Overview

Dataset statistics

Number of variables11
Number of observations96
Missing cells33
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory94.4 B

Variable types

Categorical3
Text2
Numeric5
DateTime1

Dataset

Description부산광역시_대규모점포등록현황_20230630
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15055771

Alerts

위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
총 매장면적(제곱미터) is highly overall correlated with 판매면적(제곱미터) and 2 other fieldsHigh correlation
판매면적(제곱미터) is highly overall correlated with 총 매장면적(제곱미터)High correlation
용역제공면적(제곱미터) is highly overall correlated with 총 매장면적(제곱미터) and 1 other fieldsHigh correlation
광역자치단체 is highly overall correlated with 총 매장면적(제곱미터) and 2 other fieldsHigh correlation
기초자치단체 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
광역자치단체 is highly imbalanced (85.4%)Imbalance
용역제공면적(제곱미터) has 33 (34.4%) missing valuesMissing
총 매장면적(제곱미터) has unique valuesUnique
판매면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:43:09.242389
Analysis finished2023-12-10 16:43:12.800460
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광역자치단체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size900.0 B
부산광역시
94 
부산광역시
 
2

Length

Max length6
Median length5
Mean length5.0208333
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 94
97.9%
부산광역시 2
 
2.1%

Length

2023-12-11T01:43:12.870679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:43:12.953582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 96
100.0%

기초자치단체
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size900.0 B
부산진구
17 
해운대구
13 
사하구
12 
기장군
9 
동래구
8 
Other values (11)
37 

Length

Max length4
Median length3
Mean length3.1458333
Min length2

Unique

Unique3 ?
Unique (%)3.1%

Sample

1st row중구
2nd row영도구
3rd row부산진구
4th row부산진구
5th row부산진구

Common Values

ValueCountFrequency (%)
부산진구 17
17.7%
해운대구 13
13.5%
사하구 12
12.5%
기장군 9
9.4%
동래구 8
8.3%
남구 7
7.3%
연제구 5
 
5.2%
사상구 5
 
5.2%
북구 4
 
4.2%
금정구 4
 
4.2%
Other values (6) 12
12.5%

Length

2023-12-11T01:43:13.049931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산진구 17
17.7%
해운대구 13
13.5%
사하구 12
12.5%
기장군 9
9.4%
동래구 8
8.3%
남구 7
7.3%
연제구 5
 
5.2%
사상구 5
 
5.2%
북구 4
 
4.2%
금정구 4
 
4.2%
Other values (6) 12
12.5%

상호
Text

Distinct95
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T01:43:13.261399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.3333333
Min length3

Characters and Unicode

Total characters800
Distinct characters176
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)97.9%

Sample

1st row롯데마트 광복점
2nd row홈플러스 영도점
3rd row홈플러스 서면점
4th row홈플러스 가야점
5th row이마트 트레이더스서면점
ValueCountFrequency (%)
홈플러스 13
 
8.1%
이마트 6
 
3.7%
부산점 6
 
3.7%
롯데마트 5
 
3.1%
롯데백화점 4
 
2.5%
동래점 4
 
2.5%
광복점 3
 
1.9%
센텀시티점 3
 
1.9%
해운대점 3
 
1.9%
메가마트 3
 
1.9%
Other values (104) 111
68.9%
2023-12-11T01:43:13.605485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
8.1%
점 61
 
7.6%
스 29
 
3.6%
산 26
 
3.2%
트 25
 
3.1%
부 22
 
2.8%
아 20
 
2.5%
마 18
 
2.2%
가 15
 
1.9%
데 15
 
1.9%
Other values (166) 504
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
88.6%
Space Separator 65
 
8.1%
Uppercase Letter 15
 
1.9%
Lowercase Letter 4
 
0.5%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 61
 
8.6%
스 29
 
4.1%
산 26
 
3.7%
트 25
 
3.5%
부 22
 
3.1%
아 20
 
2.8%
마 18
 
2.5%
가 15
 
2.1%
데 15
 
2.1%
이 15
 
2.1%
Other values (149) 463
65.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
33.3%
N 3
20.0%
O 1
 
