Overview

Dataset statistics

Number of variables3
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory708.0 B
Average record size in memory29.5 B

Variable types

Text3

Dataset

Description대구광역시 수성구 행정기관 현황에 대한 데이터로 행정복지센터 위치(주소), 연락처 등에 대한 정보를 제공합니다.
Author대구광역시 수성구
URLhttps://www.data.go.kr/data/15046135/fileData.do

Alerts

구분 has unique valuesUnique
주소 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:33:07.291951
Analysis finished2023-12-12 04:33:07.556704
Duration0.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T13:33:07.691256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.7916667
Min length2

Characters and Unicode

Total characters91
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row수성구청
2nd row범어1동
3rd row범어2동
4th row범어3동
5th row범어4동
ValueCountFrequency (%)
수성구청 1
 
4.2%
범어1동 1
 
4.2%
고산2동 1
 
4.2%
고산1동 1
 
4.2%
범물2동 1
 
4.2%
범물1동 1
 
4.2%
지산2동 1
 
4.2%
지산1동 1
 
4.2%
두산동 1
 
4.2%
파동 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T13:33:08.103935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 20
22.0%
1 7
 
7.7%
2 7
 
7.7%
산 6
 
6.6%
범 6
 
6.6%
수 4
 
4.4%
어 4
 
4.4%
3 4
 
4.4%
성 4
 
4.4%
만 3
 
3.3%
Other values (15) 26
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
76.9%
Decimal Number 20
 
22.0%
Other Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 20
28.6%
산 6
 
8.6%
범 6
 
8.6%
수 4
 
5.7%
어 4
 
5.7%
성 4
 
5.7%
만 3
 
4.3%
가 3
 
4.3%
촌 3
 
4.3%
고 3
 
4.3%
Other values (10) 14
20.0%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
2 7
35.0%
3 4
20.0%
4 2
 
10.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
76.9%
Common 21
 
23.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 20
28.6%
산 6
 
8.6%
범 6
 
8.6%
수 4
 
5.7%
어 4
 
5.7%
성 4
 
5.7%
만 3
 
4.3%
가 3
 
4.3%
촌 3
 
4.3%
고 3
 
4.3%
Other values (10) 14
20.0%
Common
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 4
19.0%
4 2
 
9.5%
· 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
76.9%
ASCII 20
 
22.0%
None 1
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 20
28.6%
산 6
 
8.6%
범 6
 
8.6%
수 4
 
5.7%
어 4
 
5.7%
성 4
 
5.7%
만 3
 
4.3%
가 3
 
4.3%
촌 3
 
4.3%
고 3
 
4.3%
Other values (10) 14
20.0%
ASCII
ValueCountFrequency (%)
1 7
35.0%
2 7
35.0%
3 4
20.0%
4 2
 
10.0%
None
ValueCountFrequency (%)
· 1
100.0%

주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T13:33:08.382145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26.5
Mean length24.5
Min length21

Characters and Unicode

Total characters588
Distinct characters61
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

Unique24 ?
Unique (%)100.0%

Sample

1st row대구광역시 수성구 달구벌대로 2450(범어동)
2nd row 대구광역시 수성구 범어천로 97(범어동)
3rd row 대구광역시 수성구 달구벌대로489안길 47(범어동)
4th row대구광역시 수성구 상록로 42(범어동)
5th row 대구광역시 수성구 달구벌대로504길 26(범어동)
ValueCountFrequency (%)
대구광역시 24
25.0%
수성구 24
25.0%
달구벌대로 3
 
3.1%
범안로 2
 
2.1%
상화로 1
 
1.0%
청솔로2길 1
 
1.0%
64(황금동 1
 
1.0%
수성로50길 1
 
1.0%
38(중동 1
 
1.0%
들안로9길 1
 
1.0%
Other values (37) 37
38.5%
2023-12-12T13:33:08.887753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
16.0%
구 53
 
9.0%
대 29
 
4.9%
수 28
 
4.8%
성 28
 
4.8%
시 25
 
4.3%
동 25
 
4.3%
( 24
 
4.1%
광 24
 
4.1%
역 24
 
4.1%
Other values (51) 234
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361
61.4%
Space Separator 94
 
16.0%
Decimal Number 83
 
14.1%
Open Punctuation 24
 
4.1%
Close Punctuation 24
 
4.1%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 53
14.7%
대 29
 
8.0%
수 28
 
7.8%
성 28
 
7.8%
시 25
 
6.9%
동 25
 
6.9%
광 24
 
6.6%
역 24
 
6.6%
로 24
 
6.6%
범 11
 
3.0%
Other values (37) 90
24.9%
Decimal Number
ValueCountFrequency (%)
2 12
14.5%
4 11
13.3%
1 10
12.0%
6 9
10.8%
3 9
10.8%
5 9
10.8%
0 8
9.6%
7 7
8.4%
9 6
7.2%
8 2
 
