Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells9
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory61.3 B

Variable types

Categorical1
Text4
DateTime2

Dataset

Description경기도 용인시 대규모 점포 현황입니다. 업태, 상호명, 소재지 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2022-07-21
URLhttps://www.data.go.kr/data/15003157/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
팩스 has 9 (36.0%) missing valuesMissing
상호명 has unique valuesUnique
연락처 has unique valuesUnique
영업개시일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:33:12.149229
Analysis finished2023-12-12 23:33:12.700126
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업태
Categorical

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
대형마트
11 
전문점
8 
쇼핑센터
5 
백화점
 
1

Length

Max length4
Median length4
Mean length3.64
Min length3

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row대형마트
2nd row쇼핑센터
3rd row대형마트
4th row쇼핑센터
5th row전문점

Common Values

ValueCountFrequency (%)
대형마트 11
44.0%
전문점 8
32.0%
쇼핑센터 5
20.0%
백화점 1
 
4.0%

Length

2023-12-13T08:33:12.778892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:33:12.922819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대형마트 11
44.0%
전문점 8
32.0%
쇼핑센터 5
20.0%
백화점 1
 
4.0%

상호명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T08:33:13.139808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.8
Min length4

Characters and Unicode

Total characters220
Distinct characters93
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

Unique25 ?
Unique (%)100.0%

Sample

1st row정동마트
2nd row골드타워 모드빌
3rd row(주)이마트 용인점
4th row더와이스퀘어
5th row신세계까사 양지점
ValueCountFrequency (%)
주)이마트 6
 
14.0%
용인점 2
 
4.7%
수지점 2
 
4.7%
기흥점 2
 
4.7%
정동마트 1
 
2.3%
수원프리미엄아울렛 1
 
2.3%
롯데마트 1
 
2.3%
신갈점 1
 
2.3%
㈜이마트 1
 
2.3%
트레이더스 1
 
2.3%
Other values (25) 25
58.1%
2023-12-13T08:33:13.565123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
8.2%
점 16
 
7.3%
트 11
 
5.0%
이 10
 
4.5%
마 9
 
4.1%
) 7
 
3.2%
( 7
 
3.2%
주 6
 
2.7%
아 4
 
1.8%
기 4
 
1.8%
Other values (83) 128
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183
83.2%
Space Separator 18
 
8.2%
Close Punctuation 7
 
3.2%
Open Punctuation 7
 
3.2%
Other Symbol 2
 
0.9%
Uppercase Letter 2
 
0.9%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 16
 
8.7%
트 11
 
6.0%
이 10
 
5.5%
마 9
 
4.9%
주 6
 
3.3%
아 4
 
2.2%
기 4
 
2.2%
흥 4
 
2.2%
프 4
 
2.2%
리 4
 
2.2%
Other values (76) 111
60.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
84.1%
Common 33
 
15.0%
Latin 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 16
 
8.6%
트 11
 
5.9%
이 10
 
5.4%
마 9
 
4.9%
주 6
 
3.2%
아 4
 
2.2%
기 4
 
2.2%
흥 4
 
2.2%
프 4
 
2.2%
리 4
 
2.2%
Other values (77) 113
61.1%
Common
ValueCountFrequency (%)
18
54.5%
) 7
 
21.2%
( 7
 
21.2%
& 1
 
3.0%
Latin
ValueCountFrequency (%)
K 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183
83.2%
ASCII 35
 
15.9%
None 2
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
51.4%
) 7
 
20.0%
( 7
 
20.0%
& 1
 
2.9%
K 1
 
2.9%
A 1
 
2.9%
Hangul
ValueCountFrequency (%)
점 16
 
8.7%
트 11
 
6.0%
이 10
 
5.5%
마 9
 
4.9%
주 6
 
3.3%
아 4
 
2.2%
기 4
 
2.2%
흥 4
 
2.2%
프 4
 
2.2%
리 4
 
2.2%
Other values (76) 111
60.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지(사무실)
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T08:33:13.879109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length23.72
Min length21

Characters and Unicode

Total characters593
Distinct characters67
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

Unique23 ?
Unique (%)92.0%

Sample

1st row처인구 고림로 206 (고림동 599-8)
2nd row처인구 금령로 71번길 8 (김량장동 254-51)
3rd row처인구 명지로 53 (역북동 586-6)
4th row처인구 중부대로 1294 (역북동 802)
5th row처인구 양지면 죽양대로 2309 (양지면 양지리 112)
ValueCountFrequency (%)
기흥구 14
 
