Overview

Dataset statistics

Number of variables16
Number of observations41
Missing cells41
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory135.2 B

Variable types

Numeric1
Text4
Categorical5
Boolean6

Dataset

Description대구 북구 전통시장 28개 중 하나인 태전중앙시장의 상점정보에 대한 csv 파일이다. 시장의 상점들의 주소, 상품권 사용 유무 등의 정보을 파악할 수 있다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15109917/fileData.do

Alerts

전통시장 상가번영회 가입유무 has constant value ""Constant
상점 홈페이지 주소 has constant value ""Constant
소재지 지번주소 is highly imbalanced (83.5%)Imbalance
온누리 상품권 사용유무 is highly imbalanced (62.2%)Imbalance
문화상품권 사용유무 is highly imbalanced (53.9%)Imbalance
전자상품권 사용유무 is highly imbalanced (62.2%)Imbalance
위도 is highly imbalanced (83.5%)Imbalance
경도 is highly imbalanced (83.5%)Imbalance
대표품목 has 1 (2.4%) missing valuesMissing
상점 홈페이지 주소 has 40 (97.6%) missing valuesMissing
상점코드 has unique valuesUnique
상점명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:13:44.556785
Analysis finished2023-12-12 06:13:46.030841
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상점코드
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.487805
Minimum1
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T15:13:46.114856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median26
Q342
95-th percentile51
Maximum54
Range53
Interquartile range (IQR)29

Descriptive statistics

Standard deviation16.572752
Coefficient of variation (CV)0.60291288
Kurtosis-1.3567004
Mean27.487805
Median Absolute Deviation (MAD)15
Skewness-0.047220713
Sum1127
Variance274.6561
MonotonicityStrictly increasing
2023-12-12T15:13:46.519691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1
 
2.4%
43 1
 
2.4%
35 1
 
2.4%
36 1
 
2.4%
37 1
 
2.4%
38 1
 
2.4%
39 1
 
2.4%
40 1
 
2.4%
41 1
 
2.4%
42 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
9 1
2.4%
11 1
2.4%
12 1
2.4%
ValueCountFrequency (%)
54 1
2.4%
52 1
2.4%
51 1
2.4%
50 1
2.4%
49 1
2.4%
48 1
2.4%
46 1
2.4%
45 1
2.4%
44 1
2.4%
43 1
2.4%

상점명
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T15:13:46.738750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.8536585
Min length3

Characters and Unicode

Total characters240
Distinct characters121
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

Unique41 ?
Unique (%)100.0%

Sample

1st row세종찌짐이
2nd row소문난김밥
3rd row태전돼지국밥
4th row청우원 일등 한우 쇠고기
5th row동원장식
ValueCountFrequency (%)
주)맛찬들 2
 
3.9%
세종찌짐이 1
 
2.0%
시장고추방앗간 1
 
2.0%
동광떡집 1
 
2.0%
동광떡집_2 1
 
2.0%
최신이용소 1
 
2.0%
장수건강원 1
 
2.0%
중앙족발 1
 
2.0%
달래분식 1
 
2.0%
잡곡잡화 1
 
2.0%
Other values (40) 40
78.4%
2023-12-12T15:13:47.120655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
5.4%
10
 
4.2%
9
 
3.8%
_ 8
 
3.3%
2 7
 
2.9%
6
 
2.5%
6
 
2.5%
5
 
2.1%
5
 
2.1%
5
 
2.1%
Other values (111) 166
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
86.7%
Space Separator 10
 
4.2%
Decimal Number 9
 
3.8%
Connector Punctuation 8
 
3.3%
Close Punctuation 2
 
0.8%
Open Punctuation 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
6.2%
9
 
4.3%
6
 
2.9%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
4
 
1.9%
4
 
1.9%
3
 
1.4%
Other values (103) 148
71.2%
Decimal Number
ValueCountFrequency (%)
2 7
77.8%
1 1
 
11.1%
3 1
 
11.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
86.7%
Common 32
 
13.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
6.2%
9
 
4.3%
6
 
2.9%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
4
 
1.9%
4
 
1.9%
3
 
1.4%
Other values (103) 148
71.2%
Common
ValueCountFrequency (%)
10
31.2%
_ 8
25.0%
2 7
21.9%
) 2
 
6.2%
( 2
 
6.2%
1 1
 
3.1%
3 1
 
3.1%
& 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
86.7%
ASCII 32
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13
 
6.2%
9
 
4.3%
6
 
2.9%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
4
 
1.9%
4
 
1.9%
3
 
1.4%
Other values (103) 148
71.2%
ASCII
ValueCountFrequency (%)
10
31.2%
_ 8
25.0%
2 7
21.9%
) 2
 
6.2%
( 2
 
6.2%
1 1
 
3.1%
3 1
 
3.1%
& 1
 
3.1%
Distinct34
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T15:13:47.358395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length23.292683
Min length21

Characters and Unicode

Total characters955
Distinct characters126
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

Unique27 ?
Unique (%)65.9%

Sample

1st row대구광역시 북구 태전로 15 (세종찌짐이)
2nd row대구광역시 북구 태전로 15 (소문난김밥)
3rd row대구광역시 북구 태전로 15 (태전돼지국밥)
4th row대구광역시 북구 태전로 15 (청우원 일등 한우 쇠고기)
5th row대구광역시 북구 태전로 15 (동원장식)
ValueCountFrequency (%)
대구광역시 41
19.1%
태전로 41
19.1%
15 41
19.1%
북구 41
19.1%
중앙족발 2
 
