Overview

Dataset statistics

Number of variables11
Number of observations57
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory91.3 B

Variable types

Numeric1
Categorical3
Text6
DateTime1

Dataset

Description인천광역시 대규모점포(대형마트, 백화점, 쇼핑센터, 복합쇼핑몰)의 소재지, 연면적 등에 대해 알 수 있습니다.* 유통산업정보시스템 기준 자료 입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15045294&srcSe=7661IVAWM27C61E190

Alerts

광역지자체명 has constant value ""Constant
연번 is highly overall correlated with 기초지자체명High correlation
기초지자체명 is highly overall correlated with 연번High correlation
건물 연면적 has 1 (1.8%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
영업개시일 has unique valuesUnique

Reproduction

Analysis started2024-01-28 07:25:15.064362
Analysis finished2024-01-28 07:25:15.965419
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-28T16:25:16.026219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-01-28T16:25:16.137513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

광역지자체명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
인천광역시
57 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 57
100.0%

Length

2024-01-28T16:25:16.243516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:25:16.313376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 57
100.0%

기초지자체명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
서구
11 
연수구
11 
남동구
9 
미추홀구
8 
부평구
8 
Other values (3)
10 

Length

Max length4
Median length3
Mean length2.8421053
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계양구
2nd row계양구
3rd row계양구
4th row계양구
5th row남동구

Common Values

ValueCountFrequency (%)
서구 11
19.3%
연수구 11
19.3%
남동구 9
15.8%
미추홀구 8
14.0%
부평구 8
14.0%
계양구 4
 
7.0%
동구 3
 
5.3%
중구 3
 
5.3%

Length

2024-01-28T16:25:16.396897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:25:16.494847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 11
19.3%
연수구 11
19.3%
남동구 9
15.8%
미추홀구 8
14.0%
부평구 8
14.0%
계양구 4
 
7.0%
동구 3
 
5.3%
중구 3
 
5.3%

법인명
Text

Distinct43
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-28T16:25:16.684381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length13
Mean length7.8421053
Min length4

Characters and Unicode

Total characters447
Distinct characters134
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)63.2%

Sample

1st row홈플러스주식회사
2nd row홈플러스주식회사
3rd row㈜이마트
4th row롯데쇼핑(주) 롯데마트 계양점
5th row공장용품상가자치위원회
ValueCountFrequency (%)
롯데쇼핑㈜ 5
 
7.5%
홈플러스㈜ 4
 
6.0%
주식회사 3
 
4.5%
홈플러스 3
 
4.5%
홈플러스주식회사 3
 
4.5%
㈜이마트 3
 
4.5%
㈜이랜드리테일 2
 
3.0%
롯데쇼핑주식회사 2
 
3.0%
이랜드리테일 2
 
3.0%
롯데쇼핑(주 1
 
1.5%
Other values (39) 39
58.2%
2024-01-28T16:25:16.991687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 23
 
5.1%
스 17
 
3.8%
주 17
 
3.8%
이 12
 
2.7%
데 12
 
2.7%
롯 12
 
2.7%
플 11
 
2.5%
러 11
 
2.5%
홈 11
 
2.5%
핑 11
 
2.5%
Other values (124) 310
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 391
87.5%
Other Symbol 23
 
5.1%
Open Punctuation 11
 
2.5%
Space Separator 10
 
2.2%
Close Punctuation 10
 
2.2%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 17
 
4.3%
주 17
 
4.3%
이 12
 
3.1%
데 12
 
3.1%
롯 12
 
3.1%
플 11
 
2.8%
러 11
 
2.8%
홈 11
 
2.8%
핑 11
 
2.8%
쇼 11
 
2.8%
Other values (118) 266
68.0%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
6 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 414
92.6%
Common 33
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 23
 
5.6%
스 17
 
4.1%
주 17
 
4.1%
이 12
 
2.9%
데 12
 
2.9%
롯 12
 
2.9%
플 11
 
2.7%
러 11
 
2.7%
홈 11
 
2.7%
핑 11
 
2.7%
Other values (119) 277
66.9%
Common
ValueCountFrequency (%)
( 11
33.3%
10
30.3%
) 10
30.3%
5 1
 
3.0%
6 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 391
87.5%
ASCII 33
 
7.4%
None 23
 
5.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 23
100.0%
Hangul
ValueCountFrequency (%)
스 17
 
