Overview

Dataset statistics

Number of variables8
Number of observations82
Missing cells134
Missing cells (%)20.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory65.6 B

Variable types

Text6
Categorical1
DateTime1

Dataset

Description순천시 지역 창업 생태계 데이터를 구축하여 지역기반 스타트업을 활성화하고자 순천시 일자리 지원 데이터를 제공합니다.
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15111429/fileData.do

Alerts

대상 has 3 (3.7%) missing valuesMissing
접수일자 has 43 (52.4%) missing valuesMissing
접수종료일자 has 45 (54.9%) missing valuesMissing
등록일자 has 43 (52.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:55:01.535749
Analysis finished2023-12-12 20:55:03.134431
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-13T05:55:03.296739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters1312
Distinct characters14
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

Unique82 ?
Unique (%)100.0%

Sample

1st rowREQ-003-09-00001
2nd rowREQ-003-09-00002
3rd rowREQ-003-09-00003
4th rowREQ-003-09-00004
5th rowREQ-003-09-00005
ValueCountFrequency (%)
req-003-09-00001 1
 
1.2%
req-003-09-00061 1
 
1.2%
req-003-09-00059 1
 
1.2%
req-003-09-00058 1
 
1.2%
req-003-09-00057 1
 
1.2%
req-003-09-00056 1
 
1.2%
req-003-09-00055 1
 
1.2%
req-003-09-00054 1
 
1.2%
req-003-09-00053 1
 
1.2%
req-003-09-00052 1
 
1.2%
Other values (72) 72
87.8%
2023-12-13T05:55:03.652370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 509
38.8%
- 246
18.8%
3 100
 
7.6%
9 90
 
6.9%
R 82
 
6.2%
E 82
 
6.2%
Q 82
 
6.2%
1 19
 
1.4%
2 19
 
1.4%
4 18
 
1.4%
Other values (4) 65
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 820
62.5%
Dash Punctuation 246
 
18.8%
Uppercase Letter 246
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 509
62.1%
3 100
 
12.2%
9 90
 
11.0%
1 19
 
2.3%
2 19
 
2.3%
4 18
 
2.2%
5 18
 
2.2%
6 18
 
2.2%
7 18
 
2.2%
8 11
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
R 82
33.3%
E 82
33.3%
Q 82
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1066
81.2%
Latin 246
 
18.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 509
47.7%
- 246
23.1%
3 100
 
9.4%
9 90
 
8.4%
1 19
 
1.8%
2 19
 
1.8%
4 18
 
1.7%
5 18
 
1.7%
6 18
 
1.7%
7 18
 
1.7%
Latin
ValueCountFrequency (%)
R 82
33.3%
E 82
33.3%
Q 82
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 509
38.8%
- 246
18.8%
3 100
 
7.6%
9 90
 
6.9%
R 82
 
6.2%
E 82
 
6.2%
Q 82
 
6.2%
1 19
 
1.4%
2 19
 
1.4%
4 18
 
1.4%
Other values (4) 65
 
5.0%

제목
Text

Distinct81
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-13T05:55:03.960904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length16.158537
Min length9

Characters and Unicode

Total characters1325
Distinct characters248
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)97.6%

Sample

1st row에너지 e-뉴딜 프로젝트
2nd row노인일자리 및 사회활동 지원사업
3rd row스마트 + 유망기업 일자리
4th row신재생에너지 도제 & 취업패키지 사업
5th row데이터 사이언스(D.S)
ValueCountFrequency (%)
청년 18
 
6.1%
지원 14
 
4.8%
전남 13
 
4.4%
지원사업 12
 
4.1%
운영 8
 
2.7%
일자리 5
 
1.7%
사업 5
 
1.7%
육성 4
 
1.4%
모집 4
 
1.4%
프로젝트 4
 
1.4%
Other values (175) 207
70.4%
2023-12-13T05:55:04.386453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
16.0%
업 75
 
