Overview

Dataset statistics

Number of variables10
Number of observations224
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory89.6 B

Variable types

Text1
Numeric9

Dataset

Description참조표준데이터 년간 등록 건수 및 수집정보를 제공합니다. 플라즈마, 유기화합물, 태양, 품력 한국인 건강지수, 한국인 체열, 한국인 뇌파, 환경방사능 등의 참조표준을 구축하여 업데이트 한 내용입니다. CSV 파일로서 컬럼명은 년도, 수집건수, 유효데이터, 유효참조표준, 검증참조표준, 인증 참조표준 등으로 구성되어 있음
Author한국표준과학연구원
URLhttps://www.data.go.kr/data/15062649/fileData.do

Alerts

년도 is highly overall correlated with 유효데이터High correlation
수집 is highly overall correlated with 유효데이터High correlation
생산 is highly overall correlated with 유효데이터High correlation
유효데이터 is highly overall correlated with 년도 and 2 other fieldsHigh correlation
유효참조표준 is highly overall correlated with 제정High correlation
제정 is highly overall correlated with 유효참조표준High correlation
수집 has 173 (77.2%) zerosZeros
생산 has 135 (60.3%) zerosZeros
유효데이터 has 96 (42.9%) zerosZeros
유효참조표준 has 67 (29.9%) zerosZeros
검증참조표준 has 171 (76.3%) zerosZeros
인증참조표준 has 197 (87.9%) zerosZeros
제정 has 12 (5.4%) zerosZeros
개정 has 203 (90.6%) zerosZeros

Reproduction

Analysis started2023-12-12 08:09:53.742121
Analysis finished2023-12-12 08:10:03.864509
Duration10.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

DB 코드
Text

Distinct90
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T17:10:04.129042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.7455357
Min length3

Characters and Unicode

Total characters1959
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)24.6%

Sample

1st rowS02003001
2nd rowS05001001
3rd rowS03003001
4th rowS02001001
5th rowS03004001
ValueCountFrequency (%)
s02001001 14
 
6.2%
s01002001 12
 
5.4%
s01004001 11
 
4.9%
s10003001 9
 
4.0%
s02004001 7
 
3.1%
s03004001 7
 
3.1%
s10004001 7
 
3.1%
s10006001 7
 
3.1%
s13002001 6
 
2.7%
s01001001 6
 
2.7%
Other values (80) 138
61.6%
2023-12-12T17:10:04.659896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1062
54.2%
1 388
 
19.8%
S 198
 
10.1%
2 107
 
5.5%
3 74
 
3.8%
4 45
 
2.3%
5 33
 
1.7%
6 30
 
1.5%
8 14
 
0.7%
7 5
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1761
89.9%
Uppercase Letter 198
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1062
60.3%
1 388
 
22.0%
2 107
 
6.1%
3 74
 
4.2%
4 45
 
2.6%
5 33
 
1.9%
6 30
 
1.7%
8 14
 
0.8%
7 5
 
0.3%
9 3
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
S 198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1761
89.9%
Latin 198
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1062
60.3%
1 388
 
22.0%
2 107
 
6.1%
3 74
 
4.2%
4 45
 
2.6%
5 33
 
1.9%
6 30
 
1.7%
8 14
 
0.8%
7 5
 
0.3%
9 3
 
0.2%
Latin
ValueCountFrequency (%)
S 198
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1959
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1062
54.2%
1 388
 
19.8%
S 198
 
10.1%
2 107
 
5.5%
3 74
 
3.8%
4 45
 
2.3%
5 33
 
1.7%
6 30
 
1.5%
8 14
 
0.7%
7 5
 
0.3%

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.433
Minimum2007
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:04.824532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2008
Q12012
median2016
Q32019
95-th percentile2021
Maximum2021
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.1523647
Coefficient of variation (CV)0.0020602841
Kurtosis-1.0176398
Mean2015.433
Median Absolute Deviation (MAD)3
Skewness-0.35013306
Sum451457
Variance17.242132
MonotonicityNot monotonic
2023-12-12T17:10:04.977327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2021 26
11.6%
2020 25
11.2%
2017 21
9.4%
2014 17
 
