Overview

Dataset statistics

Number of variables5
Number of observations116
Missing cells39
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory41.1 B

Variable types

Text4
Categorical1

Dataset

Description대구광역시 서구_자원봉사 할인가맹점 현황_20240101
Author대구광역시 서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15092904&dataSetDetailId=150929041a32541a4c7dc&provdMethod=FILE

Alerts

담당부서 has constant value ""Constant
전화번호 has 39 (33.6%) missing valuesMissing
업체명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 14:17:00.052331
Analysis finished2024-03-13 14:17:00.543782
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T23:17:00.739960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length6.6465517
Min length2

Characters and Unicode

Total characters771
Distinct characters261
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

Unique116 ?
Unique (%)100.0%

Sample

1st row영훈자동차정비공장
2nd row대구보링
3rd row대구자동차정비
4th row삼성강철가구
5th row큰장길침구류명물거리(무궁화홈패션)
ValueCountFrequency (%)
주식회사 2
 
1.4%
미용실 2
 
1.4%
평리점 2
 
1.4%
리샤헤어 1
 
0.7%
추어나루 1
 
0.7%
돈장군숯불갈비 1
 
0.7%
안계식당 1
 
0.7%
왕돈이숯불갈비 1
 
0.7%
김밥사랑 1
 
0.7%
영훈자동차정비공장 1
 
0.7%
Other values (127) 127
90.7%
2024-03-13T23:17:01.165510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
3.1%
대 20
 
2.6%
리 14
 
1.8%
점 14
 
1.8%
구 13
 
1.7%
이 12
 
1.6%
장 11
 
1.4%
비 10
 
1.3%
식 10
 
1.3%
사 10
 
1.3%
Other values (251) 633
82.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 717
93.0%
Space Separator 24
 
3.1%
Uppercase Letter 11
 
1.4%
Open Punctuation 9
 
1.2%
Close Punctuation 9
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 20
 
2.8%
리 14
 
2.0%
점 14
 
2.0%
구 13
 
1.8%
이 12
 
1.7%
장 11
 
1.5%
비 10
 
1.4%
식 10
 
1.4%
사 10
 
1.4%
동 10
 
1.4%
Other values (239) 593
82.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
B 2
18.2%
Y 2
18.2%
K 1
9.1%
E 1
9.1%
U 1
9.1%
L 1
9.1%
M 1
9.1%
Space Separator
ValueCountFrequency (%)
24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 717
93.0%
Common 43
 
5.6%
Latin 11
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 20
 
2.8%
리 14
 
2.0%
점 14
 
2.0%
구 13
 
1.8%
이 12
 
1.7%
장 11
 
1.5%
비 10
 
1.4%
식 10
 
1.4%
사 10
 
1.4%
동 10
 
1.4%
Other values (239) 593
82.7%
Latin
ValueCountFrequency (%)
S 2
18.2%
B 2
18.2%
Y 2
18.2%
K 1
9.1%
E 1
9.1%
U 1
9.1%
L 1
9.1%
M 1
9.1%
Common
ValueCountFrequency (%)
24
55.8%
( 9
 
20.9%
) 9
 
20.9%
: 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 717
93.0%
ASCII 54
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
44.4%
( 9
 
16.7%
) 9
 
16.7%
S 2
 
3.7%
B 2
 
3.7%
Y 2
 
3.7%
K 1
 
1.9%
E 1
 
1.9%
U 1
 
1.9%
L 1
 
1.9%
Other values (2) 2
 
3.7%
Hangul
ValueCountFrequency (%)
대 20
 
2.8%
리 14
 
2.0%
점 14
 
2.0%
구 13
 
1.8%
이 12
 
1.7%
장 11
 
1.5%
비 10
 
1.4%
식 10
 
1.4%
사 10
 
1.4%
동 10
 
1.4%
Other values (239) 593
82.7%

도로명주소
Text

Distinct114
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T23:17:01.492296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.12069
Min length10

Characters and Unicode

Total characters2218
Distinct characters75
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)96.6%

Sample

1st row서구 와룡로 460(이현동)
2nd row서구 염색공단천로 88(비산동)
3rd row서구 팔달로 80(비산동)
4th row서구 문화로17길 32
5th row서구 큰장로 61(내당동)
ValueCountFrequency (%)
서구 114
25.2%
대구광역시 56
 
12.4%
1층 18
 
4.0%
국채보상로 13
 
2.9%
통학로 10
 
2.2%
평리동 8
 
1.8%
비산동 7
 
1.5%
문화로 7
 
1.5%
서대구로 6
 
1.3%
달구벌대로 4
 
0.9%
Other values (169) 210
46.4%
2024-03-13T23:17:02.042885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
15.5%
구 199
 