5.7%
지 55
 
4.2%
년 44
 
3.3%
원 41
 
3.1%
청 38
 
2.9%
사 33
 
2.5%
2 33
 
2.5%
인 21
 
1.6%
자 20
 
1.5%
Other values (238) 753
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
74.1%
Space Separator 212
 
16.0%
Decimal Number 54
 
4.1%
Uppercase Letter 37
 
2.8%
Lowercase Letter 11
 
0.8%
Other Punctuation 10
 
0.8%
Dash Punctuation 6
 
0.5%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%
Math Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 75
 
7.6%
지 55
 
5.6%
년 44
 
4.5%
원 41
 
4.2%
청 38
 
3.9%
사 33
 
3.4%
인 21
 
2.1%
자 20
 
2.0%
기 20
 
2.0%
전 18
 
1.8%
Other values (198) 617
62.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
13.5%
A 4
10.8%
P 3
8.1%
T 3
8.1%
D 3
8.1%
C 3
8.1%
I 3
8.1%
B 2
 
5.4%
O 2
 
5.4%
N 2
 
5.4%
Other values (7) 7
18.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
o 2
18.2%
n 2
18.2%
a 2
18.2%
t 1
9.1%
g 1
9.1%
i 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 33
61.1%
0 15
27.8%
4 2
 
3.7%
3 2
 
3.7%
1 1
 
1.9%
6 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 4
40.0%
. 3
30.0%
@ 1
 
10.0%
& 1
 
10.0%
/ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 982
74.1%
Common 295
 
22.3%
Latin 48
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 75
 
7.6%
지 55
 
5.6%
년 44
 
4.5%
원 41
 
4.2%
청 38
 
3.9%
사 33
 
3.4%
인 21
 
2.1%
자 20
 
2.0%
기 20
 
2.0%
전 18
 
1.8%
Other values (198) 617
62.8%
Latin
ValueCountFrequency (%)
S 5
 
10.4%
A 4
 
8.3%
P 3
 
6.2%
T 3
 
6.2%
D 3
 
6.2%
C 3
 
6.2%
I 3
 
6.2%
e 2
 
4.2%
o 2
 
4.2%
n 2
 
4.2%
Other values (14) 18
37.5%
Common
ValueCountFrequency (%)
212
71.9%
2 33
 
11.2%
0 15
 
5.1%
- 6
 
2.0%
) 5
 
1.7%
( 5
 
1.7%
, 4
 
1.4%
+ 3
 
1.0%
. 3
 
1.0%
4 2
 
0.7%
Other values (6) 7
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 982
74.1%
ASCII 343
 
25.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
61.8%
2 33
 
9.6%
0 15
 
4.4%
- 6
 
1.7%
S 5
 
1.5%
) 5
 
1.5%
( 5
 
1.5%
, 4
 
1.2%
A 4
 
1.2%
+ 3
 
0.9%
Other values (30) 51
 
14.9%
Hangul
ValueCountFrequency (%)
업 75
 
7.6%
지 55
 
5.6%
년 44
 
4.5%
원 41
 
4.2%
청 38
 
3.9%
사 33
 
3.4%
인 21
 
2.1%
자 20
 
2.0%
기 20
 
2.0%
전 18
 
1.8%
Other values (198) 617
62.8%

지원분야
Categorical

Distinct22
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
취업지원
45 
창업지원
13 
기업지원
 
3
취업지원 및 교육훈련
 
2
육성 및 양성지원
 
2
Other values (17)
17 

Length

Max length20
Median length4
Mean length5.2439024
Min length4

Unique

Unique17 ?
Unique (%)20.7%

Sample

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

Common Values

ValueCountFrequency (%)
취업지원 45
54.9%
창업지원 13
 
15.9%
기업지원 3
 
3.7%
취업지원 및 교육훈련 2
 
2.4%
육성 및 양성지원 2
 
2.4%
과제활동 지원 1
 
1.2%
취업,고용 지원 1
 
1.2%
취업연계 지원사업 1
 
1.2%
임금지원 1
 
1.2%
구직수당지원 1
 
1.2%
Other values (12) 12
 
14.6%

Length

2023-12-13T05:55:04.556033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취업지원 47
41.6%
창업지원 16
 