6.7%
M 1
 
6.7%
B 1
 
6.7%
T 1
 
6.7%
F 1
 
6.7%
I 1
 
6.7%
W 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
x 1
25.0%
e 1
25.0%
l 1
25.0%
p 1
25.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 709
88.6%
Common 72
 
9.0%
Latin 19
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 61
 
8.6%
스 29
 
4.1%
산 26
 
3.7%
트 25
 
3.5%
부 22
 
3.1%
아 20
 
2.8%
마 18
 
2.5%
가 15
 
2.1%
데 15
 
2.1%
이 15
 
2.1%
Other values (149) 463
65.3%
Latin
ValueCountFrequency (%)
C 5
26.3%
N 3
15.8%
O 1
 
5.3%
M 1
 
5.3%
B 1
 
5.3%
T 1
 
5.3%
x 1
 
5.3%
e 1
 
5.3%
l 1
 
5.3%
p 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
65
90.3%
( 3
 
4.2%
) 3
 
4.2%
- 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 709
88.6%
ASCII 91
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
71.4%
C 5
 
5.5%
N 3
 
3.3%
( 3
 
3.3%
) 3
 
3.3%
- 1
 
1.1%
O 1
 
1.1%
M 1
 
1.1%
B 1
 
1.1%
T 1
 
1.1%
Other values (7) 7
 
7.7%
Hangul
ValueCountFrequency (%)
점 61
 
8.6%
스 29
 
4.1%
산 26
 
3.7%
트 25
 
3.5%
부 22
 
3.1%
아 20
 
2.8%
마 18
 
2.5%
가 15
 
2.1%
데 15
 
2.1%
이 15
 
2.1%
Other values (149) 463
65.3%

업태
Categorical

Distinct6
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size900.0 B
대형마트
33 
그 밖의 대규모점포
27 
쇼핑센터
16 
전문점
9 
백화점
7 

Length

Max length10
Median length4
Mean length5.5625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대형마트 33
34.4%
그 밖의 대규모점포 27
28.1%
쇼핑센터 16
16.7%
전문점 9
 
9.4%
백화점 7
 
7.3%
복합쇼핑몰 4
 
4.2%

Length

2023-12-11T01:43:13.744691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:43:13.855441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대형마트 33
22.0%
그 27
18.0%
밖의 27
18.0%
대규모점포 27
18.0%
쇼핑센터 16
10.7%
전문점 9
 
6.0%
백화점 7
 
4.7%
복합쇼핑몰 4
 
2.7%

도로명주소
Text

Distinct91
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-11T01:43:14.130864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length23.791667
Min length18

Characters and Unicode

Total characters2284
Distinct characters151
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

Unique87 ?
Unique (%)90.6%

Sample

1st row부산광역시 중구 중앙대로 2(중앙동7가)
2nd row부산광역시 영도구 대교로14번길 57(봉래동2가)
3rd row부산광역시 부산진구 동천로 4(전포동)
4th row부산광역시 부산진구 가야대로 506(가야동)
5th row부산광역시 부산진구 시민공원로 31(부암동)
ValueCountFrequency (%)
부산광역시 89
 
21.6%
부산진구 17
 
4.1%
해운대구 13
 
3.2%
사하구 12
 
2.9%
기장군 10
 
2.4%
중앙대로 9
 
2.2%
동래구 8
 
1.9%
남구 7
 
1.7%
부산 6
 
1.5%
다대로 5
 
1.2%
Other values (178) 236
57.3%
2023-12-11T01:43:14.586714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
321
 
14.1%
부 125
 
5.5%
산 119
 
5.2%
동 113
 
4.9%
로 95
 
4.2%
( 94
 
4.1%
) 94
 
4.1%
광 94
 
4.1%
시 93
 
4.1%
구 90
 
3.9%
Other values (141) 1046
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1492
65.3%
Space Separator 321
 
14.1%
Decimal Number 278
 
12.2%
Open Punctuation 94
 
4.1%
Close Punctuation 94
 
4.1%
Other Punctuation 4
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 125
 