11.0%
수지구 6
 
4.7%
처인구 5
 
3.9%
중부대로 4
 
3.1%
죽전동 4
 
3.1%
용구대로 3
 
2.4%
고매동 3
 
2.4%
63 2
 
1.6%
동백죽전대로 2
 
1.6%
공세동 2
 
1.6%
Other values (73) 82
64.6%
2023-12-13T08:33:14.255290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
 
17.2%
구 29
 
4.9%
동 26
 
4.4%
1 26
 
4.4%
3 26
 
4.4%
2 25
 
4.2%
로 25
 
4.2%
( 25
 
4.2%
) 25
 
4.2%
5 18
 
3.0%
Other values (57) 266
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
43.2%
Decimal Number 171
28.8%
Space Separator 102
 
17.2%
Open Punctuation 25
 
4.2%
Close Punctuation 25
 
4.2%
Dash Punctuation 14
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 29
 
11.3%
동 26
 
10.2%
로 25
 
9.8%
흥 16
 
6.2%
기 15
 
5.9%
대 12
 
4.7%
지 11
 
4.3%
고 8
 
3.1%
죽 7
 
2.7%
중 7
 
2.7%
Other values (43) 100
39.1%
Decimal Number
ValueCountFrequency (%)
1 26
15.2%
3 26
15.2%
2 25
14.6%
5 18
10.5%
8 15
8.8%
4 14
8.2%
0 13
7.6%
6 13
7.6%
9 11
6.4%
7 10
 
5.8%
Space Separator
ValueCountFrequency (%)
102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 337
56.8%
Hangul 256
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 29
 
11.3%
동 26
 
10.2%
로 25
 
9.8%
흥 16
 
6.2%
기 15
 
5.9%
대 12
 
4.7%
지 11
 
4.3%
고 8
 
3.1%
죽 7
 
2.7%
중 7
 
2.7%
Other values (43) 100
39.1%
Common
ValueCountFrequency (%)
102
30.3%
1 26
 
7.7%
3 26
 
7.7%
2 25
 
7.4%
( 25
 
7.4%
) 25
 
7.4%
5 18
 
5.3%
8 15
 
4.5%
- 14
 
4.2%
4 14
 
4.2%
Other values (4) 47
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 337
56.8%
Hangul 256
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
30.3%
1 26
 
7.7%
3 26
 
7.7%
2 25
 
7.4%
( 25
 
7.4%
) 25
 
7.4%
5 18
 
5.3%
8 15
 
4.5%
- 14
 
4.2%
4 14
 
4.2%
Other values (4) 47
13.9%
Hangul
ValueCountFrequency (%)
구 29
 
11.3%
동 26
 
10.2%
로 25
 
9.8%
흥 16
 
6.2%
기 15
 
5.9%
대 12
 
4.7%
지 11
 
4.3%
고 8
 
3.1%
죽 7
 
2.7%
중 7
 
2.7%
Other values (43) 100
39.1%

연락처
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T08:33:14.464389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.08
Min length9

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row031-335-8808
2nd row031-339-3430
3rd row031-326-1234
4th row031-333-6446
5th row031-816-9430
ValueCountFrequency (%)
031-335-8808 1
 
4.0%
031-5186-6500 1
 
4.0%
031-695-1041 1
 
4.0%
031-266-0455 1
 
4.0%
031-266-6071 1
 
4.0%
031-270-1052 1
 
4.0%
031-5174-4000 1
 
4.0%
031-8021-1051 1
 
4.0%
031-204-2006 1
 
4.0%
031-327-1200 1
 
4.0%
Other values (15) 15
60.0%
2023-12-13T08:33:14.844494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64
21.2%
- 49
16.2%
1 43
14.2%
3 38
12.6%
2 22
 
7.3%
5 17
 
5.6%
8 17
 
5.6%
4 17
 
5.6%
6 17
 
5.6%
7 9
 
3.0%
Other values (2) 9
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 251
83.1%
Dash Punctuation 49
 
16.2%
Space Separator 2
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64
25.5%
1 43
17.1%
3 38
15.1%
2 22
 
8.8%
5 17
 
6.8%
8 17
 
6.8%
4 17
 
6.8%
6 17
 
6.8%
7 9
 
3.6%
9 7
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64
21.2%
- 49
16.2%
1 43
14.2%
3 38
12.6%
2 22
 