7.6%
2019 17
 
7.6%
2015 17
 
7.6%
2016 15
 
6.7%
2010 14
 
6.2%
2013 14
 
6.2%
2018 14
 
6.2%
Other values (5) 44
19.6%
ValueCountFrequency (%)
2007 6
 
2.7%
2008 8
3.6%
2009 11
4.9%
2010 14
6.2%
2011 9
4.0%
2012 10
4.5%
2013 14
6.2%
2014 17
7.6%
2015 17
7.6%
2016 15
6.7%
ValueCountFrequency (%)
2021 26
11.6%
2020 25
11.2%
2019 17
7.6%
2018 14
6.2%
2017 21
9.4%
2016 15
6.7%
2015 17
7.6%
2014 17
7.6%
2013 14
6.2%
2012 10
 
4.5%

수집
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131305.29
Minimum0
Maximum22746857
Zeros173
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:05.143315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4926.8
Maximum22746857
Range22746857
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1530318.9
Coefficient of variation (CV)11.654662
Kurtosis216.69405
Mean131305.29
Median Absolute Deviation (MAD)0
Skewness14.613975
Sum29412386
Variance2.3418759 × 1012
MonotonicityNot monotonic
2023-12-12T17:10:05.319763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 173
77.2%
3000 3
 
1.3%
1381200 2
 
0.9%
66 2
 
0.9%
6000 2
 
0.9%
22 2
 
0.9%
1778 1
 
0.4%
3322 1
 
0.4%
235 1
 
0.4%
210 1
 
0.4%
Other values (36) 36
 
16.1%
ValueCountFrequency (%)
0 173
77.2%
3 1
 
0.4%
6 1
 
0.4%
22 2
 
0.9%
66 2
 
0.9%
70 1
 
0.4%
94 1
 
0.4%
130 1
 
0.4%
171 1
 
0.4%
210 1
 
0.4%
ValueCountFrequency (%)
22746857 1
0.4%
1394200 1
0.4%
1385100 1
0.4%
1381200 2
0.9%
999900 1
0.4%
55000 1
0.4%
7329 1
0.4%
6000 2
0.9%
5114 1
0.4%
4964 1
0.4%

생산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13937.487
Minimum0
Maximum1361300
Zeros135
Zeros (%)60.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:05.493589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q340
95-th percentile3268.5
Maximum1361300
Range1361300
Interquartile range (IQR)40

Descriptive statistics

Standard deviation119344.08
Coefficient of variation (CV)8.5628123
Kurtosis97.774026
Mean13937.487
Median Absolute Deviation (MAD)0
Skewness9.6932796
Sum3121997
Variance1.424301 × 1010
MonotonicityNot monotonic
2023-12-12T17:10:05.700370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 135
60.3%
20 4
 
1.8%
52 3
 
1.3%
1 3
 
1.3%
40 3
 
1.3%
8 3
 
1.3%
16 3
 
1.3%
2 2
 
0.9%
26 2
 
0.9%
10 2
 
0.9%
Other values (61) 64
28.6%
ValueCountFrequency (%)
0 135
60.3%
1 3
 
1.3%
2 2
 
0.9%
5 1
 
0.4%
8 3
 
1.3%
9 1
 
0.4%
10 2
 
0.9%
14 1
 
0.4%
16 3
 
1.3%
20 4
 
1.8%
ValueCountFrequency (%)
1361300 1
0.4%
1030600 1
0.4%
538200 1
0.4%
119900 1
0.4%
9135 1
0.4%
7819 2
0.9%
7770 1
0.4%
6205 1
0.4%
5274 1
0.4%
5252 1
0.4%