8.4%
산 119
 
8.0%
동 113
 
7.6%
로 95
 
6.4%
광 94
 
6.3%
시 93
 
6.2%
구 90
 
6.0%
역 89
 
6.0%
대 66
 
4.4%
장 28
 
1.9%
Other values (126) 580
38.9%
Decimal Number
ValueCountFrequency (%)
1 54
19.4%
2 40
14.4%
3 39
14.0%
7 36
12.9%
4 28
10.1%
0 21
 
7.6%
5 21
 
7.6%
6 16
 
5.8%
9 14
 
5.0%
8 9
 
3.2%
Space Separator
ValueCountFrequency (%)
321
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1492
65.3%
Common 792
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 125
 
8.4%
산 119
 
8.0%
동 113
 
7.6%
로 95
 
6.4%
광 94
 
6.3%
시 93
 
6.2%
구 90
 
6.0%
역 89
 
6.0%
대 66
 
4.4%
장 28
 
1.9%
Other values (126) 580
38.9%
Common
ValueCountFrequency (%)
321
40.5%
( 94
 
11.9%
) 94
 
11.9%
1 54
 
6.8%
2 40
 
5.1%
3 39
 
4.9%
7 36
 
4.5%
4 28
 
3.5%
0 21
 
2.7%
5 21
 
2.7%
Other values (5) 44
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1492
65.3%
ASCII 792
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
321
40.5%
( 94
 
11.9%
) 94
 
11.9%
1 54
 
6.8%
2 40
 
5.1%
3 39
 
4.9%
7 36
 
4.5%
4 28
 
3.5%
0 21
 
2.7%
5 21
 
2.7%
Other values (5) 44
 
5.6%
Hangul
ValueCountFrequency (%)
부 125
 
8.4%
산 119
 
8.0%
동 113
 
7.6%
로 95
 
6.4%
광 94
 
6.3%
시 93
 
6.2%
구 90
 
6.0%
역 89
 
6.0%
대 66
 
4.4%
장 28
 
1.9%
Other values (126) 580
38.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.166673
Minimum35.051615
Maximum35.323729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-11T01:43:14.742384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.051615
5-th percentile35.083404
Q135.141359
median35.163488
Q335.192819
95-th percentile35.270989
Maximum35.323729
Range0.2721138
Interquartile range (IQR)0.051459653

Descriptive statistics

Standard deviation0.057137209
Coefficient of variation (CV)0.0016247545
Kurtosis0.87169039
Mean35.166673
Median Absolute Deviation (MAD)0.02762597
Skewness0.61301193
Sum3376.0006
Variance0.0032646607
MonotonicityNot monotonic
2023-12-11T01:43:14.900120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.09830894 3
 
3.1%
35.16366724 2
 
2.1%
35.14943396 2
 
2.1%
35.14648787 2
 
2.1%
35.22128992 2
 
2.1%
35.21170859 2
 
2.1%
35.20984297 1
 
1.0%
35.09892811 1
 
1.0%
35.19221051 1
 
1.0%
35.16315151 1
 
1.0%
Other values (79) 79
82.3%
ValueCountFrequency (%)
35.05161518 1
1.0%
35.05623593 1
1.0%
35.06147729 1
1.0%
35.07505997 1
1.0%
35.08243474 1
1.0%
35.08372718 1
1.0%
35.08478117 1
1.0%
35.09310945 1
1.0%
35.09590061 1
1.0%
35.09712033 1
1.0%
ValueCountFrequency (%)
35.32372898 1
1.0%
35.32305178 1
1.0%
35.32119451 1
1.0%
35.32111818 1
1.0%
35.27446075 1
1.0%
35.26983173 1
1.0%
35.25469204 1
1.0%
35.25002197 1
1.0%
35.24994464 1
1.0%
35.23517016 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.07004
Minimum128.91815
Maximum129.23553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-11T01:43:15.333991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.91815
5-th percentile128.96573
Q1129.01256
median129.06398
Q3129.11232
95-th percentile129.21245
Maximum129.23553
Range0.3173765
Interquartile range (IQR)0.099754125

Descriptive statistics

Standard deviation0.074595635
Coefficient of variation (CV)0.00057794695
Kurtosis-0.4566069
Mean129.07004
Median Absolute Deviation (MAD)0.0502027
Skewness0.32213674
Sum12390.724
Variance0.0055645087
MonotonicityNot monotonic
2023-12-11T01:43:15.485119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0367048 3
 
