Overview

Dataset statistics

Number of variables6
Number of observations26
Missing cells1
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory53.1 B

Variable types

Text3
Categorical2
DateTime1

Dataset

Description성남시 내 착한가격업소에 대한 목록으로 업소명,구별,주소, 전화번호,주요취급품목의 항목으로 구성되어 있습니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15043684/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 1 (3.8%) missing valuesMissing
업소명 has unique valuesUnique
주소(소재지) has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:30:26.062709
Analysis finished2024-04-29 22:30:27.960825
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-30T07:30:28.124790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.8461538
Min length3

Characters and Unicode

Total characters152
Distinct characters102
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row희 미용실
2nd row장미세탁소
3rd row어머니손맛
4th row도세기 맛집
5th row산성샤브샤브칼국수
ValueCountFrequency (%)
희 1
 
3.4%
대왕이발관 1
 
3.4%
김명진헤어센스 1
 
3.4%
머리나라 1
 
3.4%
명동스넥 1
 
3.4%
신정이용원 1
 
3.4%
참소한우국밥 1
 
3.4%
충남이발관 1
 
3.4%
왕두꺼비부대찌개 1
 
3.4%
메이찬 1
 
3.4%
Other values (19) 19
65.5%
2024-04-30T07:30:28.489506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 6
 
3.9%
대 4
 
2.6%
어 4
 
2.6%
용 4
 
2.6%
이 4
 
2.6%
국 4
 
2.6%
3
 
2.0%
헤 3
 
2.0%
스 3
 
2.0%
세 3
 
2.0%
Other values (92) 114
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
98.0%
Space Separator 3
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 6
 
4.0%
대 4
 
2.7%
어 4
 
2.7%
용 4
 
2.7%
이 4
 
2.7%
국 4
 
2.7%
헤 3
 
2.0%
스 3
 
2.0%
세 3
 
2.0%
실 3
 
2.0%
Other values (91) 111
74.5%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
98.0%
Common 3
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 6
 
4.0%
대 4
 
2.7%
어 4
 
2.7%
용 4
 
2.7%
이 4
 
2.7%
국 4
 
2.7%
헤 3
 
2.0%
스 3
 
2.0%
세 3
 
2.0%
실 3
 
2.0%
Other values (91) 111
74.5%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
98.0%
ASCII 3
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 6
 
4.0%
대 4
 
2.7%
어 4
 
2.7%
용 4
 
2.7%
이 4
 
2.7%
국 4
 
2.7%
헤 3
 
2.0%
스 3
 
2.0%
세 3
 
2.0%
실 3
 
2.0%
Other values (91) 111
74.5%
ASCII
ValueCountFrequency (%)
3
100.0%

구별
Categorical

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
수정구
12 
중원구
11 
분당구
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수정구
2nd row중원구
3rd row중원구
4th row수정구
5th row중원구

Common Values

ValueCountFrequency (%)
수정구 12
46.2%
중원구 11
42.3%
분당구 3
 
11.5%

Length

2024-04-30T07:30:28.605067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:30:28.690351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수정구 12
46.2%
중원구 11
42.3%
분당구 3
 
11.5%

주소(소재지)
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-30T07:30:28.879224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length29
Min length23

Characters and Unicode

Total characters754
Distinct characters70
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

Unique26 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 수정구 성남대로1179번길 8(수진동)
2nd row경기도 성남시 중원구 박석로 25번길 21(상대원동)
3rd row경기도 성남시 중원구 산성대로 80번길 18, 1층(성남동, 수성빌딩)
4th row경기도 성남시 수정구 산성대로383번길 6(단대동)
5th row경기도 성남시 중원구 산성대로 594 1층(은행동)
ValueCountFrequency (%)
경기도 26
17.0%
성남시 26
17.0%
수정구 12
 
7.8%
중원구 11
 
7.2%
산성대로 6
 
3.9%
분당구 3
 
2.0%
대왕판교로 3
 
2.0%
1층(성남동 2
 
1.3%
976번길 2
 
1.3%
둔촌대로 2
 
1.3%
Other values (60) 60
39.2%
2024-04-30T07:30:29.220455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
16.8%
성 40
 
5.3%
남 34
 
4.5%
구 29
 
3.8%
경 26
 
3.4%
로 26
 
3.4%
도 26
 
3.4%
시 26
 
3.4%
기 26
 
3.4%
1 25
 
3.3%
Other values (60) 369
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 456
60.5%
Space Separator 127
 