4.3%
주 17
 
4.3%
이 12
 
3.1%
데 12
 
3.1%
롯 12
 
3.1%
플 11
 
2.8%
러 11
 
2.8%
홈 11
 
2.8%
핑 11
 
2.8%
쇼 11
 
2.8%
Other values (118) 266
68.0%
ASCII
ValueCountFrequency (%)
( 11
33.3%
10
30.3%
) 10
30.3%
5 1
 
3.0%
6 1
 
3.0%

상호
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-28T16:25:17.191934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.9824561
Min length5

Characters and Unicode

Total characters512
Distinct characters145
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

Unique57 ?
Unique (%)100.0%

Sample

1st row홈플러스(주)계산점
2nd row홈플러스㈜작전점
3rd row㈜이마트계양점
4th row롯데쇼핑(주) 롯데마트 계양점
5th row공장용품상가
ValueCountFrequency (%)
롯데마트 5
 
5.4%
홈플러스 5
 
5.4%
인천점 3
 
3.2%
송도점 3
 
3.2%
연수점 2
 
2.2%
이마트 2
 
2.2%
검단점 2
 
2.2%
청라점 2
 
2.2%
인천 2
 
2.2%
뉴코아아울렛 2
 
2.2%
Other values (64) 65
69.9%
2024-01-28T16:25:17.499532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 40
 
7.8%
36
 
7.0%
트 20
 
3.9%
스 18
 
3.5%
마 14
 
2.7%
인 14
 
2.7%
플 14
 
2.7%
천 13
 
2.5%
롯 12
 
2.3%
데 12
 
2.3%
Other values (135) 319
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 447
87.3%
Space Separator 36
 
7.0%
Uppercase Letter 8
 
1.6%
Open Punctuation 6
 
1.2%
Close Punctuation 6
 
1.2%
Other Symbol 5
 
1.0%
Decimal Number 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 40
 
8.9%
트 20
 
4.5%
스 18
 
4.0%
마 14
 
3.1%
인 14
 
3.1%
플 14
 
3.1%
천 13
 
2.9%
롯 12
 
2.7%
데 12
 
2.7%
홈 11
 
2.5%
Other values (122) 279
62.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
37.5%
O 1
 
12.5%
H 1
 
12.5%
M 1
 
12.5%
E 1
 
12.5%
N 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 452
88.3%
Common 52
 
10.2%
Latin 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 40
 
8.8%
트 20
 
4.4%
스 18
 
4.0%
마 14
 
3.1%
인 14
 
3.1%
플 14
 
3.1%
천 13
 
2.9%
롯 12
 
2.7%
데 12
 
2.7%
홈 11
 
2.4%
Other values (123) 284
62.8%
Common
ValueCountFrequency (%)
36
69.2%
( 6
 
11.5%
) 6
 
11.5%
0 2
 
3.8%
1 1
 
1.9%
2 1
 
1.9%
Latin
ValueCountFrequency (%)
C 3
37.5%
O 1
 
12.5%
H 1
 
12.5%
M 1
 
12.5%
E 1
 
12.5%
N 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 447
87.3%
ASCII 60
 
11.7%
None 5
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 40
 
8.9%
트 20
 
4.5%
스 18
 
4.0%
마 14
 
3.1%
인 14
 
3.1%
플 14
 
3.1%
천 13
 
2.9%
롯 12
 
2.7%
데 12
 
2.7%
홈 11
 
2.5%
Other values (122) 279
62.4%
ASCII
ValueCountFrequency (%)
36
60.0%
( 6
 
10.0%
) 6
 
10.0%
C 3
 
5.0%
0 2
 
3.3%
O 1
 
1.7%
H 1
 
1.7%
M 1
 
1.7%
E 1
 
1.7%
N 1
 
1.7%
Other values (2) 2
 
3.3%
None
ValueCountFrequency (%)
㈜ 5
100.0%

업태
Categorical

Distinct6
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
대형마트
25 
그 밖의 대규모점포
11 
쇼핑센터
10 
전문점
6 
백화점
4 

Length

Max length10
Median length4
Mean length5
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row대형마트
2nd row대형마트
3rd row대형마트
4th row대형마트
5th row그 밖의 대규모점포