14.2%
및 10
 
8.8%
지원 5
 
4.4%
기업지원 4
 
3.5%
육성 4
 
3.5%
육성지원 2
 
1.8%
양성지원 2
 
1.8%
교육훈련 2
 
1.8%
임대 1
 
0.9%
Other values (20) 20
17.7%

주관기관
Text

Distinct45
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-13T05:55:04.797185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length17
Mean length11.536585
Min length3

Characters and Unicode

Total characters946
Distinct characters130
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)31.7%

Sample

1st row녹색에너지 연구원 일자리지원센터
2nd row순천시 노인복지관
3rd row전남테크노파크 기업지원단 일자리센터
4th row녹색에너지 연구원 일자리지원센터
5th row전남정보문화산업진흥원 일자리사업팀
ValueCountFrequency (%)
농촌지원과 6
 
4.5%
순천시청 6
 
4.5%
청년일자리팀 6
 
4.5%
전남테크노파크 6
 
4.5%
청년창농기술팀 6
 
4.5%
일자리경제과 5
 
3.8%
순천대학교 5
 
3.8%
전라남도중소기업일자리경제진흥원 4
 
3.0%
전남정보문화산업진흥원 4
 
3.0%
일미래센터 3
 
2.3%
Other values (54) 81
61.4%
2023-12-13T05:55:05.182760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
5.3%
원 40
 
4.2%
업 36
 
3.8%
자 36
 
3.8%
전 35
 
3.7%
남 35
 
3.7%
일 35
 
3.7%
리 32
 
3.4%
팀 25
 
2.6%
지 23
 
2.4%
Other values (120) 599
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 873
92.3%
Space Separator 50
 
5.3%
Lowercase Letter 16
 
1.7%
Uppercase Letter 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 40
 
4.6%
업 36
 
4.1%
자 36
 
4.1%
전 35
 
4.0%
남 35
 
4.0%
일 35
 
4.0%
리 32
 
3.7%
팀 25
 
2.9%
지 23
 
2.6%
과 23
 
2.6%
Other values (103) 553
63.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
18.8%
t 2
12.5%
o 2
12.5%
n 2
12.5%
i 2
12.5%
y 1
 
6.2%
c 1
 
6.2%
r 1
 
6.2%
g 1
 
6.2%
f 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
Y 1
14.3%
W 1
14.3%
C 1
14.3%
A 1
14.3%
E 1
14.3%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 873
92.3%
Common 50
 
5.3%
Latin 23
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 40
 
4.6%
업 36
 
4.1%
자 36
 
4.1%
전 35
 
4.0%
남 35
 
4.0%
일 35
 
4.0%
리 32
 
3.7%
팀 25
 
2.9%
지 23
 
2.6%
과 23
 
2.6%
Other values (103) 553
63.3%
Latin
ValueCountFrequency (%)
e 3
13.0%
t 2
 
8.7%
o 2
 
8.7%
S 2
 
8.7%
n 2
 
8.7%
i 2
 
8.7%
y 1
 
4.3%
c 1
 
4.3%
r 1
 
4.3%
Y 1
 
4.3%
Other values (6) 6
26.1%
Common
ValueCountFrequency (%)
50
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 873
92.3%
ASCII 73
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
68.5%
e 3
 