16.8%
Decimal Number 113
 
15.0%
Open Punctuation 24
 
3.2%
Close Punctuation 24
 
3.2%
Other Punctuation 5
 
0.7%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 40
 
8.8%
남 34
 
7.5%
구 29
 
6.4%
경 26
 
5.7%
로 26
 
5.7%
도 26
 
5.7%
시 26
 
5.7%
기 26
 
5.7%
동 24
 
5.3%
수 21
 
4.6%
Other values (45) 178
39.0%
Decimal Number
ValueCountFrequency (%)
1 25
22.1%
5 16
14.2%
3 13
11.5%
9 10
 
8.8%
8 9
 
8.0%
6 9
 
8.0%
0 8
 
7.1%
4 8
 
7.1%
7 8
 
7.1%
2 7
 
6.2%
Space Separator
ValueCountFrequency (%)
127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 456
60.5%
Common 298
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 40
 
8.8%
남 34
 
7.5%
구 29
 
6.4%
경 26
 
5.7%
로 26
 
5.7%
도 26
 
5.7%
시 26
 
5.7%
기 26
 
5.7%
동 24
 
5.3%
수 21
 
4.6%
Other values (45) 178
39.0%
Common
ValueCountFrequency (%)
127
42.6%
1 25
 
8.4%
( 24
 
8.1%
) 24
 
8.1%
5 16
 
5.4%
3 13
 
4.4%
9 10
 
3.4%
8 9
 
3.0%
6 9
 
3.0%
0 8
 
2.7%
Other values (5) 33
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 456
60.5%
ASCII 298
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
42.6%
1 25
 
8.4%
( 24
 
8.1%
) 24
 
8.1%
5 16
 
5.4%
3 13
 
4.4%
9 10
 
3.4%
8 9
 
3.0%
6 9
 
3.0%
0 8
 
2.7%
Other values (5) 33
 
11.1%
Hangul
ValueCountFrequency (%)
성 40
 
8.8%
남 34
 
7.5%
구 29
 
6.4%
경 26
 
5.7%
로 26
 
5.7%
도 26
 
5.7%
시 26
 
5.7%
기 26
 
5.7%
동 24
 
5.3%
수 21
 
4.6%
Other values (45) 178
39.0%

전화번호
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing1
Missing (%)3.8%
Memory size340.0 B
2024-04-30T07:30:29.390599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.12
Min length12

Characters and Unicode

Total characters303
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

Unique23 ?
Unique (%)92.0%

Sample

1st row031-722-5691
2nd row031-735-9690
3rd row031-758-7006
4th row031-743-8610
5th row031-744-8880
ValueCountFrequency (%)
031-735-5809 2
 
8.0%
031-723-7905 1
 
4.0%
031-758-9436 1
 
4.0%
031-721-5599 1
 
4.0%
031-708-6881 1
 
4.0%
031-755-1124 1
 
4.0%
031-749-2757 1
 
4.0%
031-734-7928 1
 
4.0%
031-717-8707 1
 
4.0%
031-716-9090 1
 
4.0%
Other values (14) 14
56.0%
2024-04-30T07:30:29.672161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
16.5%
0 45
14.9%
3 40
13.2%
7 38
12.5%
1 37
12.2%
9 19
 
6.3%
5 18
 
5.9%
8 17
 
5.6%
2 15
 
5.0%
4 13
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 253
83.5%
Dash Punctuation 50
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
17.8%
3 40
15.8%
7 38
15.0%
1 37
14.6%
9 19
7.5%
5 18
 
7.1%
8 17
 
6.7%
2 15
 
5.9%
4 13
 
5.1%
6 11
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
16.5%
0 45
14.9%
3 40
13.2%
7 38
12.5%
1 37
12.2%
9 19
 
6.3%
5 18
 
5.9%
8 17
 
5.6%
2 15
 
5.0%
4 13
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
16.5%
0 45
14.9%
3 40
13.2%
7 38
12.5%
1 37
12.2%
9 19
 
6.3%
5 18
 
5.9%
8 17
 
5.6%
2 15
 
5.0%
4 13
 
4.3%

업종
Categorical

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
한식
13 
미용업
6 
중식
2 
이용업
2 
세탁업
 