Common Values

ValueCountFrequency (%)
대형마트 25
43.9%
그 밖의 대규모점포 11
19.3%
쇼핑센터 10
 
17.5%
전문점 6
 
10.5%
백화점 4
 
7.0%
복합쇼핑몰 1
 
1.8%

Length

2024-01-28T16:25:17.609491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:25:17.712022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대형마트 25
31.6%
그 11
13.9%
밖의 11
13.9%
대규모점포 11
13.9%
쇼핑센터 10
 
12.7%
전문점 6
 
7.6%
백화점 4
 
5.1%
복합쇼핑몰 1
 
1.3%

소재지
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-28T16:25:17.989612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length31.877193
Min length18

Characters and Unicode

Total characters1817
Distinct characters132
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)96.5%

Sample

1st row(21060) 인천광역시 계양구 오조산공원로 14(계산동) 인천광역시 계양구 오조산공원로 14(계산동)
2nd row(21111) 인천광역시 계양구 계양대로 27(작전동) 인천광역시 계양구 계양대로 27(작전동)
3rd row(21080) 인천광역시 계양구 봉오대로 785(작전동) 인천광역시 계양구 봉오대로 785(작전동)
4th row(21060) 인천광역시 계양구 장제로 822 (계산동)
5th row인천광역시 남동구 남동서로 226(논현동)
ValueCountFrequency (%)
인천광역시 57
 
17.8%
연수구 11
 
3.4%
서구 11
 
3.4%
남동구 9
 
2.8%
부평구 8
 
2.5%
계양구 7
 
2.2%
경원대로 6
 
1.9%
청능대로 6
 
1.9%
송도동 6
 
1.9%
미추홀구 5
 
1.6%
Other values (157) 194
60.6%
2024-01-28T16:25:18.828894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
263
 
14.5%
2 120
 
6.6%
( 104
 
5.7%
) 104
 
5.7%
1 71
 
3.9%
동 69
 
3.8%
로 62
 
3.4%
인 60
 
3.3%
시 60
 
3.3%
구 59
 
3.2%
Other values (122) 845
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
48.9%
Decimal Number 453
24.9%
Space Separator 263
 
14.5%
Open Punctuation 104
 
5.7%
Close Punctuation 104
 
5.7%
Other Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 69
 
7.8%
로 62
 
7.0%
인 60
 
6.8%
시 60
 
6.8%
구 59
 
6.6%
천 59
 
6.6%
광 59
 
6.6%
역 58
 
6.5%
대 29
 
3.3%
남 15
 
1.7%
Other values (106) 358
40.3%
Decimal Number
ValueCountFrequency (%)
2 120
26.5%
1 71
15.7%
6 39
 
8.6%
7 38
 
8.4%
3 34
 
7.5%
5 34
 
7.5%
8 33
 
7.3%
4 29
 
6.4%
0 28
 
6.2%
9 27
 
6.0%
Space Separator
ValueCountFrequency (%)
263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 929
51.1%
Hangul 888
48.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 69
 
7.8%
로 62
 
7.0%
인 60
 
6.8%
시 60
 
6.8%
구 59
 
6.6%
천 59
 
6.6%
광 59
 
6.6%
역 58
 
6.5%
대 29
 
3.3%
남 15
 
1.7%
Other values (106) 358
40.3%
Common
ValueCountFrequency (%)
263
28.3%
2 120
12.9%
( 104
 
11.2%
) 104
 
11.2%
1 71
 
7.6%
6 39
 
4.2%
7 38
 
4.1%
3 34
 
3.7%
5 34
 
3.7%
8 33
 
3.6%
Other values (6) 89
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 929
51.1%
Hangul 888
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
263
28.3%
2 120
12.9%
( 104
 
11.2%
) 104
 
11.2%
1 71
 
7.6%
6 39
 
4.2%
7 38
 
4.1%
3 34
 
3.7%
5 34
 
3.7%
8 33
 
3.6%
Other values (6) 89
 
9.6%
Hangul
ValueCountFrequency (%)
동 69
 
7.8%
로 62
 
7.0%
인 60
 
6.8%
시 60
 
6.8%
구 59
 
6.6%
천 59
 
6.6%
광 59
 
6.6%
역 58
 
6.5%
대 29
 
3.3%
남 15
 
1.7%
Other values (106) 358
40.3%

건물 연면적
Text

MISSING 

Distinct55
Distinct (%)98.2%
Missing1
Missing (%)1.8%
Memory size588.0 B
2024-01-28T16:25:19.099142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.4821429
Min length5

