Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory103.1 B

Variable types

Text1
Categorical10

Dataset

Description최근 10년간 가동중 원자로 정지현황(2021년 기준)
Author원자력안전위원회
URLhttps://www.data.go.kr/data/15102087/fileData.do

Alerts

2015 is highly imbalanced (57.5%)Imbalance
구 분 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:29:28.983404
Analysis finished2023-12-12 08:29:29.860720
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T17:29:29.965056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2307692
Min length6

Characters and Unicode

Total characters162
Distinct characters17
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

Unique26 ?
Unique (%)100.0%

Sample

1st row고리 1호기
2nd row고리 2호기
3rd row고리 3호기
4th row고리 4호기
5th row한울 1호기
ValueCountFrequency (%)
1호기 6
11.5%
2호기 6
11.5%
한울 6
11.5%
한빛 6
11.5%
3호기 5
9.6%
4호기 5
9.6%
고리 4
7.7%
월성 4
7.7%
신고리 4
7.7%
5호기 2
 
3.8%
Other values (2) 4
7.7%
2023-12-12T17:29:30.249438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
16.0%
호 26
16.0%
기 26
16.0%
한 12
 
7.4%
고 8
 
4.9%
리 8
 
4.9%
울 6
 
3.7%
빛 6
 
3.7%
성 6
 
3.7%
월 6
 
3.7%
Other values (7) 32
19.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
67.9%
Space Separator 26
 
16.0%
Decimal Number 26
 
16.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 26
23.6%
기 26
23.6%
한 12
10.9%
고 8
 
7.3%
리 8
 
7.3%
울 6
 
5.5%
빛 6
 
5.5%
성 6
 
5.5%
월 6
 
5.5%
신 6
 
5.5%
Decimal Number
ValueCountFrequency (%)
2 6
23.1%
1 6
23.1%
3 5
19.2%
4 5
19.2%
5 2
 
7.7%
6 2
 
7.7%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110
67.9%
Common 52
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 26
23.6%
기 26
23.6%
한 12
10.9%
고 8
 
7.3%
리 8
 
7.3%
울 6
 
5.5%
빛 6
 
5.5%
성 6
 
5.5%
월 6
 
5.5%
신 6
 
5.5%
Common
ValueCountFrequency (%)
26
50.0%
2 6
 
11.5%
1 6
 
11.5%
3 5
 
9.6%
4 5
 
9.6%
5 2
 
3.8%
6 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110
67.9%
ASCII 52
32.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
50.0%
2 6
 
11.5%
1 6
 
11.5%
3 5
 
9.6%
4 5
 
9.6%
5 2
 
3.8%
6 2
 
3.8%
Hangul
ValueCountFrequency (%)
호 26
23.6%
기 26
23.6%
한 12
10.9%
고 8
 
7.3%
리 8
 
7.3%
울 6
 
5.5%
빛 6
 
5.5%
성 6
 
5.5%
월 6
 
5.5%
신 6
 
5.5%

2012
Categorical

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
14 
1
5 
2
3 
<NA>
3 
3
 
1

Length

Max length4
Median length1
Mean length1.3461538
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 14
53.8%
1 5
 
19.2%
2 3
 
11.5%
<NA> 3
 
11.5%
3 1
 
3.8%

Length

2023-12-12T17:29:30.412675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:30.533198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 14
53.8%
1 5
 
19.2%
2 3
 
11.5%
na 3
 
11.5%
3 1
 
3.8%

2013
Categorical

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
17 
1
5 
<NA>
3 
2
 
1

Length

Max length4
Median length1
Mean length1.3461538
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st row1
2nd row0
3rd row0
4th row2
5th row1

Common Values

ValueCountFrequency (%)
0 17
65.4%
1 5
 
19.2%
<NA> 3
 
11.5%
2 1
 
3.8%

Length

2023-12-12T17:29:30.707256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:30.842888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
65.4%
1 5
 
19.2%
na 3
 
11.5%
2 1
 
3.8%

2014
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
16 
1
7 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3461538
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 16
61.5%
1 7
26.9%
<NA> 3
 
11.5%

Length

2023-12-12T17:29:30.991062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:31.134511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 16
61.5%
1 7
26.9%
na 3
 
11.5%

2015
Categorical

IMBALANCE 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
22 
1
 
2
2
 
1
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1153846
Min length1

Unique

Unique2 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 22
84.6%
1 2
 
7.7%
2 1
 
3.8%
<NA> 1
 
3.8%

Length

2023-12-12T17:29:31.257121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:31.381635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
84.6%
1 2
 
7.7%
2 1
 
3.8%
na 1
 
3.8%

2016
Categorical

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
17 
1
6 
3
 
1
5
 
1
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1153846
Min length1

Unique

Unique3 ?
Unique (%)11.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 17
65.4%
1 6
 
23.1%
3 1
 
3.8%
5 1
 
3.8%
<NA> 1
 
3.8%

Length

2023-12-12T17:29:31.541889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:31.655491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
65.4%
1 6
 
23.1%
3 1
 
3.8%
5 1
 
3.8%
na 1
 
3.8%

2017
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
21 
1
4 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1153846
Min length1