유효데이터
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118128.62
Minimum0
Maximum22747096
Zeros96
Zeros (%)42.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:05.902221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q3179
95-th percentile3011.25
Maximum22747096
Range22747096
Interquartile range (IQR)179

Descriptive statistics

Standard deviation1522914.4
Coefficient of variation (CV)12.892001
Kurtosis221.52284
Mean118128.62
Median Absolute Deviation (MAD)12
Skewness14.845759
Sum26460812
Variance2.3192682 × 1012
MonotonicityNot monotonic
2023-12-12T17:10:06.072507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 96
42.9%
20 4
 
1.8%
52 4
 
1.8%
16 4
 
1.8%
40 3
 
1.3%
30 3
 
1.3%
1 3
 
1.3%
10 3
 
1.3%
8 3
 
1.3%
33 2
 
0.9%
Other values (90) 99
44.2%
ValueCountFrequency (%)
0 96
42.9%
1 3
 
1.3%
2 2
 
0.9%
5 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
8 3
 
1.3%
9 2
 
0.9%
10 3
 
1.3%
14 1
 
0.4%
ValueCountFrequency (%)
22747096 1
0.4%
958500 1
0.4%
854300 2
0.9%
642200 1
0.4%
316700 1
0.4%
30000 1
0.4%
9135 1
0.4%
6205 1
0.4%
5274 1
0.4%
5252 1
0.4%

유효참조표준
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.84375
Minimum0
Maximum5820
Zeros67
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:06.274454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15.5
Q367
95-th percentile705.85
Maximum5820
Range5820
Interquartile range (IQR)67

Descriptive statistics

Standard deviation660.43309
Coefficient of variation (CV)3.8209834
Kurtosis43.539885
Mean172.84375
Median Absolute Deviation (MAD)15.5
Skewness6.2263363
Sum38717
Variance436171.87
MonotonicityNot monotonic
2023-12-12T17:10:06.421077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
29.9%
1 8
 
3.6%
15 6
 
2.7%
8 6
 
2.7%
16 5
 
2.2%
78 5
 
2.2%
2 5
 
2.2%
27 5
 
2.2%
63 4
 
1.8%
10 4
 
1.8%
Other values (76) 109
48.7%
ValueCountFrequency (%)
0 67
29.9%
1 8
 
3.6%
2 5
 
2.2%
3 1
 
0.4%
4 1
 
0.4%
5 4
 
1.8%
6 3
 
1.3%
7 2
 
0.9%
8 6
 
2.7%
9 1
 
0.4%
ValueCountFrequency (%)
5820 1
0.4%
5274 1
0.4%
3672 1
0.4%
2457 1
0.4%
2300 1
0.4%
1918 1
0.4%
1836 2
0.9%
1728 1
0.4%
1188 1
0.4%
864 1
0.4%

검증참조표준
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.272321
Minimum0
Maximum5252
Zeros171
Zeros (%)76.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:06.634947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile117.75
Maximum5252
Range5252
Interquartile range (IQR)0

Descriptive statistics

Standard deviation374.10037
Coefficient of variation (CV)6.8930232
Kurtosis169.33448
Mean54.272321
Median Absolute Deviation (MAD)0
Skewness12.405184
Sum12157
Variance139951.09
MonotonicityNot monotonic
2023-12-12T17:10:06.800686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 171
76.3%
20 3
 
1.3%
2 3
 
1.3%
21 2
 
0.9%
42 2
 
0.9%
4 2
 
0.9%
10 2
 
0.9%
24 2
 
0.9%
22 2
 
0.9%
45 2
 
0.9%
Other values (32) 33
 
14.7%
ValueCountFrequency (%)
0 171
76.3%
2 3
 
1.3%
4 2
 
0.9%
8 1
 
0.4%
9 2
 
0.9%
10 2
 
0.9%
12 1
 
0.4%
15 1
 
0.4%
16 1
 
0.4%
19 1
 
0.4%
ValueCountFrequency (%)
5252 1
0.4%
1227 1
0.4%
888 1
0.4%
864 1
0.4%
641 1
0.4%
568 1
0.4%
402 1
0.4%
329 1
0.4%
288 1
0.4%
264 1
0.4%

