Overview

Dataset statistics

Number of variables4
Number of observations51
Missing cells36
Missing cells (%)17.6%
Duplicate rows1
Duplicate rows (%)2.0%
Total size in memory1.7 KiB
Average record size in memory34.6 B

Variable types

Text3
DateTime1

Dataset

Description전라남도 시군에 위치한 청소년단체 현황 (단체명, 주소,설립일,전화번호 등)에 관한 데이터를 조회하실 수 있습니다.
Author전라남도
URLhttps://www.data.go.kr/data/3036123/fileData.do

Alerts

Dataset has 1 (2.0%) duplicate rowsDuplicates
명칭 has 8 (15.7%) missing valuesMissing
주소 has 8 (15.7%) missing valuesMissing
설립일 has 8 (15.7%) missing valuesMissing
전화번호 has 12 (23.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:13:54.733199
Analysis finished2023-12-12 09:13:55.891392
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing8
Missing (%)15.7%
Memory size540.0 B
2023-12-12T18:13:56.067089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length8.7209302
Min length3

Characters and Unicode

Total characters375
Distinct characters128
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row(사)순천기독교청년회
2nd row순천여자기독교청년회
3rd row목포여자기독교청년회
4th row광양YWCA
5th row광양학교폭력신고센터 광양교통안전자원봉사대
ValueCountFrequency (%)
전남연맹 2
 
4.0%
순천여자기독교청년회 1
 
2.0%
꿈두레 1
 
2.0%
공동체 1
 
2.0%
푸른샘 1
 
2.0%
한들청소년센터 1
 
2.0%
푸른청소년육성개발원 1
 
2.0%
청소년과미래자립지원센터 1
 
2.0%
전라남도청소년미래재단 1
 
2.0%
사)꿈틀 1
 
2.0%
Other values (39) 39
78.0%
2023-12-12T18:13:56.543576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 20
 
5.3%
년 17
 
4.5%
소 15
 
4.0%
회 13
 
3.5%
한 9
 
2.4%
교 9
 
2.4%
사 9
 
2.4%
남 8
 
2.1%
전 8
 
2.1%
국 7
 
1.9%
Other values (118) 260
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
92.8%
Uppercase Letter 12
 
3.2%
Space Separator 7
 
1.9%
Close Punctuation 3
 
0.8%
Decimal Number 3
 
0.8%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 20
 
5.7%
년 17
 
4.9%
소 15
 
4.3%
회 13
 
3.7%
한 9
 
2.6%
교 9
 
2.6%
사 9
 
2.6%
남 8
 
2.3%
전 8
 
2.3%
국 7
 
2.0%
Other values (108) 233
67.0%
Uppercase Letter
ValueCountFrequency (%)
Y 3
25.0%
C 3
25.0%
A 3
25.0%
W 2
16.7%
M 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
92.8%
Common 15
 
4.0%
Latin 12
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 20
 
5.7%
년 17
 
4.9%
소 15
 
4.3%
회 13
 
3.7%
한 9
 
2.6%
교 9
 
2.6%
사 9
 
2.6%
남 8
 
2.3%
전 8
 
2.3%
국 7
 
2.0%
Other values (108) 233
67.0%
Common
ValueCountFrequency (%)
7
46.7%
) 3
20.0%
( 2
 
13.3%
1 2
 
13.3%
2 1
 
6.7%
Latin
ValueCountFrequency (%)
Y 3
25.0%
C 3
25.0%
A 3
25.0%
W 2
16.7%
M 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
92.8%
ASCII 27
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 20
 
5.7%
년 17
 
4.9%
소 15
 
4.3%
회 13
 
3.7%
한 9
 
2.6%
교 9
 
2.6%
사 9
 
2.6%
남 8
 
2.3%
전 8
 
2.3%
국 7
 
2.0%
Other values (108) 233
67.0%
ASCII
ValueCountFrequency (%)
7
25.9%
) 3
11.1%
Y 3
11.1%
C 3
11.1%
A 3
11.1%
W 2
 
7.4%
( 2
 
7.4%
1 2
 
7.4%
2 1
 
3.7%
M 1
 
3.7%

주소
Text

MISSING 

Distinct42
Distinct (%)97.7%
Missing8
Missing (%)15.7%
Memory size540.0 B
2023-12-12T18:13:56.873725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.511628
Min length14

Characters and Unicode

Total characters839
Distinct characters107
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

Unique41 ?
Unique (%)95.3%

Sample

1st row전라남도 순천시 중앙3길 6-6
2nd row전라남도 순천시 서문로 6
3rd row전라남도 목포시 영산로 139
4th row전라남도 광양시 광양읍 인덕로 977
5th row전라남도 광양시 옥곡면 강변로 443
ValueCountFrequency (%)
전라남도 43
 
21.4%
광양시 5
 
2.5%
무안군 5
 
2.5%
나주시 4
 
2.0%
목포시 4
 
2.0%
여수시 4
 
2.0%
순천시 4
 
2.0%
중앙로 3
 
1.5%
장흥군 3
 
1.5%
완도읍 3
 
1.5%
Other values (108) 123
61.2%
2023-12-12T18:13:57.355239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
18.8%
남 50
 
6.0%
도 50
 
6.0%
라 44
 
5.2%
전 43
 
5.1%
1 31
 
3.7%
로 24
 
2.9%
군 23
 
2.7%
시 22
 
2.6%
2 19
 
2.3%
Other values (97) 375
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 539
64.2%
Space Separator 158
 
18.8%
Decimal Number 131
 
15.6%
Dash Punctuation 11
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 50
 