4.1%
t 2
 
2.7%
o 2
 
2.7%
S 2
 
2.7%
n 2
 
2.7%
i 2
 
2.7%
y 1
 
1.4%
c 1
 
1.4%
r 1
 
1.4%
Other values (7) 7
 
9.6%
Hangul
ValueCountFrequency (%)
원 40
 
4.6%
업 36
 
4.1%
자 36
 
4.1%
전 35
 
4.0%
남 35
 
4.0%
일 35
 
4.0%
리 32
 
3.7%
팀 25
 
2.9%
지 23
 
2.6%
과 23
 
2.6%
Other values (103) 553
63.3%

대상
Text

MISSING 

Distinct75
Distinct (%)94.9%
Missing3
Missing (%)3.7%
Memory size788.0 B
2023-12-13T05:55:05.539610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length34
Mean length24.531646
Min length6

Characters and Unicode

Total characters1938
Distinct characters180
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)91.1%

Sample

1st row미취업 청년(만 18~39세 미만), 전국 청년들 대상(주거지 전남이전)
2nd row순천시에 주소를 두고 거주하는 만 65세이상 기초연금수급권자
3rd row전남 거주 청년 만 18~39세 미취업 청년 100명
4th row만 18~39세 이하의 미취업 청년
5th row전남(목포,여수,순천,나주,광양,무안)에 거주하는 만 39세 이하의 미취업 청년
ValueCountFrequency (%)
청년 35
 
6.8%
30
 
5.9%
39세 29
 
5.7%
만 29
 
5.7%
18 24
 
4.7%
이하 19
 
3.7%
도내 17
 
3.3%
미취업 17
 
3.3%
이상 9
 
1.8%
거주하는 8
 
1.6%
Other values (187) 294
57.5%
2023-12-13T05:55:06.051584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
435
22.4%
업 65
 
3.4%
년 61
 
3.1%
세 55
 
2.8%
하 50
 
2.6%
이 49
 
2.5%
청 48
 
2.5%
3 46
 
2.4%
만 43
 
2.2%
9 42
 
2.2%
Other values (170) 1044
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1181
60.9%
Space Separator 435
 
22.4%
Decimal Number 214
 
11.0%
Math Symbol 38
 
2.0%
Other Punctuation 38
 
2.0%
Close Punctuation 15
 
0.8%
Open Punctuation 15
 
0.8%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 65
 
5.5%
년 61
 
5.2%
세 55
 
4.7%
하 50
 
4.2%
이 49
 
4.1%
청 48
 
4.1%
만 43
 
3.6%
자 33
 
2.8%
도 31
 
2.6%
주 29
 
2.5%
Other values (149) 717
60.7%
Decimal Number
ValueCountFrequency (%)
3 46
21.5%
9 42
19.6%
1 41
19.2%
8 30
14.0%
0 19
8.9%
5 12
 
5.6%
4 10
 
4.7%
2 9
 
4.2%
6 3
 
1.4%
7 2
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 34
89.5%
= 2
 
5.3%
> 2
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 32
84.2%
/ 4
 
10.5%
% 2
 
5.3%
Space Separator
ValueCountFrequency (%)
435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1181
60.9%
Common 756
39.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 65
 
5.5%
년 61
 
5.2%
세 55
 
4.7%
하 50
 
4.2%
이 49
 
4.1%
청 48
 
4.1%
만 43
 
3.6%
자 33
 
2.8%
도 31
 
2.6%
주 29
 
2.5%
Other values (149) 717
60.7%
Common
ValueCountFrequency (%)
435
57.5%
3 46
 
6.1%
9 42
 
5.6%
1 41
 
5.4%
~ 34
 
4.5%
, 32
 
4.2%
8 30
 
4.0%
0 19
 
2.5%
) 15
 
2.0%
( 15
 
2.0%
Other values (10) 47
 
6.2%
Latin
ValueCountFrequency (%)
H 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1181
60.9%
ASCII 757
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
435
57.5%
3 46
 
