Overview

Dataset statistics

Number of variables9
Number of observations478
Missing cells290
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.7 KiB
Average record size in memory72.3 B

Variable types

Text6
DateTime3

Dataset

Description국립과학수사연구원 사전정보공표 목록 (국가기관 및 지방자치단체 등 공공기관에서 어떤 일을 하고 있고 예산을 어떻게 집행하고 있는지 국민들이 알 수 있도록 공공기관이 보유 및 관리하고 있는 정보를 국민에게 공개하는 것)
Author행정안전부 국립과학수사연구원
URLhttps://www.data.go.kr/data/15061576/fileData.do

Alerts

파일아이디 has 69 (14.4%) missing valuesMissing
작성자 has 112 (23.4%) missing valuesMissing
내용 has 109 (22.8%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:42:09.687327
Analysis finished2023-12-11 23:42:10.857380
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Text

UNIQUE 

Distinct478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T08:42:11.002215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters6692
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique478 ?
Unique (%)100.0%

Sample

1st rowNFS_PD00000142
2nd rowNFS_PD00000150
3rd rowNFS_PD00000151
4th rowNFS_PD00000152
5th rowNFS_PD00000153
ValueCountFrequency (%)
nfs_pd00000142 1
 
0.2%
nfs_pd00000313 1
 
0.2%
nfs_pd00000511 1
 
0.2%
nfs_pd00000460 1
 
0.2%
nfs_pd00000458 1
 
0.2%
nfs_pd00000459 1
 
0.2%
nfs_pd00000451 1
 
0.2%
nfs_pd00000449 1
 
0.2%
nfs_pd00000448 1
 
0.2%
nfs_pd00000504 1
 
0.2%
Other values (468) 468
97.9%
2023-12-12T08:42:11.353026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2493
37.3%
N 478
 
7.1%
F 478
 
7.1%
S 478
 
7.1%
_ 478
 
7.1%
P 478
 
7.1%
D 478
 
7.1%
3 182
 
2.7%
1 176
 
2.6%
6 173
 
2.6%
Other values (6) 800
 
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3824
57.1%
Uppercase Letter 2390
35.7%
Connector Punctuation 478
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2493
65.2%
3 182
 
4.8%
1 176
 
4.6%
6 173
 
4.5%
2 168
 
4.4%
4 166
 
4.3%
5 149
 
3.9%
7 127
 
3.3%
9 103
 
2.7%
8 87
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N 478
20.0%
F 478
20.0%
S 478
20.0%
P 478
20.0%
D 478
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 478
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4302
64.3%
Latin 2390
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2493
57.9%
_ 478
 
11.1%
3 182
 
4.2%
1 176
 
4.1%
6 173
 
4.0%
2 168
 
3.9%
4 166
 
3.9%
5 149
 
3.5%
7 127
 
3.0%
9 103
 
2.4%
Latin
ValueCountFrequency (%)
N 478
20.0%
F 478
20.0%
S 478
20.0%
P 478
20.0%
D 478
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2493
37.3%
N 478
 
7.1%
F 478
 
7.1%
S 478
 
7.1%
_ 478
 
7.1%
P 478
 
7.1%
D 478
 
7.1%
3 182
 
2.7%
1 176
 
2.6%
6 173
 
2.6%
Other values (6) 800
 
12.0%

사전정보공표 일련번호
Text

Distinct227
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T08:42:11.648481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters6692
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)29.1%

Sample

1st rowNFS_PL00000183
2nd rowNFS_PL00000178
3rd rowNFS_PL00000177
4th rowNFS_PL00000172
5th rowNFS_PL00000167
ValueCountFrequency (%)
nfs_pl00000259 55
 
11.5%
nfs_pl00000354 18
 
3.8%
nfs_pl00000230 7
 
1.5%
nfs_pl00000051 7
 
1.5%
nfs_pl00000056 7
 
1.5%
nfs_pl00000185 7
 
1.5%
nfs_pl00000334 6
 
1.3%
nfs_pl00000288 6
 
1.3%
nfs_pl00000275 6
 
1.3%
nfs_pl00000239 6
 
1.3%
Other values (217) 353
73.8%
2023-12-12T08:42:12.038362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2544
38.0%
N 478
 
7.1%
F 478
 
7.1%
S 478
 
7.1%
_ 478
 
7.1%
P 478
 
7.1%
L 478
 
7.1%
2 267
 
4.0%
1 204
 
3.0%
3 199
 
3.0%
Other values (6) 610
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3824
57.1%
Uppercase Letter 2390
35.7%
Connector Punctuation 478
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2544
66.5%
2 267
 