Characters and Unicode

Total characters419
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st row51,727.58㎡
2nd row49,129㎡
3rd row40,467㎡
4th row56,715.31㎡
5th row4956㎡
ValueCountFrequency (%)
55229.89㎡ 2
 
3.4%
㎡ 2
 
3.4%
60534㎡ 1
 
1.7%
49,129㎡ 1
 
1.7%
56215㎡ 1
 
1.7%
59662㎡ 1
 
1.7%
20750.5㎡ 1
 
1.7%
33796.5㎡ 1
 
1.7%
38090.74㎡ 1
 
1.7%
14631.95㎡ 1
 
1.7%
Other values (46) 46
79.3%
2024-01-28T16:25:19.404275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 56
13.4%
5 42
10.0%
1 41
9.8%
2 34
8.1%
9 34
8.1%
4 32
7.6%
6 31
7.4%
, 29
6.9%
3 29
6.9%
0 27
6.4%
Other values (4) 64
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 316
75.4%
Other Symbol 56
 
13.4%
Other Punctuation 45
 
10.7%
Space Separator 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 42
13.3%
1 41
13.0%
2 34
10.8%
9 34
10.8%
4 32
10.1%
6 31
9.8%
3 29
9.2%
0 27
8.5%
7 25
7.9%
8 21
6.6%
Other Punctuation
ValueCountFrequency (%)
, 29
64.4%
. 16
35.6%
Other Symbol
ValueCountFrequency (%)
㎡ 56
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 56
13.4%
5 42
10.0%
1 41
9.8%
2 34
8.1%
9 34
8.1%
4 32
7.6%
6 31
7.4%
, 29
6.9%
3 29
6.9%
0 27
6.4%
Other values (4) 64
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 363
86.6%
CJK Compat 56
 
13.4%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 56
100.0%
ASCII
ValueCountFrequency (%)
5 42
11.6%
1 41
11.3%
2 34
9.4%
9 34
9.4%
4 32
8.8%
6 31
8.5%
, 29
8.0%
3 29
8.0%
0 27
7.4%
7 25
6.9%
Other values (3) 39
10.7%

영업장 면적
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-28T16:25:19.607150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.122807
Min length5

Characters and Unicode

Total characters406
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)96.5%

Sample

1st row24,481㎡
2nd row22,684㎡
3rd row19,757㎡
4th row34,520㎡
5th row4956㎡
ValueCountFrequency (%)
28627.55㎡ 2
 
3.4%
㎡ 2
 
3.4%
5676.92㎡ 1
 
1.7%
44660.76㎡ 1
 
1.7%
22,684㎡ 1
 
1.7%
31562㎡ 1
 
1.7%
33541㎡ 1
 
1.7%
18258.64㎡ 1
 
1.7%
12903.02㎡ 1
 
1.7%
35539.24㎡ 1
 
1.7%
Other values (47) 47
79.7%
2024-01-28T16:25:19.933459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 57
14.0%
2 42
10.3%
5 35
8.6%
1 35
8.6%
3 32
7.9%
8 30
7.4%
4 29
7.1%
, 29
7.1%
0 28
6.9%
6 27
6.7%
Other values (4) 62
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 304
74.9%
Other Symbol 57
 
14.0%
Other Punctuation 43
 
10.6%
Space Separator 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 42
13.8%
5 35
11.5%
1 35
11.5%
3 32
10.5%
8 30
9.9%
4 29
9.5%
0 28
9.2%
6 27
8.9%
7 23
7.6%
9 23
7.6%
Other Punctuation
ValueCountFrequency (%)
, 29
67.4%
. 14
32.6%
Other Symbol
ValueCountFrequency (%)
㎡ 57
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 406
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 57
14.0%
2 42
10.3%
5 35
8.6%
1 35
8.6%
3 32
7.9%
8 30
7.4%
4 29
7.1%
, 29
7.1%
0 28
6.9%
6 27
6.7%
Other values (4) 62
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 349
86.0%
CJK Compat 57
 
