Overview

Dataset statistics

Number of variables7
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory65.2 B

Variable types

Text1
Numeric6

Dataset

Description세계 신규원전 건설 시장 현황에 대한 데이터로 국가별 원전 건설 현황과 건설계획(용량, 호기수 포함) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15086941/fileData.do

Alerts

건설중(호기) is highly overall correlated with 건설중(용량_ 메가와트)(MWe) and 2 other fieldsHigh correlation
건설중(용량_ 메가와트)(MWe) is highly overall correlated with 건설중(호기) and 2 other fieldsHigh correlation
건설계획(호기) is highly overall correlated with 건설계획(용량_ 메가와트)(MWe)High correlation
건설계획(용량_ 메가와트)(MWe) is highly overall correlated with 건설계획(호기)High correlation
건설검토중(호기) is highly overall correlated with 건설중(호기) and 2 other fieldsHigh correlation
건설검토중(용량_ 메가와트)(MWe) is highly overall correlated with 건설중(호기) and 2 other fieldsHigh correlation
국가명 has unique valuesUnique
건설중(호기) has 23 (56.1%) zerosZeros
건설중(용량_ 메가와트)(MWe) has 23 (56.1%) zerosZeros
건설계획(호기) has 26 (63.4%) zerosZeros
건설계획(용량_ 메가와트)(MWe) has 26 (63.4%) zerosZeros
건설검토중(호기) has 10 (24.4%) zerosZeros
건설검토중(용량_ 메가와트)(MWe) has 10 (24.4%) zerosZeros

Reproduction

Analysis started2023-12-12 06:26:17.831071
Analysis finished2023-12-12 06:26:22.286526
Duration4.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가명
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T15:26:22.463128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.4390244
Min length2

Characters and Unicode

Total characters141
Distinct characters80
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row아르헨티나
2nd row아르메니아
3rd row방글라데시
4th row벨라루스
5th row벨기에
ValueCountFrequency (%)
아르헨티나 1
 
2.4%
리투아니아 1
 
2.4%
네덜란드 1
 
2.4%
파키스탄 1
 
2.4%
폴란드 1
 
2.4%
루마니아 1
 
2.4%
러시아 1
 
2.4%
사우디아라비아 1
 
2.4%
슬로바키아 1
 
2.4%
슬로베니아 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T15:26:22.856036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 13
 
9.2%
스 9
 
6.4%
라 5
 
3.5%
니 4
 
2.8%
란 4
 
2.8%
국 4
 
2.8%
키 4
 
2.8%
르 3
 
2.1%
나 3
 
2.1%
리 3
 
2.1%
Other values (70) 89
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138
97.9%
Uppercase Letter 3
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 13
 
9.4%
스 9
 
6.5%
라 5
 
3.6%
니 4
 
2.9%
란 4
 
2.9%
국 4
 
2.9%
키 4
 
2.9%
르 3
 
2.2%
나 3
 
2.2%
리 3
 
2.2%
Other values (67) 86
62.3%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138
97.9%
Latin 3
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 13
 
9.4%
스 9
 
6.5%
라 5
 
3.6%
니 4
 
2.9%
란 4
 
2.9%
국 4
 
2.9%
키 4
 
2.9%
르 3
 
2.2%
나 3
 
2.2%
리 3
 
2.2%
Other values (67) 86
62.3%
Latin
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138
97.9%
ASCII 3
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 13
 
9.4%
스 9
 
6.5%
라 5
 
3.6%
니 4
 
2.9%
란 4
 
2.9%
국 4
 
2.9%
키 4
 
2.9%
르 3
 
2.2%
나 3
 
2.2%
리 3
 
2.2%
Other values (67) 86
62.3%
ASCII
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

건설중(호기)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4146341
Minimum0
Maximum22
Zeros23
Zeros (%)56.1%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:23.006269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum22
Range22
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.6330126
Coefficient of variation (CV)2.5681641
Kurtosis27.042538
Mean1.4146341
Median Absolute Deviation (MAD)0
Skewness4.9160907
Sum58
Variance13.19878
MonotonicityNot monotonic
2023-12-12T15:26:23.165493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 23
56.1%
1 8
 
19.5%
2 5
 
12.2%
3 2
 
4.9%
22 1
 
2.4%
8 1
 
2.4%
4 1
 
2.4%
ValueCountFrequency (%)
0 23
56.1%
1 8
 
19.5%
2 5
 
12.2%
3 2
 
4.9%
4 1
 
2.4%
8 1
 
2.4%
22 1
 
2.4%
ValueCountFrequency (%)
22 1
 
2.4%
8 1
 
2.4%
4 1
 
2.4%
3 2
 
4.9%
2 5
 
12.2%
1 8
 
19.5%
0 23
56.1%

건설중(용량_ 메가와트)(MWe)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1576.6585
Minimum0
Maximum24781
Zeros23
Zeros (%)56.1%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:23.333942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31650
95-th percentile4800
Maximum24781
Range24781
Interquartile range (IQR)1650