9.3%
도 50
 
9.3%
라 44
 
8.2%
전 43
 
8.0%
로 24
 
4.5%
군 23
 
4.3%
시 22
 
4.1%
읍 19
 
3.5%
길 17
 
3.2%
양 12
 
2.2%
Other values (85) 235
43.6%
Decimal Number
ValueCountFrequency (%)
1 31
23.7%
2 19
14.5%
4 14
10.7%
3 12
 
9.2%
5 12
 
9.2%
7 11
 
8.4%
9 9
 
6.9%
0 8
 
6.1%
6 8
 
6.1%
8 7
 
5.3%
Space Separator
ValueCountFrequency (%)
158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 539
64.2%
Common 300
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 50
 
9.3%
도 50
 
9.3%
라 44
 
8.2%
전 43
 
8.0%
로 24
 
4.5%
군 23
 
4.3%
시 22
 
4.1%
읍 19
 
3.5%
길 17
 
3.2%
양 12
 
2.2%
Other values (85) 235
43.6%
Common
ValueCountFrequency (%)
158
52.7%
1 31
 
10.3%
2 19
 
6.3%
4 14
 
4.7%
3 12
 
4.0%
5 12
 
4.0%
7 11
 
3.7%
- 11
 
3.7%
9 9
 
3.0%
0 8
 
2.7%
Other values (2) 15
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 539
64.2%
ASCII 300
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
52.7%
1 31
 
10.3%
2 19
 
6.3%
4 14
 
4.7%
3 12
 
4.0%
5 12
 
4.0%
7 11
 
3.7%
- 11
 
3.7%
9 9
 
3.0%
0 8
 
2.7%
Other values (2) 15
 
5.0%
Hangul
ValueCountFrequency (%)
남 50
 
9.3%
도 50
 
9.3%
라 44
 
8.2%
전 43
 
8.0%
로 24
 
4.5%
군 23
 
4.3%
시 22
 
4.1%
읍 19
 
3.5%
길 17
 
3.2%
양 12
 
2.2%
Other values (85) 235
43.6%

설립일
Date

MISSING 

Distinct35
Distinct (%)81.4%
Missing8
Missing (%)15.7%
Memory size540.0 B
Minimum2000-05-08 00:00:00
Maximum2020-03-24 00:00:00
2023-12-12T18:13:57.554879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:13:57.700299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

전화번호
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing12
Missing (%)23.5%
Memory size540.0 B
2023-12-12T18:13:57.967544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters468
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row061-745-0601
2nd row061-774-7991
3rd row061-242-1611
4th row061-762-0012
5th row061-792-2828
ValueCountFrequency (%)
061-745-0601 1
 
2.6%
061-654-0544 1
 
2.6%
061-755-1190 1
 
2.6%
061-285-1388 1
 
2.6%
061-862-9909 1
 
2.6%
061-363-9585 1
 
2.6%
061-287-1388 1
 
2.6%
061-280-9010 1
 
2.6%
061-555-4100 1
 
2.6%
061-274-1605 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T18:13:58.500734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 78
16.7%
1 70
15.0%
6 63
13.5%
0 60
12.8%
2 38
8.1%
3 32
6.8%
7 28
 
6.0%
4 28
 
6.0%
5 28
 
6.0%
8 24
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
83.3%
Dash Punctuation 78
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 70
17.9%
6 63
16.2%
0 60
15.4%
2 38
9.7%
3 32
8.2%
7 28
 
7.2%
4 28
 
7.2%
5 28
 
7.2%
8 24
 
6.2%
9 19
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 78
16.7%
1 70
15.0%
6 63
13.5%
0 60
12.8%
2 38
8.1%
3 32
6.8%
7 28
 
6.0%
4 28
 
6.0%
5 28
 
6.0%
8 24
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 78
16.7%
1 70
15.0%
6 63
13.5%
0 60
12.8%
2 38
8.1%
3 32
6.8%
7 28
 
6.0%
4 28
 
6.0%
5 28
 
6.0%
8 24
 
5.1%

Correlations

2023-12-12T18:13:58.649463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭주소설립일전화번호
명칭1.0001.0001.0001.000
주소1.0001.0000.9931.000
설립일1.0000.9931.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-12T18:13:55.578335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:13:55.705861image/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.
2023-12-12T18:13:55.829401image/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

명칭주소설립일전화번호
0(사)순천기독교청년회전라남도 순천시 중앙3길 6-62000-05-08061-745-0601
1순천여자기독교청년회전라남도 순천시 서문로 62000-05-08061-774-7991
2목포여자기독교청년회전라남도 목포시 영산로 1392000-05-08061-242-1611
3광양YWCA전라남도 광양시 광양읍 인덕로 9772000-05-08061-762-0012
4광양학교폭력신고센터 광양교통안전자원봉사대전라남도 광양시 옥곡면 강변로 4432000-05-08061-792-2828
5여수YWCA전라남도 여수시 동문로 1202000-05-08061-654-2161
6한국걸스카우트 전남연맹전라남도 장성군 남면 나노산단5로 132000-05-08061-393-1422
7나주시민 아카데미전라남도 나주시 송월동 11072000-05-08061-333-1717
8한국불우청소년선도회전라남도 나주시 예향로 40732000-10-04061-336-8403
9영암행복한가정상담소전라남도 영암군 삼호읍 세가래1길 172007-02-20061-461-1366
명칭주소설립일전화번호
41사단법인 유스앤피플전라남도 무안군 삼향읍 남악3로82번길 152018-07-23061-274-1605
42꿈두레전라남도 장흥군 안양면 기산길 492020-03-09061-864-3939
43<NA><NA><NA><NA>
44<NA><NA><NA><NA>
45<NA><NA><NA><NA>
46<NA><NA><NA><NA>
47<NA><NA><NA><NA>
48<NA><NA><NA><NA>
49<NA><NA><NA><NA>
50<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

명칭주소설립일전화번호# duplicates
0<NA><NA><NA><NA>8