3.1%
129.1694182 2
 
2.1%
129.0639784 2
 
2.1%
129.0658605 2
 
2.1%
129.0855783 2
 
2.1%
129.0774768 2
 
2.1%
129.0744099 1
 
1.0%
128.9885412 1
 
1.0%
129.2127825 1
 
1.0%
128.9809876 1
 
1.0%
Other values (79) 79
82.3%
ValueCountFrequency (%)
128.9181487 1
1.0%
128.9516916 1
1.0%
128.9532289 1
1.0%
128.955702 1
1.0%
128.9623063 1
1.0%
128.966874 1
1.0%
128.9683596 1
1.0%
128.9705532 1
1.0%
128.9715603 1
1.0%
128.9719987 1
1.0%
ValueCountFrequency (%)
129.2355252 1
1.0%
129.2349491 1
1.0%
129.2218562 1
1.0%
129.2166394 1
1.0%
129.2127825 1
1.0%
129.2123422 1
1.0%
129.2102724 1
1.0%
129.1793443 1
1.0%
129.1782834 1
1.0%
129.1770697 1
1.0%

총 매장면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20363.031
Minimum1809
Maximum139892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-11T01:43:15.632989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1809
5-th percentile3557.5
Q16777.5
median12169.5
Q322943
95-th percentile71477
Maximum139892
Range138083
Interquartile range (IQR)16165.5

Descriptive statistics

Standard deviation24264.547
Coefficient of variation (CV)1.191598
Kurtosis8.5473772
Mean20363.031
Median Absolute Deviation (MAD)6757.5
Skewness2.7764038
Sum1954851
Variance5.8876826 × 108
MonotonicityNot monotonic
2023-12-11T01:43:15.760340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12347 1
 
1.0%
15286 1
 
1.0%
3782 1
 
1.0%
4162 1
 
1.0%
1809 1
 
1.0%
81233 1
 
1.0%
9331 1
 
1.0%
23810 1
 
1.0%
33576 1
 
1.0%
18431 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
1809 1
1.0%
2684 1
1.0%
3197 1
1.0%
3331 1
1.0%
3541 1
1.0%
3563 1
1.0%
3598 1
1.0%
3669 1
1.0%
3696 1
1.0%
3782 1
1.0%
ValueCountFrequency (%)
139892 1
1.0%
104322 1
1.0%
101059 1
1.0%
97127 1
1.0%
81233 1
1.0%
68225 1
1.0%
65649 1
1.0%
58892 1
1.0%
53531 1
1.0%
41762 1
1.0%

판매면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16651.135
Minimum1207
Maximum135626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-11T01:43:15.922338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1207
5-th percentile2887.5
Q15660.75
median10819.5
Q317739.25
95-th percentile58886.75
Maximum135626
Range134419
Interquartile range (IQR)12078.5

Descriptive statistics

Standard deviation20488.989
Coefficient of variation (CV)1.230486
Kurtosis13.370982
Mean16651.135
Median Absolute Deviation (MAD)5815.5
Skewness3.2752537
Sum1598509
Variance4.1979865 × 108
MonotonicityNot monotonic
2023-12-11T01:43:16.110558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9246 1
 
1.0%
15286 1
 
1.0%
3366 1
 
1.0%
4162 1
 
1.0%
1207 1
 
1.0%
81233 1
 
1.0%
8952 1
 
1.0%
13555 1
 
1.0%
18409 1
 
1.0%
12862 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
1207 1
1.0%
1291 1
1.0%
1447 1
1.0%
1827 1
1.0%
2757 1
1.0%
2931 1
1.0%
3127 1
1.0%
3200 1
1.0%
3366 1
1.0%
3375 1
1.0%
ValueCountFrequency (%)
135626 1
1.0%
86240 1
1.0%
81233 1
1.0%
65649 1
1.0%
61916 1
1.0%
57877 1
1.0%
53009 1
1.0%
52030 1
1.0%
40638 1
1.0%
33739 1
1.0%