1
Other values (2)
2 

Length

Max length6
Median length2
Mean length2.5384615
Min length2

Unique

Unique3 ?
Unique (%)11.5%

Sample

1st row미용업
2nd row세탁업
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 13
50.0%
미용업 6
23.1%
중식 2
 
7.7%
이용업 2
 
7.7%
세탁업 1
 
3.8%
기타서비스업 1
 
3.8%
목욕업 1
 
3.8%

Length

2024-04-30T07:30:29.805577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:30:29.950507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 13
50.0%
미용업 6
23.1%
중식 2
 
7.7%
이용업 2
 
7.7%
세탁업 1
 
3.8%
기타서비스업 1
 
3.8%
목욕업 1
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2024-04-23 00:00:00
Maximum2024-04-23 00:00:00
2024-04-30T07:30:30.042590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:30:30.126657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-04-30T07:30:30.185760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명구별주소(소재지)전화번호업종
업소명1.0001.0001.0001.0001.000
구별1.0001.0001.0000.8850.116
주소(소재지)1.0001.0001.0001.0001.000
전화번호1.0000.8851.0001.0000.985
업종1.0000.1161.0000.9851.000
2024-04-30T07:30:30.286012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별업종
구별1.0000.000
업종0.0001.000
2024-04-30T07:30:30.350567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별업종
구별1.0000.000
업종0.0001.000

Missing values

2024-04-30T07:30:27.768879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:30:27.905712image/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

업소명구별주소(소재지)전화번호업종데이터기준일자
0희 미용실수정구경기도 성남시 수정구 성남대로1179번길 8(수진동)031-722-5691미용업2024-04-23
1장미세탁소중원구경기도 성남시 중원구 박석로 25번길 21(상대원동)031-735-9690세탁업2024-04-23
2어머니손맛중원구경기도 성남시 중원구 산성대로 80번길 18, 1층(성남동, 수성빌딩)031-758-7006한식2024-04-23
3도세기 맛집수정구경기도 성남시 수정구 산성대로383번길 6(단대동)031-743-8610한식2024-04-23
4산성샤브샤브칼국수중원구경기도 성남시 중원구 산성대로 594 1층(은행동)031-744-8880한식2024-04-23
5송림순대국중원구경기도 성남시 중원구 광명로 70(성남동)031-757-9493한식2024-04-23
6전주식당수정구경기도 성남시 수정구 산성대로 595 1층(양지동)031-743-9849한식2024-04-23
7주막골숯불돼지삼겹살중원구경기도 성남시 중원구 금상로 108길 100507-1316-7728한식2024-04-23
8엄니네쌈냉면중원구경기도 성남시 중원구 제일로 35번길 6 1층(성남동)031-755-6321한식2024-04-23
9육회랑쭈꾸미랑수정구경기도 성남시 수정구 수정남로 71(수진동)031-735-5809한식2024-04-23
업소명구별주소(소재지)전화번호업종데이터기준일자
16투가리해장국수정구경기도 성남시 수정구 산성대로 595(양지동, 1층)031-733-1603한식2024-04-23
17메이찬분당구경기도 성남시 분당구 미금일로 90번길 36-5(구미동)031-716-9090중식2024-04-23
18왕두꺼비부대찌개분당구경기도 성남시 분당구 구미로 11 (구미동)031-717-8707한식2024-04-23
19충남이발관중원구경기도 성남시 중원구 산성대로 396번길18(금광동)031-734-7928이용업2024-04-23
20참소한우국밥중원구경기도 성남시 중원구 산성대로 350번길 5 (중앙동)031-749-2757한식2024-04-23
21신정이용원중원구경기도 성남시 중원구 성남대로1147번길 12 (성남동)031-755-1124한식2024-04-23
22명동스넥분당구경기도 성남시 분당구 판교로 436 (이매동)031-708-6881한식2024-04-23
23머리나라수정구경기도 성남시 수정구 수정로154번길15-1(신흥동5807)031-721-5599미용업2024-04-23
24김명진헤어센스수정구경기도 성남시 수정구 수정남로30번길 14-1 (수진동)031-758-9436미용업2024-04-23
25영광미용실수정구경기도 성남시 수정구 대왕판교로 976번길 9-7 (고등동)031-723-7026미용업2024-04-23