Overview

Dataset statistics

Number of variables19
Number of observations7454
Missing cells45990
Missing cells (%)32.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory164.0 B

Variable types

Numeric6
Text4
Categorical3
Unsupported6

Dataset

Description국가기록포털 분야별/유형별 검색 내 기술내용과 관련된 데이터로 주제명, 주제설명, 집필자 등의 정보를 서비스하고 있습니다.
Author행정안전부 국가기록원
URLhttps://www.data.go.kr/data/15122943/fileData.do

Alerts

주제유형분야ID is highly overall correlated with 분야명High correlation
분야ID is highly overall correlated with 분야ID.1 and 1 other fieldsHigh correlation
유형ID is highly overall correlated with 유형ID.1 and 1 other fieldsHigh correlation
상위주제ID is highly overall correlated with 분야명High correlation
분야ID.1 is highly overall correlated with 분야ID and 1 other fieldsHigh correlation
유형ID.1 is highly overall correlated with 유형ID and 1 other fieldsHigh correlation
서비스구분 is highly overall correlated with 분야명High correlation
분야명 is highly overall correlated with 주제유형분야ID and 4 other fieldsHigh correlation
유형명 is highly overall correlated with 유형ID and 1 other fieldsHigh correlation
주제설명 has 1159 (15.5%) missing valuesMissing
주제명2 has 7454 (100.0%) missing valuesMissing
주제서술항목명 has 7454 (100.0%) missing valuesMissing
주제분야담당자지정내역ID has 7454 (100.0%) missing valuesMissing
주제서술항목서술내용 has 7454 (100.0%) missing valuesMissing
주제콘텐츠업무기능연관ID has 7454 (100.0%) missing valuesMissing
주제서술 연관내역ID has 7454 (100.0%) missing valuesMissing
주제유형분야ID has unique valuesUnique
주제명2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제서술항목명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제분야담당자지정내역ID is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제서술항목서술내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제콘텐츠업무기능연관ID is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제서술 연관내역ID is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 20:12:56.781061
Analysis finished2023-12-12 20:13:02.870174
Duration6.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주제유형분야ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct7454
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5221.7142
Minimum31
Maximum10560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:02.989120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile591.65
Q12707.25
median5337.5
Q37288.75
95-th percentile10177.35
Maximum10560
Range10529
Interquartile range (IQR)4581.5

Descriptive statistics

Standard deviation2995.8993
Coefficient of variation (CV)0.57373865
Kurtosis-1.1020191
Mean5221.7142
Median Absolute Deviation (MAD)2515
Skewness0.079417795
Sum38922658
Variance8975412.5
MonotonicityNot monotonic
2023-12-13T05:13:03.190911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3609 1
 
< 0.1%
8095 1
 
< 0.1%
8112 1
 
< 0.1%
8111 1
 
< 0.1%
8110 1
 
< 0.1%
8108 1
 
< 0.1%
8107 1
 
< 0.1%
8104 1
 
< 0.1%
8103 1
 
< 0.1%
8101 1
 
< 0.1%
Other values (7444) 7444
99.9%
ValueCountFrequency (%)
31 1
< 0.1%
32 1
< 0.1%
33 1
< 0.1%
34 1
< 0.1%
35 1
< 0.1%
36 1
< 0.1%
37 1
< 0.1%
38 1
< 0.1%
39 1
< 0.1%
40 1
< 0.1%
ValueCountFrequency (%)
10560 1
< 0.1%
10559 1
< 0.1%
10558 1
< 0.1%
10557 1
< 0.1%
10556 1
< 0.1%
10555 1
< 0.1%
10554 1
< 0.1%
10553 1
< 0.1%
10552 1
< 0.1%
10551 1
< 0.1%

주제명
Text

Distinct7221
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size58.4 KiB
2023-12-13T05:13:03.634547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length55
Mean length10.218675
Min length2

Characters and Unicode

Total characters76170
Distinct characters689
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7098 ?
Unique (%)95.2%

Sample

1st row남북체육회담
2nd row한일회담 반대시위(6.3사태)
3rd row해양경찰학교
4th row국제협력활동
5th rowSAR협약
ValueCountFrequency (%)
및 311
 
2.2%
관한 211
 
1.5%
제정 130
 
0.9%
법률 94
 
0.7%
감사 54
 
0.4%
구축 54
 
0.4%
제도 51
 
0.4%
사업 50
 
0.4%
정책 49
 
0.3%
사건 48
 
0.3%
Other values (9192) 12967
92.5%
2023-12-13T05:13:04.332922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6807
 
8.9%
정 1782
 
2.3%
제 1659
 
2.2%
사 1534
 
2.0%
국 1079
 
1.4%
관 1058
 
1.4%
기 1053
 
1.4%
원 1020
 
1.3%
지 1020
 
1.3%
업 1002
 
1.3%
Other values (679) 58156
76.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61692
81.0%
Space Separator 6807
 