용역제공면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct62
Distinct (%)98.4%
Missing33
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean5656.8889
Minimum61
Maximum48576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-11T01:43:16.251053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile155.1
Q1797
median2048
Q35201
95-th percentile23796.2
Maximum48576
Range48515
Interquartile range (IQR)4404

Descriptive statistics

Standard deviation10104.115
Coefficient of variation (CV)1.7861612
Kurtosis10.169967
Mean5656.8889
Median Absolute Deviation (MAD)1588
Skewness3.1655212
Sum356384
Variance1.0209315 × 108
MonotonicityNot monotonic
2023-12-11T01:43:16.385796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3983 2
 
2.1%
3442 1
 
1.0%
2436 1
 
1.0%
1124 1
 
1.0%
12311 1
 
1.0%
2504 1
 
1.0%
61 1
 
1.0%
5156 1
 
1.0%
5570 1
 
1.0%
15167 1
 
1.0%
Other values (52) 52
54.2%
(Missing) 33
34.4%
ValueCountFrequency (%)
61 1
1.0%
90 1
1.0%
131 1
1.0%
154 1
1.0%
165 1
1.0%
177 1
1.0%
253 1
1.0%
380 1
1.0%
416 1
1.0%
439 1
1.0%
ValueCountFrequency (%)
48576 1
1.0%
45097 1
1.0%
42406 1
1.0%
24755 1
1.0%
15167 1
1.0%
14819 1
1.0%
13980 1
1.0%
12800 1
1.0%
12311 1
1.0%
10255 1
1.0%

실제 영업개시일
Date

Distinct94
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size900.0 B
Minimum1983-11-09 00:00:00
Maximum2021-06-30 00:00:00
2023-12-11T01:43:16.531494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:16.689354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T01:43:12.181287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.251967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.706082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.196401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.685587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:12.259683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.345147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.800512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.275591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.789191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:12.336777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.432333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.899453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.376230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.890373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:12.416007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.524454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.011041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.491437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.998748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:12.492889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:10.616076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.113087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:11.594864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:12.090158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:43:16.822191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광역자치단체기초자치단체상호업태도로명주소위도경도총 매장면적(제곱미터)판매면적(제곱미터)용역제공면적(제곱미터)실제 영업개시일
광역자치단체1.0000.7751.0000.5561.0000.0000.1260.7730.5961.0001.000
기초자치단체0.7751.0001.0000.4151.0000.8310.9200.4190.5710.3101.000
상호1.0001.0001.0000.9380.9971.0001.0001.0001.0001.0001.000
업태0.5560.4150.9381.0000.0000.2390.1270.6520.6160.4590.797
도로명주소1.0001.0000.9970.0001.0001.0001.0000.7510.7490.0000.999
위도0.0000.8311.0000.2391.0001.0000.6950.0000.0000.1971.000
경도0.1260.9201.0000.1271.0000.6951.0000.2900.1830.4411.000
총 매장면적(제곱미터)0.7730.4191.0000.6520.7510.0000.2901.0000.9430.7581.000
판매면적(제곱미터)0.5960.5711.0000.6160.7490.0000.1830.9431.0000.8151.000
용역제공면적(제곱미터)1.0000.3101.0000.4590.0000.1970.4410.7580.8151.0001.000
실제 영업개시일1.0001.0001.0000.7970.9991.0001.0001.0001.0001.0001.000
2023-12-11T01:43:16.982979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광역자치단체업태기초자치단체
광역자치단체1.0000.3930.579
업태0.3931.0000.197
기초자치단체0.5790.1971.000
2023-12-11T01:43:17.080466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도총 매장면적(제곱미터)판매면적(제곱미터)용역제공면적(제곱미터)광역자치단체기초자치단체업태
위도1.0000.5730.0890.1110.1390.0000.4970.121
경도0.5731.0000.1430.1640.1400.0650.6550.055
총 매장면적(제곱미터)0.0890.1431.0000.9530.6260.7630.1810.386
판매면적(제곱미터)0.1110.1640.9531.0000.4330.4370.2260.398
용역제공면적(제곱미터)0.1390.1400.6260.4331.0000.9580.1180.290
광역자치단체0.0000.0650.7630.4370.9581.0000.5790.393
기초자치단체0.4970.6550.1810.2260.1180.5791.0000.197
업태0.1210.0550.3860.3980.2900.3930.1971.000