9.0%
서 144
 
6.5%
로 116
 
5.2%
1 95
 
4.3%
대 86
 
3.9%
동 64
 
2.9%
( 63
 
2.8%
) 62
 
2.8%
길 57
 
2.6%
Other values (65) 988
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1252
56.4%
Decimal Number 446
 
20.1%
Space Separator 344
 
15.5%
Open Punctuation 63
 
2.8%
Close Punctuation 62
 
2.8%
Other Punctuation 26
 
1.2%
Dash Punctuation 24
 
1.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 199
15.9%
서 144
 
11.5%
로 116
 
9.3%
대 86
 
6.9%
동 64
 
5.1%
길 57
 
4.6%
시 56
 
4.5%
역 56
 
4.5%
광 56
 
4.5%
리 34
 
2.7%
Other values (49) 384
30.7%
Decimal Number
ValueCountFrequency (%)
1 95
21.3%
2 53
11.9%
3 49
11.0%
7 43
9.6%
6 42
9.4%
4 40
9.0%
5 34
 
7.6%
9 34
 
7.6%
0 30
 
6.7%
8 26
 
5.8%
Space Separator
ValueCountFrequency (%)
344
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1252
56.4%
Common 965
43.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 199
15.9%
서 144
 
11.5%
로 116
 
9.3%
대 86
 
6.9%
동 64
 
5.1%
길 57
 
4.6%
시 56
 
4.5%
역 56
 
4.5%
광 56
 
4.5%
리 34
 
2.7%
Other values (49) 384
30.7%
Common
ValueCountFrequency (%)
344
35.6%
1 95
 
9.8%
( 63
 
6.5%
) 62
 
6.4%
2 53
 
5.5%
3 49
 
5.1%
7 43
 
4.5%
6 42
 
4.4%
4 40
 
4.1%
5 34
 
3.5%
Other values (5) 140
14.5%
Latin
ValueCountFrequency (%)
M 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1252
56.4%
ASCII 966
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
35.6%
1 95
 
9.8%
( 63
 
6.5%
) 62
 
6.4%
2 53
 
5.5%
3 49
 
5.1%
7 43
 
4.5%
6 42
 
4.3%
4 40
 
4.1%
5 34
 
3.5%
Other values (6) 141
14.6%
Hangul
ValueCountFrequency (%)
구 199
15.9%
서 144
 
11.5%
로 116
 
9.3%
대 86
 
6.9%
동 64
 
5.1%
길 57
 
4.6%
시 56
 
4.5%
역 56
 
4.5%
광 56
 
4.5%
리 34
 
2.7%
Other values (49) 384
30.7%

전화번호
Text

MISSING 

Distinct77
Distinct (%)100.0%
Missing39
Missing (%)33.6%
Memory size1.0 KiB
2024-03-13T23:17:02.344354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.038961
Min length9

Characters and Unicode

Total characters927
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

Unique77 ?
Unique (%)100.0%

Sample

1st row053-558-3331
2nd row053-352-1756
3rd row053-358-5678
4th row053-356-4998
5th row053-571-8585
ValueCountFrequency (%)
053-358-1147 1
 
1.3%
053-567-9497 1
 
1.3%
053-553-9780 1
 
1.3%
053-551-2601 1
 
1.3%
053-557-1652 1
 
1.3%
053-552-8402 1
 
1.3%
053-555-6000 1
 
1.3%
1544-8855 1
 
1.3%
053-282-9982 1
 
1.3%
053-565-8100 1
 
1.3%
Other values (67) 67
87.0%
2024-03-13T23:17:02.804973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 212
22.9%
- 153
16.5%
0 128
13.8%
3 123
13.3%
6 63
 
6.8%
2 56
 
6.0%
8 44
 
4.7%
1 44
 
4.7%
7 44
 
4.7%
4 30
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 774
83.5%
Dash Punctuation 153
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 212
27.4%
0 128
16.5%
3 123
15.9%
6 63
 
8.1%
2 56
 
7.2%
8 44
 
5.7%
1 44
 
5.7%
7 44
 
5.7%
4 30
 
3.9%
9 30
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 927
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 212
22.9%
- 153
16.5%
0 128
13.8%
3 123
13.3%
6 63
 
6.8%
2 56
 
6.0%
8 44
 
4.7%
1 44
 
4.7%
7 44
 
4.7%
4 30
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 212
22.9%
- 153
16.5%
0 128
13.8%
3 123
13.3%
6 63
 
6.8%
2 56
 
6.0%
8 44
 
4.7%
1 44
 
4.7%
7 44
 
4.7%
4 30
 
3.2%

할인율
Text

Distinct54
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T23:17:03.071661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length40
Mean length13.224138
Min length6