8.9%
Decimal Number 3713
 
4.9%
Uppercase Letter 1241
 
1.6%
Close Punctuation 741
 
1.0%
Open Punctuation 729
 
1.0%
Other Punctuation 685
 
0.9%
Lowercase Letter 326
 
0.4%
Dash Punctuation 220
 
0.3%
Math Symbol 9
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 1782
 
2.9%
제 1659
 
2.7%
사 1534
 
2.5%
국 1079
 
1.7%
관 1058
 
1.7%
기 1053
 
1.7%
원 1020
 
1.7%
지 1020
 
1.7%
업 1002
 
1.6%
한 989
 
1.6%
Other values (599) 49496
80.2%
Uppercase Letter
ValueCountFrequency (%)
A 133
 
10.7%
T 109
 
8.8%
C 90
 
7.3%
S 86
 
6.9%
I 82
 
6.6%
E 78
 
6.3%
O 73
 
5.9%
P 71
 
5.7%
N 68
 
5.5%
D 64
 
5.2%
Other values (15) 387
31.2%
Lowercase Letter
ValueCountFrequency (%)
e 48
14.7%
a 36
11.0%
r 32
9.8%
o 31
9.5%
i 27
 
8.3%
n 24
 
7.4%
t 20
 
6.1%
s 16
 
4.9%
u 13
 
4.0%
m 11
 
3.4%
Other values (14) 68
20.9%
Decimal Number
ValueCountFrequency (%)
1 846
22.8%
9 728
19.6%
0 487
13.1%
2 399
10.7%
5 235
 
6.3%
7 226
 
6.1%
8 219
 
5.9%
6 196
 
5.3%
4 193
 
5.2%
3 184
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 246
35.9%
· 177
25.8%
, 123
18.0%
/ 44
 
6.4%
' 24
 
3.5%
& 23
 
3.4%
; 20
 
2.9%
# 20
 
2.9%
: 8
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 735
99.2%
」 6
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 723
99.2%
「 6
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 5
55.6%
+ 4
44.4%
Space Separator
ValueCountFrequency (%)
6807
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61686
81.0%
Common 12910
 
16.9%
Latin 1567
 
2.1%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 1782
 
2.9%
제 1659
 
2.7%
사 1534
 
2.5%
국 1079
 
1.7%
관 1058
 
1.7%
기 1053
 
1.7%
원 1020
 
1.7%
지 1020
 
1.7%
업 1002
 
1.6%
한 989
 
1.6%
Other values (593) 49490
80.2%
Latin
ValueCountFrequency (%)
A 133
 
8.5%
T 109
 
7.0%
C 90
 
5.7%
S 86
 
5.5%
I 82
 
5.2%
E 78
 
5.0%
O 73
 
4.7%
P 71
 
4.5%
N 68
 
4.3%
D 64
 
4.1%
Other values (39) 713
45.5%
Common
ValueCountFrequency (%)
6807
52.7%
1 846
 
6.6%
) 735
 
5.7%
9 728
 
5.6%
( 723
 
5.6%
0 487
 
3.8%
2 399
 
3.1%
. 246
 
1.9%
5 235
 
1.8%
7 226
 
1.8%
Other values (20) 1478
 
11.4%
Han
ValueCountFrequency (%)
超 1
14.3%
大 1
14.3%
洞 1
14.3%
前 1
14.3%
對 1
14.3%
現 1
14.3%
制 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61665
81.0%
ASCII 14286
 
18.8%
None 190
 
0.2%
Compat Jamo 20
 
< 0.1%
CJK 7
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6807
47.6%
1 846
 
5.9%
) 735
 
5.1%
9 728
 
5.1%
( 723
 
5.1%
0 487
 
3.4%
2 399
 
2.8%
. 246
 
1.7%
5 235
 
1.6%
7 226
 
1.6%
Other values (64) 2854
20.0%
Hangul
ValueCountFrequency (%)
정 1782
 
2.9%
제 1659
 
2.7%
사 1534
 
2.5%
국 1079
 
1.7%
관 1058
 
1.7%
기 1053
 
1.7%
원 1020
 
1.7%
지 1020
 
1.7%
업 1002
 
1.6%
한 989
 
1.6%
Other values (591) 49469
80.2%
None
ValueCountFrequency (%)
· 177
93.2%
「 6
 
3.2%
」 6
 
3.2%
㈜ 1
 
0.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 20
100.0%
CJK
ValueCountFrequency (%)
超 1
14.3%
大 1
14.3%
洞 1
14.3%
前 1
14.3%
對 1
14.3%
現 1
14.3%
制 1
14.3%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

주제설명
Text

MISSING 

Distinct6107
Distinct (%)97.0%
Missing1159
Missing (%)15.5%
Memory size58.4 KiB
2023-12-13T05:13:04.732293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length48
Mean length10.481811
Min length1

Characters and Unicode

Total characters65983
Distinct characters679
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6023 ?
Unique (%)95.7%