14.0%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 57
100.0%
ASCII
ValueCountFrequency (%)
2 42
12.0%
5 35
10.0%
1 35
10.0%
3 32
9.2%
8 30
8.6%
4 29
8.3%
, 29
8.3%
0 28
8.0%
6 27
7.7%
7 23
6.6%
Other values (3) 39
11.2%

매장면적
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-01-28T16:25:20.156624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.1403509
Min length5

Characters and Unicode

Total characters407
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)96.5%

Sample

1st row16,072㎡
2nd row18,735㎡
3rd row13,534㎡
4th row34,520㎡
5th row3269㎡
ValueCountFrequency (%)
25820.01㎡ 2
 
3.4%
㎡ 2
 
3.4%
4912.37㎡ 1
 
1.7%
21447.6㎡ 1
 
1.7%
18,735㎡ 1
 
1.7%
15452㎡ 1
 
1.7%
16240㎡ 1
 
1.7%
8105.86㎡ 1
 
1.7%
10964.68㎡ 1
 
1.7%
10761.59㎡ 1
 
1.7%
Other values (47) 47
79.7%
2024-01-28T16:25:20.470284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 57
14.0%
1 48
11.8%
3 35
8.6%
2 31
7.6%
8 29
7.1%
, 29
7.1%
0 28
 
6.9%
6 27
 
6.6%
4 27
 
6.6%
7 26
 
6.4%
Other values (4) 70
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 302
74.2%
Other Symbol 57
 
14.0%
Other Punctuation 46
 
11.3%
Space Separator 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 48
15.9%
3 35
11.6%
2 31
10.3%
8 29
9.6%
0 28
9.3%
6 27
8.9%
4 27
8.9%
7 26
8.6%
9 26
8.6%
5 25
8.3%
Other Punctuation
ValueCountFrequency (%)
, 29
63.0%
. 17
37.0%
Other Symbol
ValueCountFrequency (%)
㎡ 57
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 57
14.0%
1 48
11.8%
3 35
8.6%
2 31
7.6%
8 29
7.1%
, 29
7.1%
0 28
 
6.9%
6 27
 
6.6%
4 27
 
6.6%
7 26
 
6.4%
Other values (4) 70
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 350
86.0%
CJK Compat 57
 
14.0%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 57
100.0%
ASCII
ValueCountFrequency (%)
1 48
13.7%
3 35
10.0%
2 31
8.9%
8 29
8.3%
, 29
8.3%
0 28
8.0%
6 27
7.7%
4 27
7.7%
7 26
7.4%
9 26
7.4%
Other values (3) 44
12.6%

영업개시일
Date

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1980-03-11 00:00:00
Maximum2021-06-30 00:00:00
2024-01-28T16:25:20.594454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:25:20.720361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-01-28T16:25:15.710296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T16:25:20.800562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기초지자체명법인명상호업태소재지건물 연면적영업장 면적매장면적영업개시일
연번1.0000.9190.8231.0000.3831.0000.9460.9410.9411.000
기초지자체명0.9191.0000.8221.0000.2271.0001.0001.0001.0001.000
법인명0.8230.8221.0001.0000.9950.9931.0001.0001.0001.000
상호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업태0.3830.2270.9951.0001.0000.0001.0001.0001.0001.000
소재지1.0001.0000.9931.0000.0001.0000.9970.9970.9971.000
건물 연면적0.9461.0001.0001.0001.0000.9971.0001.0001.0001.000
영업장 면적0.9411.0001.0001.0001.0000.9971.0001.0001.0001.000
매장면적0.9411.0001.0001.0001.0000.9971.0001.0001.0001.000
영업개시일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-01-28T16:25:20.894169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기초지자체명업태
기초지자체명1.0000.115
업태0.1151.000
2024-01-28T16:25:20.963868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기초지자체명업태
연번1.0000.7540.206
기초지자체명0.7541.0000.115
업태0.2060.1151.000

Missing values

2024-01-28T16:25:15.802268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:25:15.918016image/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