6.1%
9 42
 
5.5%
1 41
 
5.4%
~ 34
 
4.5%
, 32
 
4.2%
8 30
 
4.0%
0 19
 
2.5%
) 15
 
2.0%
( 15
 
2.0%
Other values (11) 48
 
6.3%
Hangul
ValueCountFrequency (%)
업 65
 
5.5%
년 61
 
5.2%
세 55
 
4.7%
하 50
 
4.2%
이 49
 
4.1%
청 48
 
4.1%
만 43
 
3.6%
자 33
 
2.8%
도 31
 
2.6%
주 29
 
2.5%
Other values (149) 717
60.7%

접수일자
Text

MISSING 

Distinct32
Distinct (%)82.1%
Missing43
Missing (%)52.4%
Memory size788.0 B
2023-12-13T05:55:06.290508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9487179
Min length8

Characters and Unicode

Total characters388
Distinct characters17
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

Unique29 ?
Unique (%)74.4%

Sample

1st row연말 또는 연초
2nd row2021-05-14
3rd row2021-04-21
4th row2022-04-01
5th row2022-03-18
ValueCountFrequency (%)
2022-08-01 5
 
12.2%
2022-03-21 3
 
7.3%
2022-08-04 2
 
4.9%
2022-06-01 1
 
2.4%
2022-07-01 1
 
2.4%
2022-01-25 1
 
2.4%
2022-01-01 1
 
2.4%
2022-04-18 1
 
2.4%
2022-09-20 1
 
2.4%
2020-01-01 1
 
2.4%
Other values (24) 24
58.5%
2023-12-13T05:55:06.674329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 121
31.2%
0 102
26.3%
- 76
19.6%
1 35
 
9.0%
8 13
 
3.4%
3 8
 
2.1%
4 8
 
2.1%
7 6
 
1.5%
6 4
 
1.0%
5 4
 
1.0%
Other values (7) 11
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 304
78.4%
Dash Punctuation 76
 
19.6%
Other Letter 6
 
1.5%
Space Separator 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 121
39.8%
0 102
33.6%
1 35
 
11.5%
8 13
 
4.3%
3 8
 
2.6%
4 8
 
2.6%
7 6
 
2.0%
6 4
 
1.3%
5 4
 
1.3%
9 3
 
1.0%
Other Letter
ValueCountFrequency (%)
연 2
33.3%
말 1
16.7%
또 1
16.7%
는 1
16.7%
초 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 382
98.5%
Hangul 6
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 121
31.7%
0 102
26.7%
- 76
19.9%
1 35
 
9.2%
8 13
 
3.4%
3 8
 
2.1%
4 8
 
2.1%
7 6
 
1.6%
6 4
 
1.0%
5 4
 
1.0%
Other values (2) 5
 
1.3%
Hangul
ValueCountFrequency (%)
연 2
33.3%
말 1
16.7%
또 1
16.7%
는 1
16.7%
초 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 382
98.5%
Hangul 6
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 121
31.7%
0 102
26.7%
- 76
19.9%
1 35
 
9.2%
8 13
 
3.4%
3 8
 
2.1%
4 8
 
2.1%
7 6
 
1.6%
6 4
 
1.0%
5 4
 
1.0%
Other values (2) 5
 
1.3%
Hangul
ValueCountFrequency (%)
연 2
33.3%
말 1
16.7%
또 1
16.7%
는 1
16.7%
초 1
16.7%

접수종료일자
Text

MISSING 

Distinct27
Distinct (%)73.0%
Missing45
Missing (%)54.9%
Memory size788.0 B
2023-12-13T05:55:06.907241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length10.108108
Min length8

Characters and Unicode

Total characters374
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)59.5%

Sample

1st row2021-05-23
2nd row2021-05-07
3rd row2022-05-31
4th row2022-04-15
5th row2022-04-03
ValueCountFrequency (%)
2022-10-31 7
 