Sample

1st row한일회담반대시위(6.3사태)
2nd row해양경찰학교
3rd row국제협력활동
4th rowSAR협약
5th row유엔해양법 협약
ValueCountFrequency (%)
및 227
 
2.0%
관한 157
 
1.4%
제정 110
 
0.9%
법률 62
 
0.5%
구축 50
 
0.4%
위한 42
 
0.4%
설치 41
 
0.4%
사건 37
 
0.3%
사업 33
 
0.3%
경제협력 33
 
0.3%
Other values (8004) 10815
93.2%
2023-12-13T05:13:05.247225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5528
 
8.4%
정 1553
 
2.4%
제 1449
 
2.2%
사 1246
 
1.9%
국 934
 
1.4%
지 926
 
1.4%
기 896
 
1.4%
1 896
 
1.4%
업 868
 
1.3%
원 865
 
1.3%
Other values (669) 50822
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52449
79.5%
Space Separator 5528
 
8.4%
Decimal Number 4323
 
6.6%
Uppercase Letter 983
 
1.5%
Close Punctuation 798
 
1.2%
Open Punctuation 791
 
1.2%
Other Punctuation 674
 
1.0%
Dash Punctuation 213
 
0.3%
Lowercase Letter 115
 
0.2%
Connector Punctuation 89
 
0.1%
Other values (6) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 1553
 
3.0%
제 1449
 
2.8%
사 1246
 
2.4%
국 934
 
1.8%
지 926
 
1.8%
기 896
 
1.7%
업 868
 
1.7%
원 865
 
1.6%
한 839
 
1.6%
관 838
 
1.6%
Other values (592) 42035
80.1%
Uppercase Letter
ValueCountFrequency (%)
A 110
 
11.2%
T 86
 
8.7%
C 72
 
7.3%
S 70
 
7.1%
I 62
 
6.3%
O 60
 
6.1%
E 57
 
5.8%
P 55
 
5.6%
N 55
 
5.6%
D 49
 
5.0%
Other values (15) 307
31.2%
Lowercase Letter
ValueCountFrequency (%)
e 18
15.7%
r 16
13.9%
o 14
12.2%
a 11
9.6%
t 8
 
7.0%
s 6
 
5.2%
n 6
 
5.2%
u 6
 
5.2%
i 5
 
4.3%
y 5
 
4.3%
Other values (11) 20
17.4%
Decimal Number
ValueCountFrequency (%)
1 896
20.7%
9 786
18.2%
0 684
15.8%
2 523
12.1%
7 341
 
7.9%
5 248
 
5.7%
8 241
 
5.6%
6 213
 
4.9%
3 198
 
4.6%
4 193
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 416
61.7%
, 111
 
16.5%
· 62
 
9.2%
/ 53
 
7.9%
' 25
 
3.7%
: 6
 
0.9%
& 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 795
99.6%
」 3
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 787
99.5%
「 4
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 5
55.6%
+ 4
44.4%
Space Separator
ValueCountFrequency (%)
5528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 89
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52434
79.5%
Common 12435
 
18.8%
Latin 1098
 
1.7%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 1553
 
3.0%
제 1449
 
2.8%
사 1246
 
2.4%
국 934
 
1.8%
지 926
 
1.8%
기 896
 
1.7%
업 868
 
1.7%
원 865
 
1.6%
한 839
 
1.6%
관 838
 
1.6%
Other values (579) 42020
80.1%
Latin
ValueCountFrequency (%)
A 110
 
10.0%
T 86
 
7.8%
C 72
 
6.6%
S 70
 
6.4%
I 62
 
5.6%
O 60
 
5.5%
E 57
 
5.2%
P 55
 
5.0%
N 55
 
5.0%
D 49
 
4.5%
Other values (36) 422
38.4%
Common
ValueCountFrequency (%)
5528
44.5%
1 896
 
7.2%
) 795
 
6.4%
( 787
 
6.3%
9 786
 
6.3%
0 684
 
5.5%
2 523
 
4.2%
. 416
 
3.3%
7 341
 
2.7%
5 248
 
2.0%
Other values (20) 1431
 
11.5%
Han
ValueCountFrequency (%)
現 3
18.8%
所 1
 
6.2%
船 1
 
6.2%
造 1
 
6.2%
浦 1
 
6.2%
玉 1
 
6.2%
場 1
 
6.2%
工 1
 
6.2%
原 1
 
6.2%
昌 1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52421
79.4%
ASCII 13462
 
20.4%
None 70
 
0.1%
CJK 16
 
< 0.1%
Compat Jamo 12
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5528
41.1%
1 896
 
