Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory59.7 B

Variable types

Numeric6

Dataset

Description한국산업표준 기본현황 및 표준활동에 대한 통계정보 : 연도별 한국산업표준(KS) 현황 (연도,제정,개정,확인,폐지,보유표준수)
URLhttps://www.data.go.kr/data/15065278/fileData.do

Alerts

연도 is highly overall correlated with 제정 and 1 other fieldsHigh correlation
제정 is highly overall correlated with 연도High correlation
확인 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
보유표준수 is highly overall correlated with 확인High correlation
연도 has unique valuesUnique
제정 has unique valuesUnique
확인 has unique valuesUnique
보유표준수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:15:36.494233
Analysis finished2023-12-12 22:15:39.928413
Duration3.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011
Minimum2000
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:40.018837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001.1
Q12005.5
median2011
Q32016.5
95-th percentile2020.9
Maximum2022
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.0033726156
Kurtosis-1.2
Mean2011
Median Absolute Deviation (MAD)6
Skewness0
Sum46253
Variance46
MonotonicityStrictly increasing
2023-12-13T07:15:40.139876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2000 1
 
4.3%
2001 1
 
4.3%
2022 1
 
4.3%
2021 1
 
4.3%
2020 1
 
4.3%
2019 1
 
4.3%
2018 1
 
4.3%
2017 1
 
4.3%
2016 1
 
4.3%
2015 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
2000 1
4.3%
2001 1
4.3%
2002 1
4.3%
2003 1
4.3%
2004 1
4.3%
2005 1
4.3%
2006 1
4.3%
2007 1
4.3%
2008 1
4.3%
2009 1
4.3%
ValueCountFrequency (%)
2022 1
4.3%
2021 1
4.3%
2020 1
4.3%
2019 1
4.3%
2018 1
4.3%
2017 1
4.3%
2016 1
4.3%
2015 1
4.3%
2014 1
4.3%
2013 1
4.3%

제정
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean879
Minimum170
Maximum3616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:40.292437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170
5-th percentile191
Q1348.5
median469
Q3988.5
95-th percentile3026.6
Maximum3616
Range3446
Interquartile range (IQR)640

Descriptive statistics

Standard deviation922.60087
Coefficient of variation (CV)1.0496028
Kurtosis3.5969733
Mean879
Median Absolute Deviation (MAD)159
Skewness2.0153907
Sum20217
Variance851192.36
MonotonicityNot monotonic
2023-12-13T07:15:40.448600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
290 1
 
4.3%
1343 1
 
4.3%
356 1
 
4.3%
469 1
 
4.3%
310 1
 
4.3%
364 1
 
4.3%
441 1
 
4.3%
341 1
 
4.3%
311 1
 
4.3%
170 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
170 1
4.3%
180 1
4.3%
290 1
4.3%
310 1
4.3%
311 1
4.3%
341 1
4.3%
356 1
4.3%
361 1
4.3%
364 1
4.3%
411 1
4.3%
ValueCountFrequency (%)
3616 1
4.3%
3142 1
4.3%
1988 1
4.3%
1656 1
4.3%
1343 1
4.3%
995 1
4.3%
982 1
4.3%
916 1
4.3%
567 1
4.3%
525 1
4.3%

개정
Real number (ℝ)

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1444.6957
Minimum427
Maximum2558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:40.558466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum427
5-th percentile860.7
Q11208.5
median1482
Q31616.5
95-th percentile2143
Maximum2558
Range2131
Interquartile range (IQR)408

Descriptive statistics

Standard deviation443.53153
Coefficient of variation (CV)0.3070069
Kurtosis1.4723117
Mean1444.6957
Median Absolute Deviation (MAD)164
Skewness0.2187747
Sum33228
Variance196720.22
MonotonicityNot monotonic
2023-12-13T07:15:40.663808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1518 2
 
8.7%
427 1
 
4.3%
847 1
 
4.3%
1587 1
 
4.3%
1646 1
 
4.3%
1325 1
 
4.3%
1356 1
 
4.3%
1392 1
 
4.3%
1407 1
 
4.3%
1482 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
427 1
4.3%
847 1
4.3%
984 1
4.3%
1029 1
4.3%
1050 1
4.3%
1092 1
4.3%
1325 1
4.3%
1356 1
4.3%
1392 1
4.3%
1407 1
4.3%
ValueCountFrequency (%)
2558 1
4.3%
2171 1
4.3%
1891 1
4.3%
1810 1
4.3%
1694 1
4.3%
1646 1
4.3%
1587 1
4.3%
1518 2
8.7%
1510 1
4.3%
1508 1
4.3%

확인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2343.2609
Minimum600
Maximum4681
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:40.791293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600
5-th percentile705.3
Q11621.5
median2323
Q33134.5
95-th percentile3652.6
Maximum4681
Range4081
Interquartile range (IQR)1513

Descriptive statistics

Standard deviation1060.2668
Coefficient of variation (CV)0.45247492
Kurtosis-0.38402122
Mean2343.2609
Median Absolute Deviation (MAD)769
Skewness0.12394521
Sum53895
Variance1124165.7
MonotonicityNot monotonic
2023-12-13T07:15:40.909620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1456 1
 