Descriptive statistics

Standard deviation4034.8106
Coefficient of variation (CV)2.5590897
Kurtosis28.648685
Mean1576.6585
Median Absolute Deviation (MAD)0
Skewness5.0398644
Sum64643
Variance16279696
MonotonicityNot monotonic
2023-12-12T15:26:23.468713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 23
56.1%
2400 2
 
4.9%
29 1
 
2.4%
2810 1
 
2.4%
1250 1
 
2.4%
3440 1
 
2.4%
1400 1
 
2.4%
1900 1
 
2.4%
4800 1
 
2.4%
471 1
 
2.4%
Other values (8) 8
 
19.5%
ValueCountFrequency (%)
0 23
56.1%
29 1
 
2.4%
471 1
 
2.4%
1057 1
 
2.4%
1194 1
 
2.4%
1250 1
 
2.4%
1400 1
 
2.4%
1405 1
 
2.4%
1650 1
 
2.4%
1900 1
 
2.4%
ValueCountFrequency (%)
24781 1
2.4%
6700 1
2.4%
4800 1
2.4%
4200 1
2.4%
3440 1
2.4%
2810 1
2.4%
2756 1
2.4%
2400 2
4.9%
1900 1
2.4%
1650 1
2.4%

건설계획(호기)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4878049
Minimum0
Maximum46
Zeros26
Zeros (%)63.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:23.582613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile12
Maximum46
Range46
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.1643186
Coefficient of variation (CV)3.2817359
Kurtosis21.936927
Mean2.4878049
Median Absolute Deviation (MAD)0
Skewness4.5508778
Sum102
Variance66.656098
MonotonicityNot monotonic
2023-12-12T15:26:23.709666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 26
63.4%
1 6
 
14.6%
2 5
 
12.2%
46 1
 
2.4%
12 1
 
2.4%
25 1
 
2.4%
3 1
 
2.4%
ValueCountFrequency (%)
0 26
63.4%
1 6
 
14.6%
2 5
 
12.2%
3 1
 
2.4%
12 1
 
2.4%
25 1
 
2.4%
46 1
 
2.4%
ValueCountFrequency (%)
46 1
 
2.4%
25 1
 
2.4%
12 1
 
2.4%
3 1
 
2.4%
2 5
 
12.2%
1 6
 
14.6%
0 26
63.4%

건설계획(용량_ 메가와트)(MWe)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2557.9756
Minimum0
Maximum51660
Zeros26
Zeros (%)63.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:23.863031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31170
95-th percentile8400
Maximum51660
Range51660
Interquartile range (IQR)1170

Descriptive statistics

Standard deviation8760.0671
Coefficient of variation (CV)3.4246093
Kurtosis26.400139
Mean2557.9756
Median Absolute Deviation (MAD)0
Skewness4.9788562
Sum104877
Variance76738775
MonotonicityNot monotonic
2023-12-12T15:26:24.004344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 26
63.4%
2400 3
 
7.3%
1150 1
 
2.4%
1000 1
 
2.4%
51660 1
 
2.4%
1200 1
 
2.4%
8400 1
 
2.4%
1057 1
 
2.4%
1385 1
 
2.4%
1170 1
 
2.4%
Other values (4) 4
 
9.8%
ValueCountFrequency (%)
0 26
63.4%
1000 1
 
2.4%
1057 1
 
2.4%
1140 1
 
2.4%
1150 1
 
2.4%
1170 1
 
2.4%
1200 1
 
2.4%
1385 1
 
2.4%
2400 3
 
7.3%
2550 1
 
2.4%
ValueCountFrequency (%)
51660 1
 
2.4%
23525 1
 
2.4%
8400 1
 
2.4%
3440 1
 
2.4%
2550 1
 
2.4%
2400 3
7.3%
1385 1
 
2.4%
1200 1
 
2.4%
1170 1
 
2.4%
1150 1
 
2.4%

건설검토중(호기)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9268293
Minimum0
Maximum156
Zeros10
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:24.145326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q36
95-th percentile21
Maximum156
Range156
Interquartile range (IQR)5

Descriptive statistics

Standard deviation24.443189
Coefficient of variation (CV)3.0836024
Kurtosis35.902798
Mean7.9268293
Median Absolute Deviation (MAD)2
Skewness5.8469855
Sum325
Variance597.46951
MonotonicityNot monotonic
2023-12-12T15:26:24.290818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 10
24.4%
2 9
22.0%
1 5
12.2%
3 3
 
