Overview

Dataset statistics

Number of variables10
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory91.9 B

Variable types

Categorical2
DateTime1
Text1
Numeric6

Dataset

Description- 2022년에 표준서식으로 공시한 법인을 기준으로 작성-지역별, 설립일 기준별, 사업목적별 공익법인 의무공시 법인수(단위 : 개)
Author국세청
URLhttps://www.data.go.kr/data/15121136/fileData.do

Alerts

귀속연도 has constant value ""Constant
데이터생성일 has constant value ""Constant
사회복지 is highly overall correlated with 교육 and 4 other fieldsHigh correlation
교육 is highly overall correlated with 사회복지 and 2 other fieldsHigh correlation
학술장학 is highly overall correlated with 사회복지 and 4 other fieldsHigh correlation
예술문화 is highly overall correlated with 사회복지 and 3 other fieldsHigh correlation
의료 is highly overall correlated with 사회복지 and 4 other fieldsHigh correlation
기타 is highly overall correlated with 사회복지 and 4 other fieldsHigh correlation
구분1 is highly overall correlated with 기타High correlation
구분2 has unique valuesUnique
학술장학 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:50:59.317464
Analysis finished2023-12-12 04:51:03.246919
Duration3.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

귀속연도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2022
27 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 27
100.0%

Length

2023-12-12T13:51:03.317991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:51:03.736184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 27
100.0%

데이터생성일
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T13:51:03.833532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:03.960802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

구분1
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
지역별
17 
설립일기준
10 

Length

Max length5
Median length3
Mean length3.7407407
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역별 17
63.0%
설립일기준 10
37.0%

Length

2023-12-12T13:51:04.122591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:51:04.287315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역별 17
63.0%
설립일기준 10
37.0%

구분2
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T13:51:04.514342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length4.6666667
Min length2

Characters and Unicode

Total characters126
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row서울
2nd row인천
3rd row경기
4th row강원
5th row대전
ValueCountFrequency (%)
이후 9
24.3%
서울 1
 
2.7%
경남 1
 
2.7%
70.12.31 1
 
2.7%
71.1.1 1
 
2.7%
81.1.1 1
 
2.7%
91.1.1 1
 
2.7%
01.1.1 1
 
2.7%
06.1.1 1
 
2.7%
11.1.1 1
 
2.7%
Other values (19) 19
51.4%
2023-12-12T13:51:04.911037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28
22.2%
. 20
15.9%
10
 
7.9%
이 10
 
7.9%
후 9
 
7.1%
0 4
 
3.2%
전 4
 
3.2%
남 3
 
2.4%
경 3
 
2.4%
북 3
 
2.4%
Other values (23) 32
25.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
42.9%
Decimal Number 42
33.3%
Other Punctuation 20
 
15.9%
Space Separator 10
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
18.5%
후 9
16.7%
전 4
 
7.4%
남 3
 
5.6%
경 3
 
5.6%
북 3
 
5.6%
주 2
 
3.7%
울 2
 
3.7%
충 2
 
3.7%
대 2
 
3.7%
Other values (13) 14
25.9%
Decimal Number
ValueCountFrequency (%)
1 28
66.7%
0 4
 
9.5%
2 2
 
4.8%
8 2
 
4.8%
6 2
 
4.8%
7 2
 
4.8%
9 1
 
2.4%
3 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 20
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
57.1%
Hangul 54
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
18.5%
후 9
16.7%
전 4
 
7.4%
남 3
 
5.6%
경 3
 
5.6%
북 3
 
5.6%
주 2
 
3.7%
울 2
 
3.7%
충 2
 
3.7%
대 2
 
3.7%
Other values (13) 14
25.9%
Common
ValueCountFrequency (%)
1 28
38.9%
. 20
27.8%
10
 
13.9%
0 4
 
5.6%
2 2
 
2.8%
8 2
 
2.8%
6 2
 
2.8%
7 2
 
2.8%
9 1
 
1.4%
3 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
57.1%
Hangul 54
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28
38.9%
. 20
27.8%
10
 
13.9%
0 4
 
5.6%
2 2
 
2.8%
8 2
 
2.8%
6 2
 
2.8%
7 2
 
2.8%
9 1
 
1.4%
3 1
 
1.4%
Hangul
ValueCountFrequency (%)
이 10
18.5%
후 9
16.7%
전 4
 
7.4%
남 3
 
5.6%
경 3
 
5.6%
북 3
 
5.6%
주 2
 
3.7%
울 2
 
3.7%
충 2
 
3.7%
대 2
 
3.7%
Other values (13) 14
25.9%

사회복지
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.40741
Minimum21
Maximum642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:05.073711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile66
Q1102.5
median161
Q3300
95-th percentile619.7
Maximum642
Range621
Interquartile range (IQR)197.5

Descriptive statistics

Standard deviation181.20585
Coefficient of variation (CV)0.79683352
Kurtosis0.54134717
Mean227.40741
Median Absolute Deviation (MAD)70
Skewness1.2903087
Sum6140
Variance32835.558
MonotonicityNot monotonic
2023-12-12T13:51:05.213447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
165 2
 