7.0%
1 204
 
5.3%
3 199
 
5.2%
5 171
 
4.5%
9 116
 
3.0%
4 102
 
2.7%
8 85
 
2.2%
6 72
 
1.9%
7 64
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 478
20.0%
F 478
20.0%
S 478
20.0%
P 478
20.0%
L 478
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 478
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4302
64.3%
Latin 2390
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2544
59.1%
_ 478
 
11.1%
2 267
 
6.2%
1 204
 
4.7%
3 199
 
4.6%
5 171
 
4.0%
9 116
 
2.7%
4 102
 
2.4%
8 85
 
2.0%
6 72
 
1.7%
Latin
ValueCountFrequency (%)
N 478
20.0%
F 478
20.0%
S 478
20.0%
P 478
20.0%
L 478
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2544
38.0%
N 478
 
7.1%
F 478
 
7.1%
S 478
 
7.1%
_ 478
 
7.1%
P 478
 
7.1%
L 478
 
7.1%
2 267
 
4.0%
1 204
 
3.0%
3 199
 
3.0%
Other values (6) 610
 
9.1%

파일아이디
Text

MISSING 

Distinct409
Distinct (%)100.0%
Missing69
Missing (%)14.4%
Memory size3.9 KiB
2023-12-12T08:42:12.266734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8180
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique409 ?
Unique (%)100.0%

Sample

1st rowFILE_000000001000267
2nd rowFILE_000000001000275
3rd rowFILE_000000001000276
4th rowFILE_000000001000277
5th rowFILE_000000001000278
ValueCountFrequency (%)
file_000000001000288 1
 
0.2%
file_000000001000409 1
 
0.2%
file_000000001000801 1
 
0.2%
file_000000001000800 1
 
0.2%
file_000000001000802 1
 
0.2%
file_000000001000803 1
 
0.2%
file_000000001000808 1
 
0.2%
file_000000001000567 1
 
0.2%
file_000000001000764 1
 
0.2%
file_000000001000556 1
 
0.2%
Other values (399) 399
97.6%
2023-12-12T08:42:12.613200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4572
55.9%
1 474
 
5.8%
F 409
 
5.0%
I 409
 
5.0%
L 409
 
5.0%
E 409
 
5.0%
_ 409
 
5.0%
7 169
 
2.1%
6 164
 
2.0%
4 152
 
1.9%
Other values (5) 604
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6135
75.0%
Uppercase Letter 1636
 
20.0%
Connector Punctuation 409
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4572
74.5%
1 474
 
7.7%
7 169
 
2.8%
6 164
 
2.7%
4 152
 
2.5%
5 149
 
2.4%
2 130
 
2.1%
3 123
 
2.0%
8 102
 
1.7%
9 100
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
F 409
25.0%
I 409
25.0%
L 409
25.0%
E 409
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 409
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6544
80.0%
Latin 1636
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4572
69.9%
1 474
 
7.2%
_ 409
 
6.2%
7 169
 
2.6%
6 164
 
2.5%
4 152
 
2.3%
5 149
 
2.3%
2 130
 
2.0%
3 123
 
1.9%
8 102
 
1.6%
Latin
ValueCountFrequency (%)
F 409
25.0%
I 409
25.0%
L 409
25.0%
E 409
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4572
55.9%
1 474
 
5.8%
F 409
 
5.0%
I 409
 
5.0%
L 409
 
5.0%
E 409
 
5.0%
_ 409
 
5.0%
7 169
 
2.1%
6 164
 
2.0%
4 152
 
1.9%
Other values (5) 604
 
7.4%

제목
Text

Distinct416
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T08:42:12.987780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length16.707113
Min length4

Characters and Unicode

Total characters7986
Distinct characters331
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)79.3%

Sample

1st rowKOLAS 공인인증서 작성기준안내
2nd row연구실 안전교육
3rd row안전사고예방관련
4th row2016년 이공학과 월별 감정의뢰건수
5th row청사시설물 개보수 현황
ValueCountFrequency (%)
현황 47
 
2.8%
목록 46
 
2.8%
2018년 38
 
2.3%
출장결과보고서 37
 
2.2%
2017년 35
 
2.1%
2016년 31
 
1.9%
국립과학수사연구원 29
 
1.8%
및 24
 
1.5%
2019년 23
 
1.4%
2018 21
 
1.3%
Other values (603) 1323
80.0%
2023-12-12T08:42:13.510813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1177
 
