986-01-311986-08-25<NA>운영
1Hanbit-2PWR993977903West1981-12-101986-09-121986-10-151987-06-10<NA>운영
2Hanbit-3PWR10501000950Hanjung1989-12-231994-09-091994-10-131995-03-31<NA>운영
3Hanbit-4PWR1049998950Hanjung1990-05-261995-06-021995-07-071996-01-01<NA>운영
4Hanbit-5PWR1053994950Hanjung;West1997-06-292001-10-242001-11-242002-05-21<NA>운영
5Hanbit-6PWR1052993950Hanjung;West1997-11-202002-07-312002-09-012002-12-24<NA>운영
6Hanul-1PWR1003963903Fram1983-01-261987-12-231988-02-251988-09-10<NA>운영
7Hanul-2PWR1008965903Fram1983-07-051988-12-291989-02-251989-09-30<NA>운영
8Hanul-3PWR1050997950KHIC1993-07-211997-11-081997-12-211998-08-11<NA>운영
9Hanul-4PWR1053999950KHIC1993-11-011998-10-291998-12-141999-12-31<NA>운영
원전명노형총용량(MWe)순용량(MWe)최초설계 순용량(MWe)원자로 공급자착공일운영허가일임계일상업운전일정지일운영상태
20Shin-Kori-3PWR140013401400DOOSAN2008-10-162015-10-292015-12-292016-12-20<NA>운영
21Shin-Kori-4PWR140013401400DOOSAN2009-08-192019-02-012019-04-082019-08-29<NA>운영
22Shin-Kori-5PWR140013401400DOOSAN<NA><NA><NA><NA><NA>건설
23Shin-Kori-6PWR140013401400DOOSAN<NA><NA><NA><NA><NA>건설
24Shin-Wolsong-1PWR10451000950DOOSAN2007-11-202011-12-022012-01-072012-07-31<NA>운영
25Shin-Wolsong-2PWR1000960950DOOSAN2008-09-232014-11-142015-02-082015-07-24<NA>운영
26Wolsong-1PHWR685657643AECL1977-10-301978-02-151982-11-211983-04-222019-12-24정지
27Wolsong-2PHWR675650652AECL;KHIC;KAERI1992-06-221996-11-021997-01-291997-07-01<NA>운영
28Wolsong-3PHWR688665665AECL;Hanjung1994-03-171997-12-301998-02-191998-07-01<NA>운영
29Wolsong-4PHWR691669669AECL;Hanjung1994-07-221999-02-081999-04-101999-10-01<NA>운영