7.4%
91 2
 
7.4%
635 1
 
3.7%
261 1
 
3.7%
339 1
 
3.7%
127 1
 
3.7%
642 1
 
3.7%
522 1
 
3.7%
584 1
 
3.7%
365 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
21 1
3.7%
57 1
3.7%
87 1
3.7%
91 2
7.4%
94 1
3.7%
98 1
3.7%
107 1
3.7%
112 1
3.7%
121 1
3.7%
127 1
3.7%
ValueCountFrequency (%)
642 1
3.7%
635 1
3.7%
584 1
3.7%
522 1
3.7%
394 1
3.7%
365 1
3.7%
339 1
3.7%
261 1
3.7%
233 1
3.7%
193 1
3.7%

교육
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.7037
Minimum5
Maximum561
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:05.363631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile18.6
Q155.5
median93
Q3176.5
95-th percentile385.6
Maximum561
Range556
Interquartile range (IQR)121

Descriptive statistics

Standard deviation130.42086
Coefficient of variation (CV)0.96107076
Kurtosis3.6716874
Mean135.7037
Median Absolute Deviation (MAD)45
Skewness1.8497756
Sum3664
Variance17009.601
MonotonicityNot monotonic
2023-12-12T13:51:05.522496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
57 3
 
11.1%
127 2
 
7.4%
427 1
 
3.7%
18 1
 
3.7%
561 1
 
3.7%
249 1
 
3.7%
208 1
 
3.7%
228 1
 
3.7%
258 1
 
3.7%
105 1
 
3.7%
Other values (14) 14
51.9%
ValueCountFrequency (%)
5 1
 
3.7%
18 1
 
3.7%
20 1
 
3.7%
23 1
 
3.7%
45 1
 
3.7%
48 1
 
3.7%
54 1
 
3.7%
57 3
11.1%
75 1
 
3.7%
84 1
 
3.7%
ValueCountFrequency (%)
561 1
3.7%
427 1
3.7%
289 1
3.7%
258 1
3.7%
249 1
3.7%
228 1
3.7%
208 1
3.7%
145 1
3.7%
127 2
7.4%
112 1
3.7%

학술장학
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202.44444
Minimum12
Maximum1193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:05.704008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile29.1
Q170
median94
Q3205.5
95-th percentile641.1
Maximum1193
Range1181
Interquartile range (IQR)135.5

Descriptive statistics

Standard deviation260.17248
Coefficient of variation (CV)1.2851549
Kurtosis7.6540865
Mean202.44444
Median Absolute Deviation (MAD)43
Skewness2.6074918
Sum5466
Variance67689.718
MonotonicityNot monotonic
2023-12-12T13:51:05.896834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1193 1
 
3.7%
63 1
 
3.7%
50 1
 
3.7%
113 1
 
3.7%
320 1
 
3.7%
684 1
 
3.7%
486 1
 
3.7%
541 1
 
3.7%
342 1
 
3.7%
79 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
12 1
3.7%
27 1
3.7%
34 1
3.7%
50 1
3.7%
51 1
3.7%
63 1
3.7%
67 1
3.7%
73 1
3.7%
76 1
3.7%
79 1
3.7%
ValueCountFrequency (%)
1193 1
3.7%
684 1
3.7%
541 1
3.7%
486 1
3.7%
342 1
3.7%
320 1
3.7%
257 1
3.7%
154 1
3.7%
141 1
3.7%
126 1
3.7%

예술문화
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.666667
Minimum3
Maximum411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:06.052404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.7
Q121
median37
Q369
95-th percentile171.5
Maximum411
Range408
Interquartile range (IQR)48

Descriptive statistics

Standard deviation83.60392
Coefficient of variation (CV)1.2928441
Kurtosis11.247316
Mean64.666667
Median Absolute Deviation (MAD)20
Skewness3.0552659
Sum1746
Variance6989.6154
MonotonicityNot monotonic
2023-12-12T13:51:06.198724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
37 2
 
7.4%
23 2
 
7.4%
13 2
 
7.4%
411 1
 
3.7%
14 1
 
3.7%
20 1
 
3.7%
148 1
 
3.7%
103 1
 
3.7%
154 1
 
3.7%
179 1
 
3.7%
Other values (14) 14
51.9%
ValueCountFrequency (%)
3 1
3.7%
4 1
3.7%
13 2
7.4%
14 1
3.7%
18 1
3.7%
20 1
3.7%
22 1
3.7%
23 2
7.4%
31 1
3.7%
32 1
3.7%
ValueCountFrequency (%)
411 1
3.7%
179 1
3.7%
154 1
3.7%
148 1
3.7%
103 1
3.7%
101 1
3.7%
72 1
3.7%
66 1
3.7%
57 1
3.7%
48 1
3.7%

의료
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.148148
Minimum5
Maximum301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:06.353756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.9
Q128.5
median60
Q3116
95-th percentile236.6
Maximum301
Range296
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation76.104535
Coefficient of variation (CV)0.92643032
Kurtosis1.8059618
Mean82.148148
Median Absolute Deviation (MAD)38
Skewness1.4730311
Sum2218
Variance5791.9003
MonotonicityNot monotonic
2023-12-12T13:51:06.482232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
73 2
 