14.7%
1 332
 
4.2%
0 301
 
3.8%
2 237
 
3.0%
과 204
 
2.6%
년 175
 
2.2%
학 159
 
2.0%
수 140
 
1.8%
기 114
 
1.4%
사 109
 
1.4%
Other values (321) 5038
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5218
65.3%
Decimal Number 1251
 
15.7%
Space Separator 1177
 
14.7%
Uppercase Letter 121
 
1.5%
Lowercase Letter 82
 
1.0%
Close Punctuation 44
 
0.6%
Open Punctuation 44
 
0.6%
Other Punctuation 27
 
0.3%
Dash Punctuation 14
 
0.2%
Connector Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 204
 
3.9%
년 175
 
3.4%
학 159
 
3.0%
수 140
 
2.7%
기 114
 
2.2%
사 109
 
2.1%
정 109
 
2.1%
연 102
 
2.0%
구 101
 
1.9%
장 98
 
1.9%
Other values (266) 3907
74.9%
Uppercase Letter
ValueCountFrequency (%)
S 16
13.2%
A 16
13.2%
I 12
9.9%
O 11
9.1%
D 8
 
6.6%
N 7
 
5.8%
L 7
 
5.8%
M 6
 
5.0%
F 6
 
5.0%
C 6
 
5.0%
Other values (8) 26
21.5%
Lowercase Letter
ValueCountFrequency (%)
e 11
13.4%
i 9
11.0%
n 8
9.8%
r 8
9.8%
o 8
9.8%
t 8
9.8%
c 5
6.1%
a 5
6.1%
s 5
6.1%
m 4
 
4.9%
Other values (6) 11
13.4%
Decimal Number
ValueCountFrequency (%)
1 332
26.5%
0 301
24.1%
2 237
18.9%
9 107
 
8.6%
8 91
 
7.3%
7 61
 
4.9%
6 55
 
4.4%
5 30
 
2.4%
4 19
 
1.5%
3 18
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 20
74.1%
& 3
 
11.1%
. 2
 
7.4%
· 1
 
3.7%
/ 1
 
3.7%
Space Separator
ValueCountFrequency (%)
1177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5218
65.3%
Common 2565
32.1%
Latin 203
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 204
 
3.9%
년 175
 
3.4%
학 159
 
3.0%
수 140
 
2.7%
기 114
 
2.2%
사 109
 
2.1%
정 109
 
2.1%
연 102
 
2.0%
구 101
 
1.9%
장 98
 
1.9%
Other values (266) 3907
74.9%
Latin
ValueCountFrequency (%)
S 16
 
7.9%
A 16
 
7.9%
I 12
 
5.9%
O 11
 
5.4%
e 11
 
5.4%
i 9
 
4.4%
n 8
 
3.9%
r 8
 
3.9%
o 8
 
3.9%
t 8
 
3.9%
Other values (24) 96
47.3%
Common
ValueCountFrequency (%)
1177
45.9%
1 332
 
12.9%
0 301
 
11.7%
2 237
 
9.2%
9 107
 
4.2%
8 91
 
3.5%
7 61
 
2.4%
6 55
 
2.1%
) 44
 
1.7%
( 44
 
1.7%
Other values (11) 116
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5218
65.3%
ASCII 2767
34.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1177
42.5%
1 332
 
12.0%
0 301
 
10.9%
2 237
 
8.6%
9 107
 
3.9%
8 91
 
3.3%
7 61
 
2.2%
6 55
 
2.0%
) 44
 
1.6%
( 44
 
1.6%
Other values (44) 318
 
11.5%
Hangul
ValueCountFrequency (%)
과 204
 
3.9%
년 175
 
3.4%
학 159
 
3.0%
수 140
 
2.7%
기 114
 
2.2%
사 109
 
2.1%
정 109
 
2.1%
연 102
 
2.0%
구 101
 
1.9%
장 98
 
1.9%
Other values (266) 3907
74.9%
None
ValueCountFrequency (%)
· 1
100.0%

작성자
Text

MISSING 

Distinct64
Distinct (%)17.5%
Missing112
Missing (%)23.4%
Memory size3.9 KiB
2023-12-12T08:42:13.735228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1912568
Min length3

Characters and Unicode

Total characters1168
Distinct characters92
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)4.1%