Missing values

2023-12-11T01:43:12.600562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:43:12.742561image/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

광역자치단체기초자치단체상호업태도로명주소위도경도총 매장면적(제곱미터)판매면적(제곱미터)용역제공면적(제곱미터)실제 영업개시일
0부산광역시중구롯데마트 광복점대형마트부산광역시 중구 중앙대로 2(중앙동7가)35.098309129.03670512347924631012014-08-28
1부산광역시영도구홈플러스 영도점대형마트부산광역시 영도구 대교로14번길 57(봉래동2가)35.095901129.044231534048604812005-02-22
2부산광역시부산진구홈플러스 서면점대형마트부산광역시 부산진구 동천로 4(전포동)35.149434129.0639781103611036<NA>1999-07-06
3부산광역시부산진구홈플러스 가야점대형마트부산광역시 부산진구 가야대로 506(가야동)35.152464129.0273171006396244392002-08-21
4부산광역시부산진구이마트 트레이더스서면점대형마트부산광역시 부산진구 시민공원로 31(부암동)35.163902129.0525541149911499<NA>2005-04-27
5부산광역시부산진구농협하나로클럽 부전점대형마트부산광역시 부산진구 중앙대로 783번길 14 (부전동)35.162754129.06218743744374<NA>2006-04-28
6부산광역시부산진구롯데키즈마트 부산점대형마트부산광역시 부산진구 신천대로 241(부암동)35.163308129.049319156741325524192011-04-28
7부산광역시동래구메가마트 동래점대형마트부산광역시 동래구 충렬대로 197(명륜동)35.204546129.08113813191121989931995-08-09
8부산광역시동래구홈플러스 동래점대형마트부산광역시 동래구 중앙대로 1523(온천동)35.22129129.0855781389513895<NA>2006-10-13
9부산광역시동래구롯데마트 동래점대형마트부산광역시 동래구 중앙대로 1393(온천동)35.211709129.07747711436111832532008-05-29
광역자치단체기초자치단체상호업태도로명주소위도경도총 매장면적(제곱미터)판매면적(제곱미터)용역제공면적(제곱미터)실제 영업개시일
86부산광역시부산진구롯데쇼핑(주) 센트럴스퀘어점그 밖의 대규모점포부산 부산진구 중앙대로 666번길 50(부전동)35.151846129.0603221248144139802011-08-26
87부산광역시해운대구제니스스퀘어그 밖의 대규모점포부산광역시 해운대구 마린시티2로 33 (우동)35.157205129.1448171747117471<NA>2012-03-21
88부산광역시사하구괴정시장 종합상가그 밖의 대규모점포부산광역시 사하구 낙동대로 203(괴정동)35.100078128.99448968076807<NA>2012-07-01
89부산광역시해운대구해운대상설할인타운그 밖의 대규모점포부산광역시 해운대구 좌동순환로 473 (중동)35.163667129.1694181199211992<NA>2012-04-17
90부산광역시남구비아이에프씨몰그 밖의 대규모점포부산광역시 남구 문현금융로 40(문현동)35.146488129.0658619643566039832014-09-01
91부산광역시기장군오시리아스퀘어그 밖의 대규모점포부산광역시 기장군 기장읍 기장해안로 9835.187708129.212342129161063822782016-07-01
92부산광역시금정구남산(농수산)시장그 밖의 대규모점포부산광역시 금정구 금강로 700(남산동)35.269832129.0892934477293115462016-10-10
93부산광역시기장군탑스퀘어그 밖의 대규모점포부산광역시 기장군 정관읍 정관중앙로 4535.321195129.1782833530010545247552018-04-07
94부산광역시서구경동타워 쇼핑그 밖의 대규모점포부산광역시 서구 보수대로 27 (토성동1가, 경동 리인)35.099271129.0242465026367613502018-01-12
95부산광역시해운대구엘시티 더 몰그 밖의 대규모점포부산광역시 해운대구 달맞이길 30(중동, 엘시티)35.161328129.168013285552011984362021-03-22