7.3%
6 3
 
7.3%
8 3
 
7.3%
4 1
 
2.4%
156 1
 
2.4%
28 1
 
2.4%
5 1
 
2.4%
Other values (4) 4
 
9.8%
ValueCountFrequency (%)
0 10
24.4%
1 5
12.2%
2 9
22.0%
3 3
 
7.3%
4 1
 
2.4%
5 1
 
2.4%
6 3
 
7.3%
8 3
 
7.3%
9 1
 
2.4%
10 1
 
2.4%
ValueCountFrequency (%)
156 1
 
2.4%
28 1
 
2.4%
21 1
 
2.4%
18 1
 
2.4%
10 1
 
2.4%
9 1
 
2.4%
8 3
7.3%
6 3
7.3%
5 1
 
2.4%
4 1
 
2.4%

건설검토중(용량_ 메가와트)(MWe)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8793.9512
Minimum0
Maximum177550
Zeros10
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:26:24.469710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1100
median2400
Q38000
95-th percentile20100
Maximum177550
Range177550
Interquartile range (IQR)7900

Descriptive statistics

Standard deviation27794.622
Coefficient of variation (CV)3.1606523
Kurtosis36.256139
Mean8793.9512
Median Absolute Deviation (MAD)2400
Skewness5.8841423
Sum360552
Variance7.7254101 × 108
MonotonicityNot monotonic
2023-12-12T15:26:24.645008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 10
24.4%
2400 3
 
7.3%
3000 2
 
4.9%
1350 1
 
2.4%
2000 1
 
2.4%
8000 1
 
2.4%
17000 1
 
2.4%
11250 1
 
2.4%
10500 1
 
2.4%
9600 1
 
2.4%
Other values (19) 19
46.3%
ValueCountFrequency (%)
0 10
24.4%
100 1
 
2.4%
600 1
 
2.4%
720 1
 
2.4%
1000 1
 
2.4%
1060 1
 
2.4%
1200 1
 
2.4%
1350 1
 
2.4%
1500 1
 
2.4%
2000 1
 
2.4%
ValueCountFrequency (%)
177550 1
2.4%
32000 1
2.4%
20100 1
2.4%
17000 1
2.4%
11562 1
2.4%
11250 1
2.4%
10500 1
2.4%
9900 1
2.4%
9600 1
2.4%
8400 1
2.4%

Interactions

2023-12-12T15:26:21.392246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.082295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.757520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.343768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.928344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.804407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.479765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.169792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.838926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.454651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.011027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.908806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.590599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.291250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.921503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.551822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.391473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.994530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.691771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.397157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.001451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.627621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.479190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.076125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.809045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.518415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.079573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.736349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.569223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.171631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.939391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:18.655726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.208951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:19.835666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:20.699844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:26:21.289110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:26:24.784050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가명건설중(호기)건설중(용량_ 메가와트)(MWe)건설계획(호기)건설계획(용량_ 메가와트)(MWe)건설검토중(호기)건설검토중(용량_ 메가와트)(MWe)
국가명1.0001.0001.0001.0001.0001.0001.000
건설중(호기)1.0001.0000.9970.9910.9910.7710.832
건설중(용량_ 메가와트)(MWe)1.0000.9971.0000.9860.9860.7580.814
건설계획(호기)1.0000.9910.9861.0001.0000.8321.000
건설계획(용량_ 메가와트)(MWe)1.0000.9910.9861.0001.0000.8321.000
건설검토중(호기)1.0000.7710.7580.8320.8321.0000.994
건설검토중(용량_ 메가와트)(MWe)1.0000.8320.8141.0001.0000.9941.000
2023-12-12T15:26:24.934068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건설중(호기)건설중(용량_ 메가와트)(MWe)건설계획(호기)건설계획(용량_ 메가와트)(MWe)건설검토중(호기)건설검토중(용량_ 메가와트)(MWe)
건설중(호기)1.0000.9940.3570.3810.5950.601
건설중(용량_ 메가와트)(MWe)0.9941.0000.3470.3740.6040.616
건설계획(호기)0.3570.3471.0000.9910.3380.301
건설계획(용량_ 메가와트)(MWe)0.3810.3740.9911.0000.3550.324
건설검토중(호기)0.5950.6040.3380.3551.0000.979
건설검토중(용량_ 메가와트)(MWe)0.6010.6160.3010.3240.9791.000

Missing values

2023-12-12T15:26:22.067734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:26:22.232412image/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

국가명건설중(호기)건설중(용량_ 메가와트)(MWe)건설계획(호기)건설계획(용량_ 메가와트)(MWe)건설검토중(호기)건설검토중(용량_ 메가와트)(MWe)
0아르헨티나1291115021350
1아르메니아000011060
2방글라데시224000022400
3벨라루스111940022400
4벨기에000000
5브라질114050044000
6불가리아001100033000
7캐나다000021500
8중국22247814651660156177550
9체코001120033600
국가명건설중(호기)건설중(용량_ 메가와트)(MWe)건설계획(호기)건설계획(용량_ 메가와트)(MWe)건설검토중(호기)건설검토중(용량_ 메가와트)(MWe)
31남아공000089600
32스페인000000
33스웨덴000000
34스위스000000
35터키4480000810500
36우크라이나2190000911250
37UAE114000000
38영국23440234401017000
39미국1125032550188000
40우즈베키스탄002240022400