Sample

1st row공보경
2nd row운영지원과
3rd row운영지원과
4th row신동일
5th row신동일
ValueCountFrequency (%)
변호정 33
 
9.0%
신동일 25
 
6.8%
박정욱 24
 
6.6%
이종혁 19
 
5.2%
권순철 19
 
5.2%
장종임 19
 
5.2%
신용익 13
 
3.6%
이동하 13
 
3.6%
연구기획과 12
 
3.3%
박명철 12
 
3.3%
Other values (54) 177
48.4%
2023-12-12T08:42:14.152610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 70
 
6.0%
이 46
 
3.9%
김 43
 
3.7%
동 41
 
3.5%
호 41
 
3.5%
박 39
 
3.3%
종 38
 
3.3%
신 38
 
3.3%
영 35
 
3.0%
변 33
 
2.8%
Other values (82) 744
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1163
99.6%
Lowercase Letter 4
 
0.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 70
 
6.0%
이 46
 
4.0%
김 43
 
3.7%
동 41
 
3.5%
호 41
 
3.5%
박 39
 
3.4%
종 38
 
3.3%
신 38
 
3.3%
영 35
 
3.0%
변 33
 
2.8%
Other values (78) 739
63.5%
Lowercase Letter
ValueCountFrequency (%)
t 2
50.0%
s 1
25.0%
e 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1163
99.6%
Latin 4
 
0.3%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 70
 
6.0%
이 46
 
4.0%
김 43
 
3.7%
동 41
 
3.5%
호 41
 
3.5%
박 39
 
3.4%
종 38
 
3.3%
신 38
 
3.3%
영 35
 
3.0%
변 33
 
2.8%
Other values (78) 739
63.5%
Latin
ValueCountFrequency (%)
t 2
50.0%
s 1
25.0%
e 1
25.0%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1163
99.6%
ASCII 5
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 70
 
6.0%
이 46
 
4.0%
김 43
 
3.7%
동 41
 
3.5%
호 41
 
3.5%
박 39
 
3.4%
종 38
 
3.3%
신 38
 
3.3%
영 35
 
3.0%
변 33
 
2.8%
Other values (78) 739
63.5%
ASCII
ValueCountFrequency (%)
t 2
40.0%
2 1
20.0%
s 1
20.0%
e 1
20.0%

작성일
Date

Distinct133
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2012-11-07 00:00:00
Maximum2020-03-30 00:00:00
2023-12-12T08:42:14.295104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:42:14.477542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록일자
Date

Distinct233
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2017-11-08 11:51:26.260000
Maximum2020-03-30 15:57:20.200000
2023-12-12T08:42:14.628809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:42:14.806236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일자
Date

Distinct241
Distinct (%)50.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2017-11-08 11:51:26.260000
Maximum2020-03-30 15:57:20.200000
2023-12-12T08:42:14.989320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:42:15.133383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

내용
Text

MISSING 

Distinct301
Distinct (%)81.6%
Missing109
Missing (%)22.8%
Memory size3.9 KiB
2023-12-12T08:42:15.491574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length206
Median length59
Mean length23.373984
Min length4

Characters and Unicode

Total characters8625
Distinct characters375
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique266 ?
Unique (%)72.1%

Sample

1st row2016년 연구실안전교육
2nd row2016년 연구실 현장지도 점검 보고
3rd row2016년 1월-10월의 이공학과 월별 감정의뢰건수입니다.
4th row2016년 대전과학수사연구소 청사시설물 개보수 현황입니다.
5th row2016년 대전과학수사연구소 주요업무계획입니다.
ValueCountFrequency (%)
2016년 42
 
2.5%
39
 
2.4%
현황 31
 
1.9%
2018년 30
 
1.8%
목록 29
 
1.8%
대전과학수사연구소 28
 
1.7%
및 23
 
1.4%
개정전문 17
 
1.0%
2019년 16
 
1.0%
2019 14
 
0.8%
Other values (695) 1387
83.8%
2023-12-12T08:42:16.059896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1288
 
14.9%
1 236
 
2.7%
0 217
 
2.5%
2 215
 
2.5%
과 174
 
2.0%
. 154
 
1.8%
학 142
 
1.6%
정 130
 
1.5%
수 126
 
1.5%
사 120
 
1.4%
Other values (365) 5823
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5163
59.9%
Space Separator 1288
 