2.4%
Space Separator
ValueCountFrequency (%)
94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 361
61.4%
Common 227
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 53
14.7%
대 29
 
8.0%
수 28
 
7.8%
성 28
 
7.8%
시 25
 
6.9%
동 25
 
6.9%
광 24
 
6.6%
역 24
 
6.6%
로 24
 
6.6%
범 11
 
3.0%
Other values (37) 90
24.9%
Common
ValueCountFrequency (%)
94
41.4%
( 24
 
10.6%
) 24
 
10.6%
2 12
 
5.3%
4 11
 
4.8%
1 10
 
4.4%
6 9
 
4.0%
3 9
 
4.0%
5 9
 
4.0%
0 8
 
3.5%
Other values (4) 17
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 361
61.4%
ASCII 227
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
41.4%
( 24
 
10.6%
) 24
 
10.6%
2 12
 
5.3%
4 11
 
4.8%
1 10
 
4.4%
6 9
 
4.0%
3 9
 
4.0%
5 9
 
4.0%
0 8
 
3.5%
Other values (4) 17
 
7.5%
Hangul
ValueCountFrequency (%)
구 53
14.7%
대 29
 
8.0%
수 28
 
7.8%
성 28
 
7.8%
시 25
 
6.9%
동 25
 
6.9%
광 24
 
6.6%
역 24
 
6.6%
로 24
 
6.6%
범 11
 
3.0%
Other values (37) 90
24.9%

연락처
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T13:33:09.193891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row053-666-2000
2nd row053-666-3301
3rd row053-666-3302
4th row053-666-3303
5th row053-666-3304
ValueCountFrequency (%)
053-666-2000 1
 
4.2%
053-666-3301 1
 
4.2%
053-666-3322 1
 
4.2%
053-666-3321 1
 
4.2%
053-666-3320 1
 
4.2%
053-666-3319 1
 
4.2%
053-666-3318 1
 
4.2%
053-666-3317 1
 
4.2%
053-666-3316 1
 
4.2%
053-666-3315 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T13:33:09.651781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 74
25.7%
3 73
25.3%
- 48
16.7%
0 38
13.2%
5 26
 
9.0%
1 13
 
4.5%
2 8
 
2.8%
4 2
 
0.7%
7 2
 
0.7%
8 2
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 74
30.8%
3 73
30.4%
0 38
15.8%
5 26
 
10.8%
1 13
 
5.4%
2 8
 
3.3%
4 2
 
0.8%
7 2
 
0.8%
8 2
 
0.8%
9 2
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 74
25.7%
3 73
25.3%
- 48
16.7%
0 38
13.2%
5 26
 
9.0%
1 13
 
4.5%
2 8
 
2.8%
4 2
 
0.7%
7 2
 
0.7%
8 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 74
25.7%
3 73
25.3%
- 48
16.7%
0 38
13.2%
5 26
 
9.0%
1 13
 
4.5%
2 8
 
2.8%
4 2
 
0.7%
7 2
 
0.7%
8 2
 
0.7%

Correlations

2023-12-12T13:33:09.808130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분주소연락처
구분1.0001.0001.000
주소1.0001.0001.000
연락처1.0001.0001.000

Missing values

2023-12-12T13:33:07.446033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:33:07.519732image/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

구분주소연락처
0수성구청대구광역시 수성구 달구벌대로 2450(범어동)053-666-2000
1범어1동대구광역시 수성구 범어천로 97(범어동)053-666-3301
2범어2동대구광역시 수성구 달구벌대로489안길 47(범어동)053-666-3302
3범어3동대구광역시 수성구 상록로 42(범어동)053-666-3303
4범어4동대구광역시 수성구 달구벌대로504길 26(범어동)053-666-3304
5만촌1동대구광역시 수성구 국채보상로 1001(만촌동)053-666-3305
6만촌2동대구광역시 수성구 무열로 12(만촌동)053-666-3306
7만촌3동대구광역시 수성구 교학로2길 45(만촌동)053-666-3307
8수성1가대구광역시 수성구 명덕로73길 7(수성동1가)053-666-3308
9수성2·3가대구광역시 수성구 명덕로 443-2(수성동3가)053-666-3309
구분주소연락처
14상동대구광역시 수성구 들안로9길 56(상동)053-666-3314
15파동대구광역시 수성구 파동로 136(파동)053-666-3315
16두산동대구광역시 수성구 상화로 95(두산동)053-666-3316
17지산1동대구광역시 수성구 지범로21길 16(지산동)053-666-3317
18지산2동대구광역시 수성구 용학로33길 9(지산동)053-666-3318
19범물1동대구광역시 수성구 범안로 76(범물동)053-666-3319
20범물2동대구광역시 수성구 범안로 52(범물동)053-666-3320
21고산1동대구광역시 수성구 달구벌대로 3260-2(신매동)053-666-3321
22고산2동대구광역시 수성구 달구벌대로 3091(시지동)053-666-3322
23고산3동대구광역시 수성구 고산로 152(매호동)053-666-3323