6.7%
) 795
 
5.9%
( 787
 
5.8%
9 786
 
5.8%
0 684
 
5.1%
2 523
 
3.9%
. 416
 
3.1%
7 341
 
2.5%
5 248
 
1.8%
Other values (61) 2458
18.3%
Hangul
ValueCountFrequency (%)
정 1553
 
3.0%
제 1449
 
2.8%
사 1246
 
2.4%
국 934
 
1.8%
지 926
 
1.8%
기 896
 
1.7%
업 868
 
1.7%
원 865
 
1.7%
한 839
 
1.6%
관 838
 
1.6%
Other values (577) 42007
80.1%
None
ValueCountFrequency (%)
· 62
88.6%
「 4
 
5.7%
」 3
 
4.3%
㈜ 1
 
1.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 12
100.0%
CJK
ValueCountFrequency (%)
現 3
18.8%
所 1
 
6.2%
船 1
 
6.2%
造 1
 
6.2%
浦 1
 
6.2%
玉 1
 
6.2%
場 1
 
6.2%
工 1
 
6.2%
原 1
 
6.2%
昌 1
 
6.2%
Other values (4) 4
25.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

서비스구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.4 KiB
Y
5774 
N
1162 
R
 
518

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
Y 5774
77.5%
N 1162
 
15.6%
R 518
 
6.9%

Length

2023-12-13T05:13:05.673462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:05.768811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 5774
77.5%
n 1162
 
15.6%
r 518
 
6.9%

주제 등록일자
Text

Distinct379
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size58.4 KiB
2023-12-13T05:13:06.091131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.999061
Min length7

Characters and Unicode

Total characters104349
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)2.5%

Sample

1st row20061116 14:38
2nd row20070813 11:07
3rd row20070813 11:07
4th row20070813 11:07
5th row20070813 11:07
ValueCountFrequency (%)
20061105 2130
 
14.3%
01:55 2130
 
14.3%
20070914 760
 
5.1%
20071001 733
 
4.9%
15:58 733
 
4.9%
15:54 728
 
4.9%
13:47 370
 
2.5%
20171027 369
 
2.5%
20151116 359
 
2.4%
20140923 293
 
2.0%
Other values (339) 6302
42.3%
2023-12-13T05:13:06.615047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25196
24.1%
1 20156
19.3%
5 11640
11.2%
2 10694
10.2%
7453
 
7.1%
: 7453
 
7.1%
7 5124
 
4.9%
6 4078
 
3.9%
4 4062
 
3.9%
3 3395
 
3.3%
Other values (9) 5098
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89436
85.7%
Other Punctuation 7455
 
7.1%
Space Separator 7453
 
7.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25196
28.2%
1 20156
22.5%
5 11640
13.0%
2 10694
12.0%
7 5124
 
5.7%
6 4078
 
4.6%
4 4062
 
4.5%
3 3395
 
3.8%
8 3114
 
3.5%
9 1977
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
V 1
20.0%
A 1
20.0%
L 1
20.0%
U 1
20.0%
E 1
20.0%
Other Punctuation
ValueCountFrequency (%)
: 7453
> 99.9%
# 1
 
< 0.1%
! 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
7453
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104344
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25196
24.1%
1 20156
19.3%
5 11640
11.2%
2 10694
10.2%
7453
 
7.1%
: 7453
 
7.1%
7 5124
 
4.9%
6 4078
 
3.9%
4 4062
 
3.9%
3 3395
 
3.3%
Other values (4) 5093
 
4.9%
Latin
ValueCountFrequency (%)
V 1
20.0%
A 1
20.0%
L 1
20.0%
U 1
20.0%
E 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25196
24.1%
1 20156
19.3%
5 11640
11.2%
2 10694
10.2%
7453
 
7.1%
: 7453
 
7.1%
7 5124
 
4.9%
6 4078
 
3.9%
4 4062
 
3.9%
3 3395
 
3.3%
Other values (9) 5098
 
4.9%

분야ID
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.551113
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:06.773348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median13
Q319
95-th percentile26
Maximum28
Range27
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.1958478
Coefficient of variation (CV)0.53101524
Kurtosis-0.91837494
Mean13.551113
Median Absolute Deviation (MAD)5
Skewness0.17832407
Sum101010
Variance51.780226
MonotonicityNot monotonic
2023-12-13T05:13:06.947913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8 575
 
7.7%
12 460
 
6.2%
18 454
 
6.1%
17 446
 
6.0%
9 325
 
4.4%
10 325
 
4.4%
11 319
 
4.3%
6 300
 
4.0%
14 273
 
3.7%
7 270
 
3.6%
Other values (18) 3707
49.7%
ValueCountFrequency (%)
1 241
3.2%
2 164
 
2.2%
3 207
 
2.8%
4 216
 
2.9%
5 242
3.2%
6 300
4.0%
7 270
3.6%
8 575
7.7%
9 325
4.4%
10 325
4.4%
ValueCountFrequency (%)
28 133
1.8%
27 119
1.6%
26 233
3.1%
25 168
2.3%
24 255
3.4%
23 172
2.3%
22 114
1.5%
21 265
3.6%
20 242
3.2%
19 176
2.4%