4.3%
1554 1
 
4.3%
3227 1
 
4.3%
2942 1
 
4.3%
2068 1
 
4.3%
2549 1
 
4.3%
2733 1
 
4.3%
3505 1
 
4.3%
1963 1
 
4.3%
1689 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
600 1
4.3%
702 1
4.3%
735 1
4.3%
1108 1
4.3%
1456 1
4.3%
1554 1
4.3%
1689 1
4.3%
1963 1
4.3%
2010 1
4.3%
2059 1
4.3%
ValueCountFrequency (%)
4681 1
4.3%
3669 1
4.3%
3505 1
4.3%
3441 1
4.3%
3351 1
4.3%
3227 1
4.3%
3042 1
4.3%
2942 1
4.3%
2733 1
4.3%
2549 1
4.3%

폐지
Real number (ℝ)

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean407.73913
Minimum41
Maximum3827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:41.059470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile110.1
Q1137
median208
Q3301
95-th percentile905.9
Maximum3827
Range3786
Interquartile range (IQR)164

Descriptive statistics

Standard deviation768.92867
Coefficient of variation (CV)1.8858349
Kurtosis19.928455
Mean407.73913
Median Absolute Deviation (MAD)78
Skewness4.3660388
Sum9378
Variance591251.29
MonotonicityNot monotonic
2023-12-13T07:15:41.200781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
137 2
 
8.7%
41 1
 
4.3%
319 1
 
4.3%
130 1
 
4.3%
176 1
 
4.3%
127 1
 
4.3%
216 1
 
4.3%
208 1
 
4.3%
554 1
 
4.3%
298 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
41 1
4.3%
110 1
4.3%
111 1
4.3%
127 1
4.3%
130 1
4.3%
137 2
8.7%
176 1
4.3%
181 1
4.3%
182 1
4.3%
188 1
4.3%
ValueCountFrequency (%)
3827 1
4.3%
945 1
4.3%
554 1
4.3%
446 1
4.3%
319 1
4.3%
304 1
4.3%
298 1
4.3%
270 1
4.3%
257 1
4.3%
216 1
4.3%

보유표준수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20291.304
Minimum10845
Maximum24129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T07:15:41.334913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10845
5-th percentile12323
Q120215.5
median20734
Q322409
95-th percentile23892.9
Maximum24129
Range13284
Interquartile range (IQR)2193.5

Descriptive statistics

Standard deviation3428.5833
Coefficient of variation (CV)0.16896811
Kurtosis2.6384591
Mean20291.304
Median Absolute Deviation (MAD)869
Skewness-1.6570185
Sum466700
Variance11755183
MonotonicityNot monotonic
2023-12-13T07:15:41.469726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
10845 1
 
4.3%
12006 1
 
4.3%
21436 1
 
4.3%
21199 1
 
4.3%
20916 1
 
4.3%
20734 1
 
4.3%
20507 1
 
4.3%
20282 1
 
4.3%
20149 1
 
4.3%
20392 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
10845 1
4.3%
12006 1
4.3%
15176 1
4.3%
18014 1
4.3%
19865 1
4.3%
20149 1
4.3%
20282 1
4.3%
20392 1
4.3%
20482 1
4.3%
20507 1
4.3%
ValueCountFrequency (%)
24129 1
4.3%
23923 1
4.3%
23622 1
4.3%
23372 1
4.3%
23062 1
4.3%
22760 1
4.3%
22058 1
4.3%
21436 1
4.3%
21251 1
4.3%
21199 1
4.3%

Interactions

2023-12-13T07:15:39.243559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:36.654189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.084627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.828069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.243957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.755601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.313869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:36.724599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.172256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.887794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.313109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.831297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.404355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:36.800297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.268492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.965353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.388986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.910843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.473599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:36.866663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.354744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.021040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.458804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.980680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.578657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:36.939956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.437108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.090039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.545425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.076179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.674712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.015393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:37.525311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.170411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:38.659976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:15:39.154538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:15:41.558412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도제정개정확인폐지보유표준수
연도1.0000.5860.6410.4470.4730.709
제정0.5861.0000.7680.7620.0000.944
개정0.6410.7681.0000.0000.9780.213
확인0.4470.7620.0001.0000.4760.719
폐지0.4730.0000.9780.4761.0000.000
보유표준수0.7090.9440.2130.7190.0001.000
2023-12-13T07:15:41.677218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도제정개정확인폐지보유표준수
연도1.000-0.5810.0500.550-0.0460.284
제정-0.5811.0000.415-0.4280.222-0.023
개정0.0500.4151.0000.0790.3760.181
확인0.550-0.4280.0791.000-0.0750.607
폐지-0.0460.2220.376-0.0751.000-0.191
보유표준수0.284-0.0230.1810.607-0.1911.000

Missing values

2023-12-13T07:15:39.784090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:15:39.889201image/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

연도제정개정확인폐지보유표준수
0200029042714564110845
1200113431426155418212006
2200236161810110844615176
320033142151860030418014
420041988102970213719865
520051656109273527021251
620069951694205918822058
720079162558335121422760
820084831891304218123062
920095671508232325723372
연도제정개정확인폐지보유표준수
1320131808473669382720482
1420149822171201094520520
1520151701510168929820392
1620163111482196355420149
1720173411407350520820282
1820184411392273321620507
1920193641356254913720734
2020203101325206812720916
2120214691646294217621199
2220223561587322713021436