Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells5
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory57.3 B

Variable types

Categorical3
Text3
DateTime1

Dataset

Description대구광역시 동구_자원봉사자 할인가맹점 현황_20200529
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15052511&dataSetDetailId=150525111b9776dfde786&provdMethod=FILE

Alerts

구군명 has constant value ""Constant
연락처 has 5 (5.0%) missing valuesMissing
업소명 has unique valuesUnique
도로명 주소 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:35:17.589654
Analysis finished2024-04-19 05:35:18.171043
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
대구광역시 동구
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 동구
2nd row대구광역시 동구
3rd row대구광역시 동구
4th row대구광역시 동구
5th row대구광역시 동구

Common Values

ValueCountFrequency (%)
대구광역시 동구 100
100.0%

Length

2024-04-19T14:35:18.237452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:35:18.327277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 100
50.0%
동구 100
50.0%

업소명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-19T14:35:18.543492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length6.98
Min length3

Characters and Unicode

Total characters698
Distinct characters235
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row씨네 80
2nd row동화사 집단시설지구(산중식당)
3rd row동화사 집단시설지구(산채식당)
4th row동화사 집단시설지구(고향식당)
5th row동화사 집단시설지구(폭포식당)
ValueCountFrequency (%)
동화사 8
 
6.2%
방촌점 2
 
1.6%
gm대우 2
 
1.6%
씨네 1
 
0.8%
착한낙지랑산오징어 1
 
0.8%
명품세탁 1
 
0.8%
효성미용실 1
 
0.8%
대광상사 1
 
0.8%
백담구이 1
 
0.8%
큰집삼계탕 1
 
0.8%
Other values (110) 110
85.3%
2024-04-19T14:35:18.933224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
4.2%
식 17
 
2.4%
당 15
 
2.1%
스 14
 
2.0%
동 14
 
2.0%
집 13
 
1.9%
사 13
 
1.9%
구 13
 
1.9%
( 12
 
1.7%
) 12
 
1.7%
Other values (225) 546
78.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 631
90.4%
Space Separator 29
 
4.2%
Open Punctuation 12
 
1.7%
Close Punctuation 12
 
1.7%
Other Symbol 5
 
0.7%
Decimal Number 5
 
0.7%
Uppercase Letter 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 17
 
2.7%
당 15
 
2.4%
스 14
 
2.2%
동 14
 
2.2%
집 13
 
2.1%
사 13
 
2.1%
구 13
 
2.1%
지 11
 
1.7%
미 10
 
1.6%
화 10
 
1.6%
Other values (215) 501
79.4%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
6 1
20.0%
0 1
20.0%
8 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
50.0%
G 2
50.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 636
91.1%
Common 58
 
8.3%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 17
 
2.7%
당 15
 
2.4%
스 14
 
2.2%
동 14
 
2.2%
집 13
 
2.0%
사 13
 
2.0%
구 13
 
2.0%
지 11
 
1.7%
미 10
 
1.6%
화 10
 
1.6%
Other values (216) 506
79.6%
Common
ValueCountFrequency (%)
29
50.0%
( 12
20.7%
) 12
20.7%
3 2
 
3.4%
6 1
 
1.7%
0 1
 
1.7%
8 1
 
1.7%
Latin
ValueCountFrequency (%)
M 2
50.0%
G 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 631
90.4%
ASCII 62
 
8.9%
None 5
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
46.8%
( 12
19.4%
) 12
19.4%
3 2
 
3.2%
M 2
 
3.2%
G 2
 
3.2%
6 1
 
1.6%
0 1
 
1.6%
8 1
 
1.6%
Hangul
ValueCountFrequency (%)
식 17
 
2.7%
당 15
 
2.4%
스 14
 
2.2%
동 14
 
2.2%
집 13
 
2.1%
사 13
 
2.1%
구 13
 
2.1%
지 11
 
1.7%
미 10
 
1.6%
화 10
 
1.6%
Other values (215) 501
79.4%
None
ValueCountFrequency (%)
㈜ 5
100.0%

업종
Categorical

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
음식점
45 
자동차정비
9 
미용업
7 
세탁업
5 
꽃집
 
3
Other values (24)
31 

Length

Max length10
Median length3
Mean length3.34
Min length2

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st row영화관
2nd row음식점
3rd row음식점
4th row음식점
5th row음식점

