Overview

Dataset statistics

Number of variables2
Number of observations988
Missing cells0
Missing cells (%)0.0%
Duplicate rows3
Duplicate rows (%)0.3%
Total size in memory15.6 KiB
Average record size in memory16.1 B

Variable types

DateTime1
Text1

Dataset

Description전라남도 여수시 관광홈페이지 문화관광해설사 일반투어 신청에 관한 데이터로 신청등록일자, 신청단체명, 해설사 위도, 해설사 경도 등의 정보를 제공합니다 .
Author전라남도 여수시
URLhttps://www.data.go.kr/data/15040848/fileData.do

Alerts

Dataset has 3 (0.3%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 09:44:37.170559
Analysis finished2023-12-12 09:44:37.598207
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신청일자
Date

Distinct985
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
Minimum2016-01-05 15:35:00
Maximum2023-08-11 13:30:00
2023-12-12T18:44:37.686485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:37.897703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신청단체
Text

Distinct819
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2023-12-12T18:44:38.293926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length32
Mean length10.546559
Min length2

Characters and Unicode

Total characters10420
Distinct characters484
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique706 ?
Unique (%)71.5%

Sample

1st row관봉초등학교
2nd row한국수력원자력, 한수원
3rd row한국교원대학교
4th row한국교원대학교
5th row행복산악회
ValueCountFrequency (%)
여수 19
 
1.1%
3학년 19
 
1.1%
광주 11
 
0.6%
여수미평초등학교 10
 
0.6%
전남대학교 10
 
0.6%
교육훈련단 10
 
0.6%
해병대 10
 
0.6%
여수신월초등학교 9
 
0.5%
9
 
0.5%
사단법인 9
 
0.5%
Other values (1209) 1628
93.3%
2023-12-12T18:44:38.850311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
798
 
7.7%
학 429
 
4.1%
교 413
 
4.0%
회 311
 
3.0%
여 211
 
2.0%
원 198
 
1.9%
등 182
 
1.7%
사 174
 
1.7%
대 170
 
1.6%
수 159
 
1.5%
Other values (474) 7375
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8990
86.3%
Space Separator 798
 
7.7%
Decimal Number 211
 
2.0%
Close Punctuation 115
 
1.1%
Uppercase Letter 114
 
1.1%
Open Punctuation 103
 
1.0%
Other Punctuation 45
 
0.4%
Lowercase Letter 24
 
0.2%
Dash Punctuation 10
 
0.1%
Math Symbol 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 429
 
4.8%
교 413
 
4.6%
회 311
 
3.5%
여 211
 
2.3%
원 198
 
2.2%
등 182
 
2.0%
사 174
 
1.9%
대 170
 
1.9%
수 159
 
1.8%
전 158
 
1.8%
Other values (419) 6585
73.2%
Uppercase Letter
ValueCountFrequency (%)
C 17
14.9%
A 15
13.2%
Y 10
 
8.8%
W 9
 
7.9%
B 8
 
7.0%
P 7
 
6.1%
M 6
 
5.3%
S 6
 
5.3%
K 6
 
5.3%
I 4
 
3.5%
Other values (13) 26
22.8%
Decimal Number
ValueCountFrequency (%)
3 52
24.6%
2 37
17.5%
1 35
16.6%
4 21
10.0%
5 20
 
9.5%
0 16
 
7.6%
6 14
 
6.6%
8 10
 
4.7%
7 4
 
1.9%
9 2
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
a 4
16.7%
o 3
12.5%
w 3
12.5%
y 3
12.5%
l 3
12.5%
c 3
12.5%
b 2
8.3%
h 1
 
4.2%
i 1
 
4.2%
k 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 28
62.2%
. 10
 
22.2%
/ 4
 
8.9%
: 3
 
6.7%
Math Symbol
ValueCountFrequency (%)
< 3
30.0%
~ 3
30.0%
> 3
30.0%
+ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
798
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8990
86.3%
Common 1292
 
12.4%
Latin 138
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 429
 
4.8%
교 413
 
4.6%
회 311
 
3.5%
여 211
 
2.3%
원 198
 
2.2%
등 182
 
2.0%
사 174
 
1.9%
대 170
 
1.9%
수 159
 
1.8%
전 158
 
1.8%
Other values (419) 6585
73.2%
Latin
ValueCountFrequency (%)
C 17
 
12.3%
A 15
 
10.9%
Y 10
 
7.2%
W 9
 
6.5%
B 8
 
5.8%
P 7
 
5.1%
M 6
 
4.3%
S 6
 
4.3%
K 6
 
4.3%
I 4
 
2.9%
Other values (23) 50
36.2%
Common
ValueCountFrequency (%)
798
61.8%
) 115
 
8.9%
( 103
 
8.0%
3 52
 
4.0%
2 37
 
2.9%
1 35
 
2.7%
, 28
 
2.2%
4 21
 
1.6%
5 20
 
1.5%
0 16
 
1.2%
Other values (12) 67
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8989
86.3%
ASCII 1430
 
13.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
798
55.8%
) 115
 
8.0%
( 103
 
7.2%
3 52
 
3.6%
2 37
 
2.6%
1 35
 
2.4%
, 28
 
2.0%
4 21
 
1.5%
5 20
 
1.4%
C 17
 
1.2%
Other values (45) 204
 
14.3%
Hangul
ValueCountFrequency (%)
학 429
 
4.8%
교 413
 
4.6%
회 311
 
3.5%
여 211
 
2.3%
원 198
 
2.2%
등 182
 
2.0%
사 174
 
1.9%
대 170
 
1.9%
수 159
 
1.8%
전 158
 
1.8%
Other values (418) 6584
73.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

Missing values

2023-12-12T18:44:37.473045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:44:37.560978image/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

신청일자신청단체
02016-01-05 15:35관봉초등학교
12016-01-12 16:19한국수력원자력, 한수원
22016-01-18 11:47한국교원대학교
32016-01-18 11:50한국교원대학교
42016-02-12 11:13행복산악회
52016-02-16 16:06지방행정연수원 사무관 연구과정
62016-02-17 19:50YWCA
72016-02-19 11:38대한민국해군 교육사령부 리더십센터
82016-02-19 11:43KPC, 한수원
92016-02-26 09:39한국농어촌공사
신청일자신청단체
9782023-07-12 13:37문화재청 현충사관리소
9792023-07-13 14:42전라남도교육청학생교육문화회관
9802023-07-15 16:5032명
9812023-07-17 09:53광주 글로벌 지역아동센터
9822023-07-17 10:22농식품공무원교육원
9832023-07-17 10:33광주 글로벌 지역아동센터
9842023-07-21 11:10아산시 마을공동육아 별헤는 아이
9852023-07-28 14:30(주)이씨에스텔레콤
9862023-07-28 16:46미래인재교육원
9872023-08-11 13:30다낭회

Duplicate rows

Most frequently occurring

신청일자신청단체# duplicates
02021-12-12 19:32캐리어에어컨2
12023-04-18 16:42서울시인재개발원2
22023-04-20 13:54여수청년회의소 특우회전남지구2