16.3%
예산 3
 
7.0%
2022-06-07 2
 
4.7%
2022-08-19 2
 
4.7%
소진시까지 2
 
4.7%
2022-04-22 2
 
4.7%
2022-09-23 1
 
2.3%
2022-03-31 1
 
2.3%
2022-12-31 1
 
2.3%
2022-03-03 1
 
2.3%
Other values (21) 21
48.8%
2023-12-13T05:55:07.259811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 108
28.9%
0 78
20.9%
- 68
18.2%
1 32
 
8.6%
3 24
 
6.4%
7 8
 
2.1%
6
 
1.6%
6 5
 
1.3%
9 5
 
1.3%
4 5
 
1.3%
Other values (15) 35
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 272
72.7%
Dash Punctuation 68
 
18.2%
Other Letter 26
 
7.0%
Space Separator 6
 
1.6%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3
11.5%
지 3
11.5%
까 3
11.5%
진 3
11.5%
소 3
11.5%
산 3
11.5%
예 3
11.5%
순 2
7.7%
착 1
 
3.8%
마 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
2 108
39.7%
0 78
28.7%
1 32
 
11.8%
3 24
 
8.8%
7 8
 
2.9%
6 5
 
1.8%
9 5
 
1.8%
4 5
 
1.8%
5 4
 
1.5%
8 3
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
93.0%
Hangul 26
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 108
31.0%
0 78
22.4%
- 68
19.5%
1 32
 
9.2%
3 24
 
6.9%
7 8
 
2.3%
6
 
1.7%
6 5
 
1.4%
9 5
 
1.4%
4 5
 
1.4%
Other values (4) 9
 
2.6%
Hangul
ValueCountFrequency (%)
시 3
11.5%
지 3
11.5%
까 3
11.5%
진 3
11.5%
소 3
11.5%
산 3
11.5%
예 3
11.5%
순 2
7.7%
착 1
 
3.8%
마 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
93.0%
Hangul 26
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 108
31.0%
0 78
22.4%
- 68
19.5%
1 32
 
9.2%
3 24
 
6.9%
7 8
 
2.3%
6
 
1.7%
6 5
 
1.4%
9 5
 
1.4%
4 5
 
1.4%
Other values (4) 9
 
2.6%
Hangul
ValueCountFrequency (%)
시 3
11.5%
지 3
11.5%
까 3
11.5%
진 3
11.5%
소 3
11.5%
산 3
11.5%
예 3
11.5%
순 2
7.7%
착 1
 
3.8%
마 1
 
3.8%

등록일자
Date

MISSING 

Distinct31
Distinct (%)79.5%
Missing43
Missing (%)52.4%
Memory size788.0 B
Minimum2020-01-01 00:00:00
Maximum2022-10-06 00:00:00
2023-12-13T05:55:07.401863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:55:07.536862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

Correlations

2023-12-13T05:55:07.630695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번제목지원분야주관기관대상접수일자접수종료일자등록일자
순번1.0001.0001.0001.0001.0001.0001.0001.000
제목1.0001.0001.0000.9860.9950.9690.9471.000
지원분야1.0001.0001.0000.9020.9990.0000.0000.000
주관기관1.0000.9860.9021.0000.9930.9880.9590.987
대상1.0000.9950.9990.9931.0001.0001.0001.000
접수일자1.0000.9690.0000.9881.0001.0000.9930.990
접수종료일자1.0000.9470.0000.9591.0000.9931.0000.990
등록일자1.0001.0000.0000.9871.0000.9900.9901.000

Missing values

2023-12-13T05:55:02.799344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:55:02.935933image/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.
2023-12-13T05:55:03.050907image/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