7.3%
5 17
 
5.6%
8 17
 
5.6%
4 17
 
5.6%
6 17
 
5.6%
7 9
 
3.0%
Other values (2) 9
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64
21.2%
- 49
16.2%
1 43
14.2%
3 38
12.6%
2 22
 
7.3%
5 17
 
5.6%
8 17
 
5.6%
4 17
 
5.6%
6 17
 
5.6%
7 9
 
3.0%
Other values (2) 9
 
3.0%

팩스
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing9
Missing (%)36.0%
Memory size332.0 B
2023-12-13T08:33:15.016386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.125
Min length8

Characters and Unicode

Total characters130
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

Unique16 ?
Unique (%)100.0%

Sample

1st row339-3427
2nd row326-1090
3rd row333-6447
4th row8009-1090
5th row285-4154
ValueCountFrequency (%)
339-3427 1
 
6.2%
326-1090 1
 
6.2%
333-6447 1
 
6.2%
8009-1090 1
 
6.2%
285-4154 1
 
6.2%
546-1090 1
 
6.2%
679-0125 1
 
6.2%
289-0680 1
 
6.2%
327-1090 1
 
6.2%
204-0497 1
 
6.2%
Other values (6) 6
37.5%
2023-12-13T08:33:15.607237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26
20.0%
- 16
12.3%
9 14
10.8%
6 12
9.2%
2 11
8.5%
1 11
8.5%
3 9
 
6.9%
4 8
 
6.2%
8 8
 
6.2%
5 8
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114
87.7%
Dash Punctuation 16
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
22.8%
9 14
12.3%
6 12
10.5%
2 11
9.6%
1 11
9.6%
3 9
 
7.9%
4 8
 
7.0%
8 8
 
7.0%
5 8
 
7.0%
7 7
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26
20.0%
- 16
12.3%
9 14
10.8%
6 12
9.2%
2 11
8.5%
1 11
8.5%
3 9
 
6.9%
4 8
 
6.2%
8 8
 
6.2%
5 8
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26
20.0%
- 16
12.3%
9 14
10.8%
6 12
9.2%
2 11
8.5%
1 11
8.5%
3 9
 
6.9%
4 8
 
6.2%
8 8
 
6.2%
5 8
 
6.2%

영업개시일
Date

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2002-02-25 00:00:00
Maximum2022-03-25 00:00:00
2023-12-13T08:33:15.716272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:33:15.835705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2022-07-21 00:00:00
Maximum2022-07-21 00:00:00
2023-12-13T08:33:15.937955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:33:16.055327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T08:33:16.120353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태상호명소재지(사무실)연락처팩스영업개시일
업태1.0001.0000.8871.0001.0001.000
상호명1.0001.0001.0001.0001.0001.000
소재지(사무실)0.8871.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
팩스1.0001.0001.0001.0001.0001.000
영업개시일1.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T08:33:12.498499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:33:12.647383image/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

업태상호명소재지(사무실)연락처팩스영업개시일데이터기준일자
0대형마트정동마트처인구 고림로 206 (고림동 599-8)031-335-8808<NA>2021-12-022022-07-21
1쇼핑센터골드타워 모드빌처인구 금령로 71번길 8 (김량장동 254-51)031-339-3430339-34272002-02-252022-07-21
2대형마트(주)이마트 용인점처인구 명지로 53 (역북동 586-6)031-326-1234326-10902005-11-222022-07-21
3쇼핑센터더와이스퀘어처인구 중부대로 1294 (역북동 802)031-333-6446333-64472019-06-012022-07-21
4전문점신세계까사 양지점처인구 양지면 죽양대로 2309 (양지면 양지리 112)031-816-9430<NA>2022-03-252022-07-21
5전문점리빙파워센터기흥구 신고매로 59 (고매동 271)031-282-5580<NA>2020-04-292022-07-21
6전문점이케아 기흥점기흥구 신고매로 62 (고매동 산41-7)02-310-8700<NA>2019-12-122022-07-21
7전문점롯데프리미엄아울렛 기흥점기흥구 신고매로124 (고매동 280)1577-0001<NA>2018-12-062022-07-21
8대형마트코스트코 공세점기흥구 탑실로 38 (공세동 734-1)031-289-5600<NA>2015-08-242022-07-21
9대형마트(주)이마트 보라점기흥구 한보라1로 92 (보라동 623-1)031-8009-10508009-10902008-10-312022-07-21
업태상호명소재지(사무실)연락처팩스영업개시일데이터기준일자
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