Common Values

ValueCountFrequency (%)
음식점 45
45.0%
자동차정비 9
 
9.0%
미용업 7
 
7.0%
세탁업 5
 
5.0%
꽃집 3
 
3.0%
이용업 3
 
3.0%
화장품 2
 
2.0%
호텔 2
 
2.0%
영화관 2
 
2.0%
스포츠센터 2
 
2.0%
Other values (19) 20
20.0%

Length

2024-04-19T14:35:19.079358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
음식점 45
44.6%
자동차정비 9
 
8.9%
미용업 7
 
6.9%
세탁업 5
 
5.0%
꽃집 3
 
3.0%
이용업 3
 
3.0%
영화관 2
 
2.0%
스포츠센터 2
 
2.0%
서점 2
 
2.0%
호텔 2
 
2.0%
Other values (20) 21
20.8%

도로명 주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-19T14:35:19.309615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length17.09
Min length9

Characters and Unicode

Total characters1709
Distinct characters97
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row동구 팔공산로 1184(용수동)
2nd row동구 팔공산로 185길 55(용수동)
3rd row동구 팔공산로 185길 72(용수동)
4th row동구 팔공산로 185길 63(용수동)
5th row동구 팔공산로 185길 74(용수동)
ValueCountFrequency (%)
동구 100
29.9%
팔공산로 10
 
3.0%
동촌로 6
 
1.8%
185길 6
 
1.8%
팔공로 5
 
1.5%
효신로 5
 
1.5%
화랑로25길 4
 
1.2%
아양로 3
 
0.9%
1층 3
 
0.9%
동부로 3
 
0.9%
Other values (170) 190
56.7%
2024-04-19T14:35:19.693023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
14.0%
동 222
 
13.0%
로 107
 
6.3%
구 102
 
6.0%
) 90
 
5.3%
( 90
 
5.3%
1 88
 
5.1%
길 58
 
3.4%
2 58
 
3.4%
신 44
 
2.6%
Other values (87) 611
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 882
51.6%
Decimal Number 376
22.0%
Space Separator 239
 
14.0%
Close Punctuation 90
 
5.3%
Open Punctuation 90
 
5.3%
Dash Punctuation 18
 
1.1%
Other Punctuation 14
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 222
25.2%
로 107
12.1%
구 102
11.6%
길 58
 
6.6%
신 44
 
5.0%
효 30
 
3.4%
공 25
 
2.8%
팔 25
 
2.8%
목 18
 
2.0%
천 16
 
1.8%
Other values (72) 235
26.6%
Decimal Number
ValueCountFrequency (%)
1 88
23.4%
2 58
15.4%
5 42
11.2%
3 41
10.9%
8 33
 
8.8%
6 30
 
8.0%
9 27
 
7.2%
4 25
 
6.6%
0 16
 
4.3%
7 16
 
4.3%
Space Separator
ValueCountFrequency (%)
239
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 882
51.6%
Common 827
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 222
25.2%
로 107
12.1%
구 102
11.6%
길 58
 
6.6%
신 44
 
5.0%
효 30
 
3.4%
공 25
 
2.8%
팔 25
 
2.8%
목 18
 
2.0%
천 16
 
1.8%
Other values (72) 235
26.6%
Common
ValueCountFrequency (%)
239
28.9%
) 90
 
10.9%
( 90
 
10.9%
1 88
 
10.6%
2 58
 
7.0%
5 42
 
5.1%
3 41
 
5.0%
8 33
 
4.0%
6 30
 
3.6%
9 27
 
3.3%
Other values (5) 89
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 882
51.6%
ASCII 827
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
28.9%
) 90
 
10.9%
( 90
 
10.9%
1 88
 
10.6%
2 58
 
7.0%
5 42
 
5.1%
3 41
 
5.0%
8 33
 
4.0%
6 30
 
3.6%
9 27
 
3.3%
Other values (5) 89
 
10.8%
Hangul
ValueCountFrequency (%)
동 222
25.2%
로 107
12.1%
구 102
11.6%
길 58
 
6.6%
신 44
 
5.0%
효 30
 
3.4%
공 25
 
2.8%
팔 25
 
2.8%
목 18
 
2.0%
천 16
 
1.8%
Other values (72) 235
26.6%

연락처
Text

MISSING 

Distinct95
Distinct (%)100.0%
Missing5
Missing (%)5.0%
Memory size932.0 B
2024-04-19T14:35:19.958280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021053
Min length12