순번제목지원분야주관기관대상접수일자접수종료일자등록일자
0REQ-003-09-00001에너지 e-뉴딜 프로젝트취업지원녹색에너지 연구원 일자리지원센터미취업 청년(만 18~39세 미만), 전국 청년들 대상(주거지 전남이전)<NA><NA><NA>
1REQ-003-09-00002노인일자리 및 사회활동 지원사업취업지원순천시 노인복지관순천시에 주소를 두고 거주하는 만 65세이상 기초연금수급권자연말 또는 연초<NA><NA>
2REQ-003-09-00003스마트 + 유망기업 일자리취업지원전남테크노파크 기업지원단 일자리센터전남 거주 청년 만 18~39세 미취업 청년 100명<NA><NA><NA>
3REQ-003-09-00004신재생에너지 도제 & 취업패키지 사업취업지원녹색에너지 연구원 일자리지원센터만 18~39세 이하의 미취업 청년<NA><NA><NA>
4REQ-003-09-00005데이터 사이언스(D.S)취업지원전남정보문화산업진흥원 일자리사업팀전남(목포,여수,순천,나주,광양,무안)에 거주하는 만 39세 이하의 미취업 청년<NA><NA><NA>
5REQ-003-09-00006전남 청년 툰(TOON)취업지원전남정보문화산업진흥원 일자리사업팀순천시에 거주하는 만 39세 이하의 미취업 청년<NA><NA><NA>
6REQ-003-09-000072021년 신중년 경력형 일자리 지원사업취업지원순천시청만50~70세 교육분야 경력자2021-05-142021-05-232021-05-14
7REQ-003-09-00008탄소중립 스마트그린 프로젝트취업지원전남테크노파크 기업지원단 일자리센터전남 거주 청년 만 18~39세 미취업 청년<NA><NA><NA>
8REQ-003-09-00009전남 청년 창업지원창업지원전남창조경제혁신센터 고용지원본부만 18 ~ 39세 이하의 미취업 청년<NA><NA><NA>
9REQ-003-09-00010청년창업 후속지원창업지원전라남도환경산업진흥원전남 내 만 39세 이하 창업 7년 미만 청년 창업자<NA><NA><NA>
순번제목지원분야주관기관대상접수일자접수종료일자등록일자
72REQ-003-09-000732022학년도 직무체험형 인턴 참여자 모집취업지원순천대학교 대학일자리센터순천대학교 3,4학년 및 졸업생2022-09-192022-10-032022-09-20
73REQ-003-09-000742022년 전남 IP창업Zone창업지원전남테크노파크예비창업자 및 2022년 기창업자2022-01-212022-02-162022-01-21
74REQ-003-09-00075전남 중소기업 면접비 지원면접비 지원전라남도 일자리 종합센터전남 소재 중소기업 면접자2022-03-21예산 소진시까지2022-08-26
75REQ-003-09-00076희망기업 및 직무탐방(2차) 참여팀 모집취업지원순천대학교 대학일자리센터순천대학교 재학생 및 졸업생2022-07-122022-07-292022-07-12
76REQ-003-09-00077BigData 엔지니어, B-Con.S 코스 참여자 모집취업지원순천대학교 협력기관 Soft Engineer Society내일배움카드 발급 가능자 / 3,4학년 / 졸업(예정)자2022-07-28<NA>2022-07-08
77REQ-003-09-00078CAP@청년층직업지도프로그램취업지원순천대학교 대학일자리센터<NA>2022-06-232022-07-062022-07-08
78REQ-003-09-00079대학졸업생 행정인턴 운영취업지원 및 교육훈련순천시청 투자일자리과만 18 ~ 29세 / 순천시에 주소를 두고 있는 대학졸업자<NA><NA><NA>
79REQ-003-09-00080대학졸업생 직장체험 운영취업지원 및 교육훈련순천시청 투자일자리과순천시 거주자이면서 대학 재학생<NA><NA><NA>
80REQ-003-09-00081청춘창고, 청춘웃장 청년 창업지원창업지원, 경영지원순천시청 투자일자리과만 19 ~ 39세 이하 대한민국에 거주하는 청년<NA><NA><NA>
81REQ-003-09-00082순천시 지역기반 기술형 창업지원사업창업지원순천시만 39세 이하 순천시에 주소지를 둔 미취업 청년2020-08-032020-08-122020-08-03