14.9%
Decimal Number 947
 
11.0%
Lowercase Letter 559
 
6.5%
Other Punctuation 342
 
4.0%
Uppercase Letter 135
 
1.6%
Close Punctuation 78
 
0.9%
Open Punctuation 59
 
0.7%
Dash Punctuation 43
 
0.5%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 174
 
3.4%
학 142
 
2.8%
정 130
 
2.5%
수 126
 
2.4%
사 120
 
2.3%
년 119
 
2.3%
연 102
 
2.0%
전 102
 
2.0%
구 100
 
1.9%
기 95
 
1.8%
Other values (292) 3953
76.6%
Lowercase Letter
ValueCountFrequency (%)
t 70
12.5%
i 57
10.2%
o 41
 
7.3%
e 39
 
7.0%
n 39
 
7.0%
m 38
 
6.8%
a 37
 
6.6%
s 36
 
6.4%
r 32
 
5.7%
h 28
 
5.0%
Other values (13) 142
25.4%
Uppercase Letter
ValueCountFrequency (%)
S 20
14.8%
C 14
 
10.4%
O 10
 
7.4%
D 9
 
6.7%
A 9
 
6.7%
P 8
 
5.9%
M 8
 
5.9%
H 6
 
4.4%
I 6
 
4.4%
E 6
 
4.4%
Other values (12) 39
28.9%
Decimal Number
ValueCountFrequency (%)
1 236
24.9%
0 217
22.9%
2 215
22.7%
8 69
 
7.3%
6 62
 
6.5%
9 51
 
5.4%
7 33
 
3.5%
5 27
 
2.9%
4 21
 
2.2%
3 16
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 154
45.0%
, 71
20.8%
: 71
20.8%
/ 34
 
9.9%
' 8
 
2.3%
% 2
 
0.6%
· 1
 
0.3%
& 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 6
66.7%
+ 2
 
22.2%
∼ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 77
98.7%
』 1
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 58
98.3%
『 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1288
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5165
59.9%
Common 2766
32.1%
Latin 694
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 174
 
3.4%
학 142
 
2.7%
정 130
 
2.5%
수 126
 
2.4%
사 120
 
2.3%
년 119
 
2.3%
연 102
 
2.0%
전 102
 
2.0%
구 100
 
1.9%
기 95
 
1.8%
Other values (293) 3955
76.6%
Latin
ValueCountFrequency (%)
t 70
 
10.1%
i 57
 
8.2%
o 41
 
5.9%
e 39
 
5.6%
n 39
 
5.6%
m 38
 
5.5%
a 37
 
5.3%
s 36
 
5.2%
r 32
 
4.6%
h 28
 
4.0%
Other values (35) 277
39.9%
Common
ValueCountFrequency (%)
1288
46.6%
1 236
 
8.5%
0 217
 
7.8%
2 215
 
7.8%
. 154
 
5.6%
) 77
 
2.8%
, 71
 
2.6%
: 71
 
2.6%
8 69
 
2.5%
6 62
 
2.2%
Other values (17) 306
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5149
59.7%
ASCII 3456
40.1%
Compat Jamo 14
 
0.2%
None 5
 
0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1288
37.3%
1 236
 
6.8%
0 217
 
6.3%
2 215
 
6.2%
. 154
 
4.5%
) 77
 
2.2%
, 71
 
2.1%
: 71
 
2.1%
t 70
 
2.0%
8 69
 
2.0%
Other values (58) 988
28.6%
Hangul
ValueCountFrequency (%)
과 174
 
3.4%
학 142
 
2.8%
정 130
 
2.5%
수 126
 
2.4%
사 120
 
2.3%
년 119
 
2.3%
연 102
 
2.0%
전 102
 
2.0%
구 100
 
1.9%
기 95
 
1.8%
Other values (291) 3939
76.5%
Compat Jamo
ValueCountFrequency (%)
ㅇ 14
100.0%
None
ValueCountFrequency (%)
㈜ 2
40.0%
· 1
20.0%
『 1
20.0%
』 1
20.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

Missing values

2023-12-12T08:42:10.538704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:42:10.685907image/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.
2023-12-12T08:42:10.804268image/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