7.4%
34 2
 
7.4%
98 1
 
3.7%
127 1
 
3.7%
8 1
 
3.7%
18 1
 
3.7%
170 1
 
3.7%
152 1
 
3.7%
254 1
 
3.7%
301 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
5 1
3.7%
8 1
3.7%
11 1
3.7%
18 1
3.7%
20 1
3.7%
26 1
3.7%
27 1
3.7%
30 1
3.7%
34 2
7.4%
46 1
3.7%
ValueCountFrequency (%)
301 1
3.7%
254 1
3.7%
196 1
3.7%
170 1
3.7%
152 1
3.7%
127 1
3.7%
118 1
3.7%
114 1
3.7%
98 1
3.7%
73 2
7.4%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.7037
Minimum15
Maximum940
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T13:51:06.628815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile26.1
Q155
median66
Q3152.5
95-th percentile400.2
Maximum940
Range925
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation190.48376
Coefficient of variation (CV)1.3255313
Kurtosis11.798139
Mean143.7037
Median Absolute Deviation (MAD)20
Skewness3.1583212
Sum3880
Variance36284.063
MonotonicityNot monotonic
2023-12-12T13:51:06.743399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
66 2
 
7.4%
60 2
 
7.4%
57 2
 
7.4%
55 2
 
7.4%
940 1
 
3.7%
148 1
 
3.7%
46 1
 
3.7%
79 1
 
3.7%
278 1
 
3.7%
275 1
 
3.7%
Other values (13) 13
48.1%
ValueCountFrequency (%)
15 1
3.7%
24 1
3.7%
31 1
3.7%
41 1
3.7%
46 1
3.7%
48 1
3.7%
55 2
7.4%
57 2
7.4%
58 1
3.7%
60 2
7.4%
ValueCountFrequency (%)
940 1
3.7%
435 1
3.7%
319 1
3.7%
278 1
3.7%
275 1
3.7%
222 1
3.7%
156 1
3.7%
149 1
3.7%
148 1
3.7%
79 1
3.7%

Interactions

2023-12-12T13:51:02.467848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:50:59.678482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.301119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.867191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.357010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.909913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.557208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:50:59.768261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.398618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.955839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.439398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.999542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.647012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:50:59.861966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.485315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.034936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.544510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.092853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.723947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:50:59.965582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.606861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.115866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.631749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.189328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.825943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.088657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.698603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.204692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.730789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.292965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.926620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.223241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:00.781251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.281485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:01.827982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:02.385075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:51:06.833813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1구분2사회복지교육학술장학예술문화의료기타
구분11.0001.0000.5370.6500.5630.7110.0000.814
구분21.0001.0001.0001.0001.0001.0001.0001.000
사회복지0.5371.0001.0000.9250.8210.7990.8150.682
교육0.6501.0000.9251.0000.8190.6730.7270.690
학술장학0.5631.0000.8210.8191.0000.9340.8950.926
예술문화0.7111.0000.7990.6730.9341.0000.9020.993
의료0.0001.0000.8150.7270.8950.9021.0000.904
기타0.8141.0000.6820.6900.9260.9930.9041.000
2023-12-12T13:51:06.959490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사회복지교육학술장학예술문화의료기타구분1
사회복지1.0000.8470.8520.7700.7640.6810.340
교육0.8471.0000.7480.4800.5270.4260.421
학술장학0.8520.7481.0000.6960.8260.7220.365
예술문화0.7700.4800.6961.0000.7040.8900.475
의료0.7640.5270.8260.7041.0000.7820.000
기타0.6810.4260.7220.8900.7821.0000.563
구분10.3400.4210.3650.4750.0000.5631.000

Missing values

2023-12-12T13:51:03.034750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:51:03.183768image/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

귀속연도데이터생성일구분1구분2사회복지교육학술장학예술문화의료기타
020222023-06-30지역별서울635427119341198940
120222023-06-30지역별인천915763133448
220222023-06-30지역별경기394289257101196222
320222023-06-30지역별강원1125794434658
420222023-06-30지역별대전915773132766
520222023-06-30지역별충북945476184960
620222023-06-30지역별충남1889391317357
720222023-06-30지역별세종215123515
820222023-06-30지역별광주1367592222041
920222023-06-30지역별전북151106109326560
귀속연도데이터생성일구분1구분2사회복지교육학술장학예술문화의료기타
1720222023-06-30설립일기준20.1.1 이후9818517226148
1820222023-06-30설립일기준18.1.1 이후12145675747149
1920222023-06-30설립일기준16.1.1 이후10748796660156
2020222023-06-30설립일기준11.1.1 이후365112342179301435
2120222023-06-30설립일기준06.1.1 이후584105541154254319
2220222023-06-30설립일기준01.1.1 이후522258486103152275
2320222023-06-30설립일기준91.1.1 이후642228684148170278
2420222023-06-30설립일기준81.1.1 이후165208320377379
2520222023-06-30설립일기준71.1.1 이후127249113201846
2620222023-06-30설립일기준70.12.31 이전3395615037855