Characters and Unicode

Total characters1534
Distinct characters142
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

Unique40 ?
Unique (%)34.5%

Sample

1st row수리비 5%
2nd row수리비 5%
3rd row수리비 5%
4th row전체품목5%
5th row전체품목10%
ValueCountFrequency (%)
전체품목 55
15.4%
5 47
 
13.2%
할인 43
 
12.0%
10 17
 
4.8%
서비스 15
 
4.2%
기타 12
 
3.4%
전품목 9
 
2.5%
제공(음료수 8
 
2.2%
시 8
 
2.2%
펌,염색10 7
 
2.0%
Other values (101) 136
38.1%
2024-03-13T23:17:03.489720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
241
 
15.7%
% 100
 
6.5%
품 89
 
5.8%
목 82
 
5.3%
전 76
 
5.0%
체 65
 
4.2%
0 61
 
4.0%
5 59
 
3.8%
할 55
 
3.6%
인 55
 
3.6%
Other values (132) 651
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 906
59.1%
Space Separator 241
 
15.7%
Decimal Number 185
 
12.1%
Other Punctuation 131
 
8.5%
Open Punctuation 32
 
2.1%
Close Punctuation 32
 
2.1%
Lowercase Letter 5
 
0.3%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 89
 
9.8%
목 82
 
9.1%
전 76
 
8.4%
체 65
 
7.2%
할 55
 
6.1%
인 55
 
6.1%
제 25
 
2.8%
비 23
 
2.5%
서 22
 
2.4%
기 21
 
2.3%
Other values (114) 393
43.4%
Decimal Number
ValueCountFrequency (%)
0 61
33.0%
5 59
31.9%
1 54
29.2%
2 8
 
4.3%
3 3
 
1.6%
Other Punctuation
ValueCountFrequency (%)
% 100
76.3%
, 27
 
20.6%
. 3
 
2.3%
: 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
l 2
40.0%
g 1
20.0%
k 1
20.0%
m 1
20.0%
Space Separator
ValueCountFrequency (%)
241
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 906
59.1%
Common 623
40.6%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 89
 
9.8%
목 82
 
9.1%
전 76
 
8.4%
체 65
 
7.2%
할 55
 
6.1%
인 55
 
6.1%
제 25
 
2.8%
비 23
 
2.5%
서 22
 
2.4%
기 21
 
2.3%
Other values (114) 393
43.4%
Common
ValueCountFrequency (%)
241
38.7%
% 100
16.1%
0 61
 
9.8%
5 59
 
9.5%
1 54
 
8.7%
( 32
 
5.1%
) 32
 
5.1%
, 27
 
4.3%
2 8
 
1.3%
. 3
 
0.5%
Other values (4) 6
 
1.0%
Latin
ValueCountFrequency (%)
l 2
40.0%
g 1
20.0%
k 1
20.0%
m 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 906
59.1%
ASCII 628
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
241
38.4%
% 100
15.9%
0 61
 
9.7%
5 59
 
9.4%
1 54
 
8.6%
( 32
 
5.1%
) 32
 
5.1%
, 27
 
4.3%
2 8
 
1.3%
. 3
 
0.5%
Other values (8) 11
 
1.8%
Hangul
ValueCountFrequency (%)
품 89
 
9.8%
목 82
 
9.1%
전 76
 
8.4%
체 65
 
7.2%
할 55
 
6.1%
인 55
 
6.1%
제 25
 
2.8%
비 23
 
2.5%
서 22
 
2.4%
기 21
 
2.3%
Other values (114) 393
43.4%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
복지정책과
116 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복지정책과 116
100.0%

Length

2024-03-13T23:17:03.640988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:17:03.749104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지정책과 116
100.0%

Correlations

2024-03-13T23:17:03.821026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호할인율
전화번호1.0001.000
할인율1.0001.000

Missing values

2024-03-13T23:17:00.367744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T23:17:00.495116image/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

업체명도로명주소전화번호할인율담당부서
0영훈자동차정비공장서구 와룡로 460(이현동)053-558-3331수리비 5%복지정책과
1대구보링서구 염색공단천로 88(비산동)053-352-1756수리비 5%복지정책과
2대구자동차정비서구 팔달로 80(비산동)053-358-5678수리비 5%복지정책과
3삼성강철가구서구 문화로17길 32053-356-4998전체품목5%복지정책과
4큰장길침구류명물거리(무궁화홈패션)서구 큰장로 61(내당동)053-571-8585전체품목10%복지정책과
5서대구꽃집서구 통학로 166-1(평리동)053-564-6232전체품목10%복지정책과
6대흥건재철물(열쇠)서구 통학로 152(평리동)053-567-0923전체품목10%(건재제외,현금결제)복지정책과
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