일련번호사전정보공표 일련번호파일아이디제목작성자작성일등록일자수정일자내용
0NFS_PD00000142NFS_PL00000183FILE_000000001000267KOLAS 공인인증서 작성기준안내공보경2017-Nov-08 11:51:26.262017-Nov-08 11:51:26.262017-Nov-08 11:51:26.26<NA>
1NFS_PD00000150NFS_PL00000178FILE_000000001000275연구실 안전교육운영지원과2017-Nov-08 11:56:49.492017-Nov-08 11:56:49.492017-Nov-08 11:56:49.492016년 연구실안전교육
2NFS_PD00000151NFS_PL00000177FILE_000000001000276안전사고예방관련운영지원과2017-Nov-08 11:57:42.422017-Nov-08 11:57:42.422017-Nov-08 11:57:42.422016년 연구실 현장지도 점검 보고
3NFS_PD00000152NFS_PL00000172FILE_0000000010002772016년 이공학과 월별 감정의뢰건수신동일2017-Nov-08 12:00:11.112017-Nov-08 12:00:11.112017-Nov-08 12:00:11.112016년 1월-10월의 이공학과 월별 감정의뢰건수입니다.
4NFS_PD00000153NFS_PL00000167FILE_000000001000278청사시설물 개보수 현황신동일2017-Nov-08 12:01:20.202017-Nov-08 12:01:20.202017-Nov-08 12:01:20.202016년 대전과학수사연구소 청사시설물 개보수 현황입니다.
5NFS_PD00000154NFS_PL00000166FILE_0000000010002792016년 주요 업무계획신동일2017-Nov-08 12:02:47.472017-Nov-08 12:02:47.472017-Nov-08 12:02:47.472016년 대전과학수사연구소 주요업무계획입니다.
6NFS_PD00000155NFS_PL00000166FILE_0000000010002802017년 주요 업무계획신동일2017-Nov-08 12:02:47.472017-Nov-08 12:02:47.472017-Nov-08 12:02:47.47대전과학수사연구소 2017년 주요업무계획을 붙임으로 공개합니다.
7NFS_PD00000156NFS_PL00000164FILE_0000000010002812016년 월별 출장현황(1월-12월)신동일2017-Nov-08 12:36:58.582017-Nov-08 12:36:58.582017-Nov-08 12:36:58.58대전과학수사연구소 2016년 월별 출장현황을 붙임과 같이 공개합니다.
8NFS_PD00000157NFS_PL00000164FILE_0000000010002822016년 월별 출장현황신동일2017-Nov-08 12:36:58.582017-Nov-08 12:36:58.582017-Nov-08 12:36:58.582016년 대전과학수사연구소 월별 출장현황입니다
9NFS_PD00000158NFS_PL00000162FILE_000000001000283직장교육 실시 현황신동일2017-Nov-08 12:37:42.422017-Nov-08 12:37:42.422017-Nov-08 12:37:42.422016년 대전과학수사연구소 직장교육 실시 현황입니다.
일련번호사전정보공표 일련번호파일아이디제목작성자작성일등록일자수정일자내용
468NFS_PD00000701NFS_PL00000259<NA>190921 미국 국제개인식별학회 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10파일 용량이 큰 관계로 http://btis.mpm.go.kr 에서 확인
469NFS_PD00000702NFS_PL00000259<NA>191012 미국 법독성학회 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10파일 용량이 큰 관계로 http://btis.mpm.go.kr 에서 확인
470NFS_PD00000703NFS_PL00000259FILE_000000001000758191013 몽골 법과학역량강화사업 기획조사 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>
471NFS_PD00000704NFS_PL00000259FILE_000000001000759191013 미국 국제과학교류학회 참석 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>
472NFS_PD00000705NFS_PL00000259FILE_000000001000760191028 미국 국제혈흔형태분석학회 발표 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>
473NFS_PD00000706NFS_PL00000259FILE_000000001000761191102 스리랑카 검사 과학수사역량강화 세미나 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>
474NFS_PD00000707NFS_PL00000259<NA>191112 미국 범죄학회 참석 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10파일 용량이 큰 관계로 http://btis.mpm.go.kr 에서 확인
475NFS_PD00000708NFS_PL00000259FILE_000000001000762191114 대만 국제임상독성학회 참석 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>
476NFS_PD00000709NFS_PL00000259<NA>191125 싱가포르 Y-chromosome 워크숍 참석 출장결과보고서<NA>2020-Feb-27 0:00:00.002020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10파일 용량이 큰 관계로 http://btis.mpm.go.kr 에서 확인
477NFS_PD00000710NFS_PL00000259FILE_000000001000763191205 캐나다 식품위조안전학회 출장결과보고서<NA>2020-Feb-27 17:59:10.102020-Feb-27 17:59:10.102020-Feb-27 17:59:10.10<NA>