연번광역지자체명기초지자체명법인명상호업태소재지건물 연면적영업장 면적매장면적영업개시일
01인천광역시계양구홈플러스주식회사홈플러스(주)계산점대형마트(21060) 인천광역시 계양구 오조산공원로 14(계산동) 인천광역시 계양구 오조산공원로 14(계산동)51,727.58㎡24,481㎡16,072㎡1998-01-08
12인천광역시계양구홈플러스주식회사홈플러스㈜작전점대형마트(21111) 인천광역시 계양구 계양대로 27(작전동) 인천광역시 계양구 계양대로 27(작전동)49,129㎡22,684㎡18,735㎡2001-06-27
23인천광역시계양구㈜이마트㈜이마트계양점대형마트(21080) 인천광역시 계양구 봉오대로 785(작전동) 인천광역시 계양구 봉오대로 785(작전동)40,467㎡19,757㎡13,534㎡2002-04-19
34인천광역시계양구롯데쇼핑(주) 롯데마트 계양점롯데쇼핑(주) 롯데마트 계양점대형마트(21060) 인천광역시 계양구 장제로 822 (계산동)56,715.31㎡34,520㎡34,520㎡2012-08-01
45인천광역시남동구공장용품상가자치위원회공장용품상가그 밖의 대규모점포인천광역시 남동구 남동서로 226(논현동)4956㎡4956㎡3269㎡1994-12-08
56인천광역시남동구한국산업단지공단남동후생시설그 밖의 대규모점포(21632) 인천광역시 남동구 남동대로239번길 68 (논현동) 남동후생시설<NA>4265㎡3631㎡1995-07-01
67인천광역시남동구소래포구종합어시장소래포구종합어시장그 밖의 대규모점포(21673) 인천광역시 남동구 소래역로 12(논현동)22388㎡13606㎡12219㎡2011-09-30
78인천광역시남동구홈플러스 주식회사홈플러스(주)구월점대형마트(21558) 인천광역시 남동구 예술로 198(구월동)82294㎡20082㎡12117㎡1999-06-24
89인천광역시남동구홈플러스홈플러스(주) 간석점대형마트(21500) 인천광역시 남동구 경원대로 971 (간석동) 경원대로 971(간석동)42745㎡37251㎡32550㎡2001-06-12
910인천광역시남동구홈플러스주식회사홈플러스(주)인천 논현점대형마트(21667) 인천광역시 남동구 청능대로 596 (논현동) 청능대로 596(논현동)119755㎡23515㎡17949㎡2010-07-08
연번광역지자체명기초지자체명법인명상호업태소재지건물 연면적영업장 면적매장면적영업개시일
4748인천광역시연수구(주)코스트코 코리아코스트코 홀세일 송도점대형마트(22009) 인천광역시 연수구 컨벤시아대로230번길 60 (송도동)47,003㎡16,784㎡13,875㎡2017-01-09
4849인천광역시연수구㈜서부티엔디스퀘어 원복합쇼핑몰(21975) 인천광역시 연수구 청능대로 210 (동춘동)169,052㎡108,205㎡88,351㎡2012-10-05
4950인천광역시연수구㈜이랜드리테일NC큐브 커넬워크점쇼핑센터(22002) 인천광역시 연수구 아트센터대로 87 (송도동)118,247㎡40,862㎡19,786㎡2013-08-31
5051인천광역시연수구홈플러스㈜홈플러스 인천송도점쇼핑센터(21984) 인천광역시 연수구 송도국제대로 165 (송도동)48,508㎡31,077㎡29,337㎡2015-10-15
5152인천광역시연수구㈜현대백화점현대백화점 프리미엄 아울렛 송도점쇼핑센터(21984) 인천광역시 연수구 송도국제대로 123 (송도동)136,534㎡58,547㎡44,643㎡2016-04-27
5253인천광역시연수구(주)에스디프런티어트리플 스트리트쇼핑센터(21984) 인천광역시 연수구 송도과학로16번길 33-3 (송도동)191,091㎡191,091㎡73,020㎡2017-04-29
5354인천광역시연수구㈜엘에프네트웍스엘에프네트웍스연수점전문점(21915) 인천광역시 연수구 청능대로23번길 11 (청학동)30,931㎡17,180㎡13,540㎡2012-12-21
5455인천광역시중구주식회사 상봉버터플라이시티그 밖의 대규모점포(22371) 인천광역시 중구 흰바위로59번길 8(운서동) 1~2층70960.47㎡7522.89㎡6296.89㎡2021-06-30
5556인천광역시중구㈜이마트이마트동인천점대형마트(22324) 인천광역시 중구 인중로 13439,947㎡18,493㎡10337㎡2001-01-06
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