인증참조표준
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.392857
Minimum0
Maximum6205
Zeros197
Zeros (%)87.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:06.944076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41.9
Maximum6205
Range6205
Interquartile range (IQR)0

Descriptive statistics

Standard deviation420.27136
Coefficient of variation (CV)11.239349
Kurtosis210.76
Mean37.392857
Median Absolute Deviation (MAD)0
Skewness14.358973
Sum8376
Variance176628.02
MonotonicityNot monotonic
2023-12-12T17:10:07.092324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 197
87.9%
5 3
 
1.3%
24 2
 
0.9%
1 2
 
0.9%
52 2
 
0.9%
60 1
 
0.4%
273 1
 
0.4%
239 1
 
0.4%
55 1
 
0.4%
18 1
 
0.4%
Other values (13) 13
 
5.8%
ValueCountFrequency (%)
0 197
87.9%
1 2
 
0.9%
5 3
 
1.3%
8 1
 
0.4%
13 1
 
0.4%
15 1
 
0.4%
18 1
 
0.4%
19 1
 
0.4%
22 1
 
0.4%
23 1
 
0.4%
ValueCountFrequency (%)
6205 1
0.4%
1020 1
0.4%
273 1
0.4%
239 1
0.4%
60 1
0.4%
59 1
0.4%
56 1
0.4%
55 1
0.4%
52 2
0.9%
48 1
0.4%

제정
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct116
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean276.20536
Minimum0
Maximum6205
Zeros12
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:07.244770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.15
Q114
median42
Q396.5
95-th percentile1657.35
Maximum6205
Range6205
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation867.01511
Coefficient of variation (CV)3.1390235
Kurtosis26.73763
Mean276.20536
Median Absolute Deviation (MAD)33.5
Skewness4.9949078
Sum61870
Variance751715.2
MonotonicityNot monotonic
2023-12-12T17:10:07.467664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
5.4%
5 10
 
4.5%
10 6
 
2.7%
52 6
 
2.7%
16 5
 
2.2%
24 5
 
2.2%
36 5
 
2.2%
78 5
 
2.2%
12 4
 
1.8%
1 4
 
1.8%
Other values (106) 162
72.3%
ValueCountFrequency (%)
0 12
5.4%
1 4
 
1.8%
2 3
 
1.3%
3 2
 
0.9%
4 3
 
1.3%
5 10
4.5%
6 3
 
1.3%
7 2
 
0.9%
8 4
 
1.8%
9 2
 
0.9%
ValueCountFrequency (%)
6205 1
0.4%
5760 1
0.4%
5274 1
0.4%
5252 1
0.4%
3672 1
0.4%
3321 1
0.4%
2300 1
0.4%
2266 1
0.4%
1836 2
0.9%
1778 1
0.4%

개정
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3169643
Minimum0
Maximum60
Zeros203
Zeros (%)90.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:10:07.606763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.85
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.606321
Coefficient of variation (CV)5.0163251
Kurtosis51.805675
Mean1.3169643
Median Absolute Deviation (MAD)0
Skewness6.8756138
Sum295
Variance43.643478
MonotonicityNot monotonic
2023-12-12T17:10:07.729131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 203
90.6%
1 5
 