유형ID
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6577676
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:07.064377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35
95-th percentile8
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5354051
Coefficient of variation (CV)0.95396042
Kurtosis1.0159405
Mean2.6577676
Median Absolute Deviation (MAD)0
Skewness1.4401255
Sum19811
Variance6.4282793
MonotonicityNot monotonic
2023-12-13T05:13:07.181941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 4383
58.8%
5 858
 
11.5%
2 754
 
10.1%
6 382
 
5.1%
7 313
 
4.2%
3 293
 
3.9%
10 292
 
3.9%
8 73
 
1.0%
9 68
 
0.9%
4 38
 
0.5%
ValueCountFrequency (%)
1 4383
58.8%
2 754
 
10.1%
3 293
 
3.9%
4 38
 
0.5%
5 858
 
11.5%
6 382
 
5.1%
7 313
 
4.2%
8 73
 
1.0%
9 68
 
0.9%
10 292
 
3.9%
ValueCountFrequency (%)
10 292
 
3.9%
9 68
 
0.9%
8 73
 
1.0%
7 313
 
4.2%
6 382
 
5.1%
5 858
 
11.5%
4 38
 
0.5%
3 293
 
3.9%
2 754
 
10.1%
1 4383
58.8%

상위주제ID
Real number (ℝ)

HIGH CORRELATION 

Distinct1950
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4192.5447
Minimum1
Maximum10545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:07.293711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile43
Q11643
median3622.5
Q36204
95-th percentile10336
Maximum10545
Range10544
Interquartile range (IQR)4561

Descriptive statistics

Standard deviation2992.2246
Coefficient of variation (CV)0.71370131
Kurtosis-0.7120909
Mean4192.5447
Median Absolute Deviation (MAD)2224.5
Skewness0.48711294
Sum31251228
Variance8953408.3
MonotonicityNot monotonic
2023-12-13T05:13:07.433321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6206 47
 
0.6%
813 41
 
0.6%
6197 38
 
0.5%
1427 37
 
0.5%
5853 36
 
0.5%
10308 30
 
0.4%
5155 29
 
0.4%
18 29
 
0.4%
7213 26
 
0.3%
11 25
 
0.3%
Other values (1940) 7116
95.5%
ValueCountFrequency (%)
1 9
 
0.1%
2 8
 
0.1%
3 5
 
0.1%
4 8
 
0.1%
5 9
 
0.1%
6 6
 
0.1%
7 14
0.2%
8 24
0.3%
9 15
0.2%
10 16
0.2%
ValueCountFrequency (%)
10545 2
 
< 0.1%
10536 2
 
< 0.1%
10535 1
 
< 0.1%
10534 8
0.1%
10533 4
0.1%
10532 3
 
< 0.1%
10531 1
 
< 0.1%
10530 4
0.1%
10529 3
 
< 0.1%
10528 5
0.1%

집필자 상세정보
Text

Distinct330
Distinct (%)4.5%
Missing69
Missing (%)0.9%
Memory size58.4 KiB
2023-12-13T05:13:07.634404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length50
Mean length20.329181
Min length3

Characters and Unicode

Total characters150131
Distinct characters251
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)1.1%

Sample

1st row한범수(경기대학교 관광개발학과 교수)
2nd row전대양(관동대학교 경찰행정학과 교수)
3rd row전대양(관동대학교 경찰행정학과 교수)
4th row전대양(관동대학교 경찰행정학과 교수)
5th row전대양(관동대학교 경찰행정학과 교수)
ValueCountFrequency (%)
교수 3800
 
17.1%
연구위원 658
 
3.0%
행정학과 517
 
2.3%
법학과 447
 
2.0%
경제학과 379
 
1.7%
성신여대 347
 
1.6%
부연구위원 337
 
1.5%
등 335
 
1.5%
산학협력단(성신여대 319
 
1.4%
정치외교학과 317
 
1.4%
Other values (419) 14810
66.5%
2023-12-13T05:13:07.974273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14875
 
9.9%
교 8863
 
5.9%
학 8581
 
5.7%
( 7374
 
4.9%
) 7370
 
4.9%
대 6436
 
4.3%
수 4997
 
3.3%
연 4658
 
3.1%
구 4656
 
3.1%
원 4394
 
2.9%
Other values (241) 77927
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118135
78.7%
Space Separator 14875
 
9.9%
Open Punctuation 7375
 
4.9%
Close Punctuation 7373
 
4.9%
Decimal Number 1620
 
1.1%
Other Punctuation 597
 
0.4%
Uppercase Letter 150
 
0.1%
Control 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 8863
 
7.5%
학 8581
 
7.3%
대 6436
 
5.4%
수 4997
 
4.2%
연 4658
 
3.9%
구 4656
 
3.9%
원 4394
 
3.7%
과 3947
 
3.3%
정 3314
 
2.8%
국 2967
 
2.5%
Other values (217) 65322
55.3%
Decimal Number
ValueCountFrequency (%)
0 807
49.8%
1 347
21.4%
7 230
 