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 21
80.8%
1 4
 
15.4%
<NA> 1
 
3.8%

Length

2023-12-12T17:29:31.768799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:31.875224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
80.8%
1 4
 
15.4%
na 1
 
3.8%

2018
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
19 
1
4 
<NA>
3 

Length

Max length4
Median length1
Mean length1.3461538
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 19
73.1%
1 4
 
15.4%
<NA> 3
 
11.5%

Length

2023-12-12T17:29:31.994670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:32.092782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
73.1%
1 4
 
15.4%
na 3
 
11.5%

2019
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
20 
1
4 
<NA>
 
2

Length

Max length4
Median length1
Mean length1.2307692
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 20
76.9%
1 4
 
15.4%
<NA> 2
 
7.7%

Length

2023-12-12T17:29:32.212620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:32.322472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
76.9%
1 4
 
15.4%
na 2
 
7.7%

2020
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
18 
1
6 
<NA>
2 

Length

Max length4
Median length1
Mean length1.2307692
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 18
69.2%
1 6
 
23.1%
<NA> 2
 
7.7%

Length

2023-12-12T17:29:32.434328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:32.581820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
69.2%
1 6
 
23.1%
na 2
 
7.7%

2021
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
0
19 
1
5 
<NA>
2 

Length

Max length4
Median length1
Mean length1.2307692
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 19
73.1%
1 5
 
19.2%
<NA> 2
 
7.7%

Length

2023-12-12T17:29:32.700816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:32.804746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
73.1%
1 5
 
19.2%
na 2
 
7.7%

Correlations

2023-12-12T17:29:32.897651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분2012201320142015201620172018201920202021
구 분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
20121.0001.0000.1090.0000.0000.2520.0000.0000.0000.5720.000
20131.0000.1091.0000.0000.7640.0000.2370.0000.0000.2050.000
20141.0000.0000.0001.0000.1270.0000.0000.0000.0000.0000.000
20151.0000.0000.7640.1271.0000.0000.0060.0000.2410.0000.000
20161.0000.2520.0000.0000.0001.0000.6810.2700.0000.1650.045
20171.0000.0000.2370.0000.0060.6811.0000.0000.0000.0000.000
20181.0000.0000.0000.0000.0000.2700.0001.0000.0000.0000.000
20191.0000.0000.0000.0000.2410.0000.0000.0001.0000.0000.000
20201.0000.5720.2050.0000.0000.1650.0000.0000.0001.0000.000
20211.0000.0000.0000.0000.0000.0450.0000.0000.0000.0001.000
2023-12-12T17:29:33.064027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018201920172015202120142020201220132016
20181.0000.0000.0000.0000.0000.0000.0000.0000.0000.424
20190.0001.0000.0000.3790.0000.0000.0000.0000.0000.000
20170.0000.0001.0000.0000.0000.0000.0000.0000.3730.455
20150.0000.3790.0001.0000.0000.1950.0000.0000.4180.000
20210.0000.0000.0000.0001.0000.0000.0000.0000.0000.035
20140.0000.0000.0000.1950.0001.0000.0000.0000.0000.000
20200.0000.0000.0000.0000.0000.0001.0000.3630.3210.258
20120.0000.0000.0000.0000.0000.0000.3631.0000.0600.221
20130.0000.0000.3730.4180.0000.0000.3210.0601.0000.000
20160.4240.0000.4550.0000.0350.0000.2580.2210.0001.000
2023-12-12T17:29:33.209256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2012201320142015201620172018201920202021
20121.0000.0600.0000.0000.2210.0000.0000.0000.3630.000
20130.0601.0000.0000.4180.0000.3730.0000.0000.3210.000
20140.0000.0001.0000.1950.0000.0000.0000.0000.0000.000
20150.0000.4180.1951.0000.0000.0000.0000.3790.0000.000
20160.2210.0000.0000.0001.0000.4550.4240.0000.2580.035
20170.0000.3730.0000.0000.4551.0000.0000.0000.0000.000
20180.0000.0000.0000.0000.4240.0001.0000.0000.0000.000
20190.0000.0000.0000.3790.0000.0000.0001.0000.0000.000
20200.3630.3210.0000.0000.2580.0000.0000.0001.0000.000
20210.0000.0000.0000.0000.0350.0000.0000.0000.0001.000

Missing values

2023-12-12T17:29:29.635721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:29:29.800687image/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

구 분2012201320142015201620172018201920202021
0고리 1호기010000<NA><NA><NA><NA>
1고리 2호기0010000001
2고리 3호기0000000011
3고리 4호기0201010010
4한울 1호기1110100000
5한울 2호기1000001001
6한울 3호기0000000000
7한울 4호기0000001000
8한울 5호기0110110000
9한울 6호기0000001010
구 분2012201320142015201620172018201920202021
16한빛 3호기0011000000
17한빛 4호기0000000000
18한빛 5호기2000000010
19한빛 6호기1100000000
20신고리 1호기1010000011
21신고리 2호기2000000010
22신고리 3호기<NA><NA><NA>0501000
23신고리 4호기<NA><NA><NA><NA><NA><NA><NA>001
24신월성 1호기3100000000
25신월성 2호기<NA><NA><NA>0000100