2.2%
18 3
 
1.3%
8 2
 
0.9%
5 2
 
0.9%
4 1
 
0.4%
54 1
 
0.4%
6 1
 
0.4%
12 1
 
0.4%
60 1
 
0.4%
Other values (4) 4
 
1.8%
ValueCountFrequency (%)
0 203
90.6%
1 5
 
2.2%
3 1
 
0.4%
4 1
 
0.4%
5 2
 
0.9%
6 1
 
0.4%
8 2
 
0.9%
9 1
 
0.4%
12 1
 
0.4%
18 3
 
1.3%
ValueCountFrequency (%)
60 1
 
0.4%
54 1
 
0.4%
42 1
 
0.4%
20 1
 
0.4%
18 3
1.3%
12 1
 
0.4%
9 1
 
0.4%
8 2
0.9%
6 1
 
0.4%
5 2
0.9%

Interactions

2023-12-12T17:10:02.166883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.068389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.058547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.991724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.380194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.431542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.432482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.449044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.290173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.283345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.171849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.152982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:56.100036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.523467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.541690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.536417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.545513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.375168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.393342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.283281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.243121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:56.212605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.626469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.649163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.630590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.633758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.464881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.540455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.381810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.344172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:56.680779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.749927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.764364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.782434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.728239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.571398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.684295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.474901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.456868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:56.798275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.852881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.889391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.903654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.822334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.658090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.817814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.582659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.569422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:56.921594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.965011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.011994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.007914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.914470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.762913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.930828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.696882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.665794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.044928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.079813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.108140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.121470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.019162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.857498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:03.044894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.819889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.769952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.155619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.177825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.208230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.238601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.117597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.980680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:03.164313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:54.952913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:55.874672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:57.253210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:58.291869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:59.312511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:00.343418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:01.209316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:10:02.072231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:10:07.834577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
DB 코드년도수집생산유효데이터유효참조표준검증참조표준인증참조표준제정개정
DB 코드1.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
년도0.0001.0000.0000.0000.0000.0000.2010.0000.0000.133
수집0.0000.0001.0000.0000.7010.4430.0000.0000.3900.000
생산0.0000.0000.0001.0000.0000.0000.0000.0000.0000.339
유효데이터0.0000.0000.7010.0001.0000.4430.0000.0000.3900.000
유효참조표준0.0000.0000.4430.0000.4431.0000.3400.0000.9500.710
검증참조표준0.0000.2010.0000.0000.0000.3401.0000.0000.6880.000
인증참조표준0.0000.0000.0000.0000.0000.0000.0001.0000.6550.000
제정0.0000.0000.3900.0000.3900.9500.6880.6551.0000.691
개정0.0000.1330.0000.3390.0000.7100.0000.0000.6911.000
2023-12-12T17:10:07.991148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도수집생산유효데이터유효참조표준검증참조표준인증참조표준제정개정
년도1.000-0.475-0.366-0.689-0.177-0.382-0.222-0.1010.080
수집-0.4751.000-0.2170.5190.2420.3390.0830.252-0.083
생산-0.366-0.2171.0000.5990.037-0.0820.087-0.0450.061
유효데이터-0.6890.5190.5991.0000.2580.2310.1910.232-0.057
유효참조표준-0.1770.2420.0370.2581.000-0.098-0.1100.5470.065
검증참조표준-0.3820.339-0.0820.231-0.0981.0000.0640.255-0.042
인증참조표준-0.2220.0830.0870.191-0.1100.0641.0000.121-0.073
제정-0.1010.252-0.0450.2320.5470.2550.1211.000-0.146
개정0.080-0.0830.061-0.0570.065-0.042-0.073-0.1461.000

Missing values

2023-12-12T17:10:03.615983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:10:03.789654image/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

DB 코드년도수집생산유효데이터유효참조표준검증참조표준인증참조표준제정개정
0S020030012008167503355079601890
1S05001001200817101626500650
2S030030012008913018353200730
3S02001001200849640188584201000
4S03004001201012410496028802880
5S060010012010011201120232888011200
6S0300200120084130833600360
7S01001001200734901222535600
8S010020012007700280280280
9S010030012007660330200200
DB 코드년도수집생산유효데이터유효참조표준검증참조표준인증참조표준제정개정
21410008001202100000018360
215100100012021000000480
216100110012021000000640
217100120012021000000960
218100130012021000000120
2191300100120210000003750
220130020012021000000720
2211300300120210000003090
2222832021000000210
22320010012021000000270