14.2%
4 118
 
7.3%
2 115
 
7.1%
9 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 322
53.9%
· 236
39.5%
/ 33
 
5.5%
# 2
 
0.3%
& 2
 
0.3%
; 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 7370
> 99.9%
） 2
 
< 0.1%
》 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
U 50
33.3%
I 50
33.3%
R 50
33.3%
Open Punctuation
ValueCountFrequency (%)
( 7374
> 99.9%
《 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
14875
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118135
78.7%
Common 31846
 
21.2%
Latin 150
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 8863
 
7.5%
학 8581
 
7.3%
대 6436
 
5.4%
수 4997
 
4.2%
연 4658
 
3.9%
구 4656
 
3.9%
원 4394
 
3.7%
과 3947
 
3.3%
정 3314
 
2.8%
국 2967
 
2.5%
Other values (217) 65322
55.3%
Common
ValueCountFrequency (%)
14875
46.7%
( 7374
23.2%
) 7370
23.1%
0 807
 
2.5%
1 347
 
1.1%
, 322
 
1.0%
· 236
 
0.7%
7 230
 
0.7%
4 118
 
0.4%
2 115
 
0.4%
Other values (11) 52
 
0.2%
Latin
ValueCountFrequency (%)
U 50
33.3%
I 50
33.3%
R 50
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118135
78.7%
ASCII 31756
 
21.2%
None 240
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14875
46.8%
( 7374
23.2%
) 7370
23.2%
0 807
 
2.5%
1 347
 
1.1%
, 322
 
1.0%
7 230
 
0.7%
4 118
 
0.4%
2 115
 
0.4%
U 50
 
0.2%
Other values (10) 148
 
0.5%
Hangul
ValueCountFrequency (%)
교 8863
 
7.5%
학 8581
 
7.3%
대 6436
 
5.4%
수 4997
 
4.2%
연 4658
 
3.9%
구 4656
 
3.9%
원 4394
 
3.7%
과 3947
 
3.3%
정 3314
 
2.8%
국 2967
 
2.5%
Other values (217) 65322
55.3%
None
ValueCountFrequency (%)
· 236
98.3%
） 2
 
0.8%
》 1
 
0.4%
《 1
 
0.4%

분야ID.1
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.551113
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:08.093314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median13
Q319
95-th percentile26
Maximum28
Range27
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.1958478
Coefficient of variation (CV)0.53101524
Kurtosis-0.91837494
Mean13.551113
Median Absolute Deviation (MAD)5
Skewness0.17832407
Sum101010
Variance51.780226
MonotonicityNot monotonic
2023-12-13T05:13:08.213864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8 575
 
7.7%
12 460
 
6.2%
18 454
 
6.1%
17 446
 
6.0%
9 325
 
4.4%
10 325
 
4.4%
11 319
 
4.3%
6 300
 
4.0%
14 273
 
3.7%
7 270
 
3.6%
Other values (18) 3707
49.7%
ValueCountFrequency (%)
1 241
3.2%
2 164
 
2.2%
3 207
 
2.8%
4 216
 
2.9%
5 242
3.2%
6 300
4.0%
7 270
3.6%
8 575
7.7%
9 325
4.4%
10 325
4.4%
ValueCountFrequency (%)
28 133
1.8%
27 119
1.6%
26 233
3.1%
25 168
2.3%
24 255
3.4%
23 172
2.3%
22 114
1.5%
21 265
3.6%
20 242
3.2%
19 176
2.4%

분야명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size58.4 KiB
외교
575 
국방/병무
 
460
농림해양수산
 
454
인사/조직
 
446
국무조정
 
325
Other values (23)
5194 

Length

Max length8
Median length7
Mean length4.193319
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화체육관광
2nd row공공질서
3rd row공공질서
4th row공공질서
5th row공공질서

Common Values

ValueCountFrequency (%)
외교 575
 
7.7%
국방/병무 460
 
6.2%
농림해양수산 454
 
6.1%
인사/조직 446
 
6.0%
국무조정 325
 
4.4%
공공질서 325
 
4.4%
교육 319
 
4.3%
지방행정 300
 
4.0%
법무/법제 273
 
3.7%
문화체육관광 270
 
3.6%
Other values (18) 3707
49.7%

Length

2023-12-13T05:13:08.385172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
외교 575
 
7.7%
국방/병무 460
 
6.2%
농림해양수산 454
 
6.1%
인사/조직 446
 
6.0%
국무조정 325
 
4.4%
공공질서 325
 
4.4%
교육 319
 
4.3%
지방행정 300
 
4.0%
법무/법제 273
 
3.7%
문화체육관광 270
 
3.6%
Other values (18) 3707
49.7%

유형ID.1
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing38
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean2.65089
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.6 KiB
2023-12-13T05:13:08.492520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35
95-th percentile8
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5400674
Coefficient of variation (CV)0.95819422
Kurtosis1.0222099
Mean2.65089
Median Absolute Deviation (MAD)0
Skewness1.4469206
Sum19659
Variance6.4519426
MonotonicityNot monotonic
2023-12-13T05:13:08.590451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 4383
58.8%
5 858
 