Characters and Unicode

Total characters1142
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

Unique95 ?
Unique (%)100.0%

Sample

1st row053-984-0801
2nd row053-982-0077
3rd row053-985-4082
4th row053-982-1755
5th row053-982-0128
ValueCountFrequency (%)
053-985-7961 1
 
1.1%
053-959-1236 1
 
1.1%
053-743-1532 1
 
1.1%
053-964-3117 1
 
1.1%
053-964-6861 1
 
1.1%
053-983-3477 1
 
1.1%
053-985-5888 1
 
1.1%
053-982-1080 1
 
1.1%
053-983-6466 1
 
1.1%
053-743-3651 1
 
1.1%
Other values (85) 85
89.5%
2024-04-19T14:35:20.337669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 190
16.6%
0 164
14.4%
5 161
14.1%
3 142
12.4%
9 97
8.5%
8 86
7.5%
1 72
 
6.3%
7 63
 
5.5%
4 63
 
5.5%
6 53
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 952
83.4%
Dash Punctuation 190
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 164
17.2%
5 161
16.9%
3 142
14.9%
9 97
10.2%
8 86
9.0%
1 72
7.6%
7 63
 
6.6%
4 63
 
6.6%
6 53
 
5.6%
2 51
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1142
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 190
16.6%
0 164
14.4%
5 161
14.1%
3 142
12.4%
9 97
8.5%
8 86
7.5%
1 72
 
6.3%
7 63
 
5.5%
4 63
 
5.5%
6 53
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 190
16.6%
0 164
14.4%
5 161
14.1%
3 142
12.4%
9 97
8.5%
8 86
7.5%
1 72
 
6.3%
7 63
 
5.5%
4 63
 
5.5%
6 53
 
4.6%

할인내용(할인율)
Categorical

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전체품목 10%
24 
전체품목 5%
16 
전체품목10%
11 
전체품목5%
 
3
전품목 10%
 
3
Other values (40)
43 

Length

Max length71
Median length38
Mean length10.42
Min length2

Unique

Unique38 ?
Unique (%)38.0%

Sample

1st row2,000원
2nd row전체품목10%
3rd row전체품목10%
4th row전체품목10%
5th row전체품목10%

Common Values

ValueCountFrequency (%)
전체품목 10% 24
24.0%
전체품목 5% 16
16.0%
전체품목10% 11
 
11.0%
전체품목5% 3
 
3.0%
전품목 10% 3
 
3.0%
전체품목 5% 3
 
3.0%
정비공임 10% 2
 
2.0%
월 수련비 10% 1
 
1.0%
객실20%,온천사우나30%,식음료10% 1
 
1.0%
일부품목(공임15%) 1
 
1.0%
Other values (35) 35
35.0%

Length

2024-04-19T14:35:20.500417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체품목 52
22.9%
10 38
16.7%
5 27
 
11.9%
전체품목10 11
 
4.8%
할인 8
 
3.5%
전품목 6
 
2.6%
제외 6
 
2.6%
20 4
 
1.8%
2,000원 3
 
1.3%
전체품목5 3
 
1.3%
Other values (63) 69
30.4%

지정일자
Date

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2006-11-20 00:00:00
Maximum2020-03-31 00:00:00
2024-04-19T14:35:20.629211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:35:20.747941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

Correlations

2024-04-19T14:35:20.839215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명업종도로명 주소연락처할인내용(할인율)지정일자
업소명1.0001.0001.0001.0001.0001.000
업종1.0001.0001.0001.0000.9120.862
도로명 주소1.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
할인내용(할인율)1.0000.9121.0001.0001.0000.972
지정일자1.0000.8621.0001.0000.9721.000
2024-04-19T14:35:20.945801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
할인내용(할인율)업종
할인내용(할인율)1.0000.368
업종0.3681.000
2024-04-19T14:35:21.036043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종할인내용(할인율)
업종1.0000.368
할인내용(할인율)0.3681.000

Missing values

2024-04-19T14:35:18.009454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:35:18.130072image/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

구군명업소명업종도로명 주소연락처할인내용(할인율)지정일자
0대구광역시 동구씨네 80영화관동구 팔공산로 1184(용수동)053-984-08012,000원2006-11-20
1대구광역시 동구동화사 집단시설지구(산중식당)음식점동구 팔공산로 185길 55(용수동)053-982-0077전체품목10%2008-03-20
2대구광역시 동구동화사 집단시설지구(산채식당)음식점동구 팔공산로 185길 72(용수동)053-985-4082전체품목10%2008-03-20
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