11.5%
2 754
 
10.1%
6 382
 
5.1%
7 313
 
4.2%
3 293
 
3.9%
10 292
 
3.9%
8 73
 
1.0%
9 68
 
0.9%
(Missing) 38
 
0.5%
ValueCountFrequency (%)
1 4383
58.8%
2 754
 
10.1%
3 293
 
3.9%
5 858
 
11.5%
6 382
 
5.1%
7 313
 
4.2%
8 73
 
1.0%
9 68
 
0.9%
10 292
 
3.9%
ValueCountFrequency (%)
10 292
 
3.9%
9 68
 
0.9%
8 73
 
1.0%
7 313
 
4.2%
6 382
 
5.1%
5 858
 
11.5%
3 293
 
3.9%
2 754
 
10.1%
1 4383
58.8%

유형명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.4 KiB
정책/제도
4383 
조직/기구
858 
사업
754 
사건/사고
 
382
조약/회담
 
313
Other values (5)
764 

Length

Max length6
Median length5
Mean length4.5536625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row회의
2nd row역사적사건
3rd row조직/기구
4th row정책/제도
5th row조약/회담

Common Values

ValueCountFrequency (%)
정책/제도 4383
58.8%
조직/기구 858
 
11.5%
사업 754
 
10.1%
사건/사고 382
 
5.1%
조약/회담 313
 
4.2%
역사적사건 293
 
3.9%
기타 292
 
3.9%
회의 73
 
1.0%
행사/이벤트 68
 
0.9%
<NA> 38
 
0.5%

Length

2023-12-13T05:13:08.709408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:08.837163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정책/제도 4383
58.8%
조직/기구 858
 
11.5%
사업 754
 
10.1%
사건/사고 382
 
5.1%
조약/회담 313
 
4.2%
역사적사건 293
 
3.9%
기타 292
 
3.9%
회의 73
 
1.0%
행사/이벤트 68
 
0.9%
na 38
 
0.5%

주제명2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

주제서술항목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

주제분야담당자지정내역ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

주제서술항목서술내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

주제콘텐츠업무기능연관ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

주제서술 연관내역ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7454
Missing (%)100.0%
Memory size65.6 KiB

Interactions

2023-12-13T05:13:01.641208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:58.694956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.183030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.653414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.317871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.008053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.754276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:58.770145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.254814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.734390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.438448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.121896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.884977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:58.845632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.341289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.886145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.562564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.246185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.977859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:58.927176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.422611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.983219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.671922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.347428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:02.069005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.019313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.505663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.087597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.790821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.443919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:02.177110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.108866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:59.580571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.205230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:00.899078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:01.542158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:13:08.958148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주제유형분야ID서비스구분분야ID유형ID상위주제ID분야ID.1분야명유형ID.1유형명
주제유형분야ID1.0000.5320.7780.4620.9450.7780.8590.3440.344
서비스구분0.5321.0000.5180.4950.5300.5180.7500.6140.614
분야ID0.7780.5181.0000.4860.8081.0001.0000.3570.357
유형ID0.4620.4950.4861.0000.4420.4860.6391.0001.000
상위주제ID0.9450.5300.8080.4421.0000.8080.8700.3220.322
분야ID.10.7780.5181.0000.4860.8081.0001.0000.3570.357
분야명0.8590.7501.0000.6390.8701.0001.0000.6370.637
유형ID.10.3440.6140.3571.0000.3220.3570.6371.0001.000
유형명0.3440.6140.3571.0000.3220.3570.6371.0001.000
2023-12-13T05:13:09.060294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야명서비스구분유형명
분야명1.0000.5340.297
서비스구분0.5341.0000.336
유형명0.2970.3361.000
2023-12-13T05:13:09.168065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주제유형분야ID분야ID유형ID상위주제ID분야ID.1유형ID.1서비스구분분야명유형명
주제유형분야ID1.0000.133-0.0840.4730.133-0.0870.3770.5260.164
분야ID0.1331.000-0.1210.0891.000-0.1200.3630.9990.171
유형ID-0.084-0.1211.000-0.004-0.1211.0000.3420.2881.000
상위주제ID0.4730.089-0.0041.0000.089-0.0070.3740.5450.152
분야ID.10.1331.000-0.1210.0891.000-0.1200.3630.9990.171
유형ID.1-0.087-0.1201.000-0.007-0.1201.0000.3360.2971.000
서비스구분0.3770.3630.3420.3740.3630.3361.0000.5340.336
분야명0.5260.9990.2880.5450.9990.2970.5341.0000.297
유형명0.1640.1711.0000.1520.1711.0000.3360.2971.000

Missing values

2023-12-13T05:13:02.325606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:13:02.581283image/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.
2023-12-13T05:13:02.777909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

주제유형분야ID주제명주제설명서비스구분주제 등록일자분야ID유형ID상위주제ID집필자 상세정보분야ID.1분야명유형ID.1유형명주제명2주제서술항목명주제분야담당자지정내역ID주제서술항목서술내용주제콘텐츠업무기능연관ID주제서술 연관내역ID
03609남북체육회담<NA>Y20061116 14:38783607한범수(경기대학교 관광개발학과 교수)7문화체육관광8회의<NA><NA><NA><NA><NA><NA>
14381한일회담 반대시위(6.3사태)한일회담반대시위(6.3사태)N20070813 11:071031013전대양(관동대학교 경찰행정학과 교수)10공공질서3역사적사건<NA><NA><NA><NA><NA><NA>
24422해양경찰학교해양경찰학교Y20070813 11:071054420전대양(관동대학교 경찰행정학과 교수)10공공질서5조직/기구<NA><NA><NA><NA><NA><NA>
34423국제협력활동국제협력활동Y20070813 11:071014419전대양(관동대학교 경찰행정학과 교수)10공공질서1정책/제도<NA><NA><NA><NA><NA><NA>
44424SAR협약SAR협약Y20070813 11:071074423전대양(관동대학교 경찰행정학과 교수)10공공질서7조약/회담<NA><NA><NA><NA><NA><NA>
54425유엔해양법 협약유엔해양법 협약Y20070813 11:071074423전대양(관동대학교 경찰행정학과 교수)10공공질서7조약/회담<NA><NA><NA><NA><NA><NA>
64427해상경비해상경비와 대테러Y20070813 11:0710110전대양(관동대학교 경찰행정학과 교수)10공공질서1정책/제도<NA><NA><NA><NA><NA><NA>
74428해양주권수호해양주권수호Y20070813 11:071014427전대양(관동대학교 경찰행정학과 교수)10공공질서1정책/제도<NA><NA><NA><NA><NA><NA>
84429어업자원보호법어업자원보호법Y20070813 11:071014428전대양(관동대학교 경찰행정학과 교수)10공공질서1정책/제도<NA><NA><NA><NA><NA><NA>
94430배타적 경제수역법배타적 경제수역법Y20070813 11:071014428전대양(관동대학교 경찰행정학과 교수)10공공질서1정책/제도<NA><NA><NA><NA><NA><NA>
주제유형분야ID주제명주제설명서비스구분주제 등록일자분야ID유형ID상위주제ID집필자 상세정보분야ID.1분야명유형ID.1유형명주제명2주제서술항목명주제분야담당자지정내역ID주제서술항목서술내용주제콘텐츠업무기능연관ID주제서술 연관내역ID
744410535소련(러시아)와 경제협력소련(러시아)와 경제협력Y20171027 13:478110496성신여대 산학협력단(성신여대 정치외교학과 교수 등)8외교1정책/제도<NA><NA><NA><NA><NA><NA>
744510536동구권과 정상외교동구권과 정상외교Y20171027 13:478110497황지환(서울대 통일연구소 선임연구원)8외교1정책/제도<NA><NA><NA><NA><NA><NA>
744610538동북아안보대화(NEASeD) 창설 제안동북아안보대화(NEASeD) 제안Y20171027 13:478510505이대우(세종연구소 수석연구위원)8외교5조직/기구<NA><NA><NA><NA><NA><NA>
744710539아세안 지역안보포럼(ARF) 출범아세안 지역안보포럼(ARF) 출범Y20171027 13:478510505이대우(세종연구소 수석연구위원)8외교5조직/기구<NA><NA><NA><NA><NA><NA>
744810540아태안보협력이사회(CSCAP) 출범아태안보협력이사회(CSCAP) 출범Y20171027 13:478510505이대우(세종연구소 수석연구위원)8외교5조직/기구<NA><NA><NA><NA><NA><NA>
744910541유라시아 이니셔티브유라시아 이니셔티브Y20171027 13:478110507이대우(세종연구소 수석연구위원)8외교1정책/제도<NA><NA><NA><NA><NA><NA>
745010542주한미군 기지이전주한미군 기지이전Y20171027 13:478110510이대우(세종연구소 수석연구위원)8외교1정책/제도<NA><NA><NA><NA><NA><NA>
74511054310·4 남북 정상회담과 남북공동선언10·4 남북 정상회담과 남북공동선언Y20171027 13:478310515이대우(세종연구소 수석연구위원)8외교3역사적사건<NA><NA><NA><NA><NA><NA>
7452105444자회담 출범4자회담 출범Y20171027 13:478510516이대우(세종연구소 수석연구위원)8외교5조직/기구<NA><NA><NA><NA><NA><NA>
745310545동북아시아 외교협력동북아시아 외교협력Y20171027 13:478110495이대우(세종연구소 수석연구위원)8외교1정책/제도<NA><NA><NA><NA><NA><NA>