0.9%
합천식당 2
 
0.9%
동광떡집 2
 
0.9%
동원장식 2
 
0.9%
창진푸드 2
 
0.9%
성진고기마트 2
 
0.9%
Other values (38) 39
18.1%
2023-12-12T15:13:47.732136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
18.2%
82
 
8.6%
44
 
4.6%
1 43
 
4.5%
43
 
4.5%
43
 
4.5%
43
 
4.5%
41
 
4.3%
) 41
 
4.3%
( 41
 
4.3%
Other values (116) 360
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
64.1%
Space Separator 174
 
18.2%
Decimal Number 86
 
9.0%
Close Punctuation 41
 
4.3%
Open Punctuation 41
 
4.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
82
13.4%
44
 
7.2%
43
 
7.0%
43
 
7.0%
43
 
7.0%
41
 
6.7%
41
 
6.7%
41
 
6.7%
41
 
6.7%
11
 
1.8%
Other values (109) 182
29.7%
Decimal Number
ValueCountFrequency (%)
1 43
50.0%
5 41
47.7%
2 2
 
2.3%
Space Separator
ValueCountFrequency (%)
174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
64.1%
Common 343
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
82
13.4%
44
 
7.2%
43
 
7.0%
43
 
7.0%
43
 
7.0%
41
 
6.7%
41
 
6.7%
41
 
6.7%
41
 
6.7%
11
 
1.8%
Other values (109) 182
29.7%
Common
ValueCountFrequency (%)
174
50.7%
1 43
 
12.5%
) 41
 
12.0%
( 41
 
12.0%
5 41
 
12.0%
2 2
 
0.6%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
64.1%
ASCII 343
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
50.7%
1 43
 
12.5%
) 41
 
12.0%
( 41
 
12.0%
5 41
 
12.0%
2 2
 
0.6%
& 1
 
0.3%
Hangul
ValueCountFrequency (%)
82
13.4%
44
 
7.2%
43
 
7.0%
43
 
7.0%
43
 
7.0%
41
 
6.7%
41
 
6.7%
41
 
6.7%
41
 
6.7%
11
 
1.8%
Other values (109) 182
29.7%

소재지 지번주소
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
대구광역시 북구 태전동 156-1
40 
대구광역시 북구 태전동 156-1 (다동 122호)
 
1

Length

Max length28
Median length18
Mean length18.243902
Min length18

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row대구광역시 북구 태전동 156-1
2nd row대구광역시 북구 태전동 156-1
3rd row대구광역시 북구 태전동 156-1
4th row대구광역시 북구 태전동 156-1
5th row대구광역시 북구 태전동 156-1

Common Values

ValueCountFrequency (%)
대구광역시 북구 태전동 156-1 40
97.6%
대구광역시 북구 태전동 156-1 (다동 122호) 1
 
2.4%

Length

2023-12-12T15:13:47.875170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:13:47.983285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 41
24.7%
북구 41
24.7%
태전동 41
24.7%
156-1 41
24.7%
다동 1
 
0.6%
122호 1
 
0.6%
Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
음식점
23 
기타
17 
쇼핑시설
 
1

Length

Max length4
Median length3
Mean length2.6097561
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
음식점 23
56.1%
기타 17
41.5%
쇼핑시설 1
 
2.4%

Length

2023-12-12T15:13:48.100218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:13:48.212722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점 23
56.1%
기타 17
41.5%
쇼핑시설 1
 
2.4%

대표품목
Text

MISSING 

Distinct34
Distinct (%)85.0%
Missing1
Missing (%)2.4%
Memory size460.0 B
2023-12-12T15:13:48.429422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length4.925
Min length2

Characters and Unicode

Total characters197
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)70.0%

Sample

1st row전, 제사음식
2nd row분식
3rd row국밥
4th row정육점(한우)
5th row인테리어 (도배 장판)
ValueCountFrequency (%)
제사음식 5
 
9.4%
인테리어 3
 
5.7%
분식 3
 
5.7%
떡집 2
 
3.8%
정육점 2
 
3.8%
족발 2
 
3.8%
튀김류 2
 
3.8%
국밥 2
 
3.8%
국수 2
 
3.8%
생닭 1
 
1.9%
Other values (29) 29
54.7%
2023-12-12T15:13:48.786565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
6.6%
, 12
 
6.1%
11
 
5.6%
8
 
4.1%
6
 
3.0%
6
 
3.0%
6
 
3.0%
5
 
2.5%
5
 
2.5%
4
 
2.0%
Other values (73) 121
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
83.2%
Space Separator 13
 
6.6%
Other Punctuation 12
 
6.1%
Close Punctuation 4
 
2.0%
Open Punctuation 4
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
6.7%
8
 
4.9%
6
 
3.7%
6
 
3.7%
6
 
3.7%
5
 
3.0%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (69) 105
64.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
83.2%
Common 33
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
6.7%
8
 
4.9%
6
 
3.7%
6
 
3.7%
6
 
3.7%
5
 
3.0%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (69) 105
64.0%
Common
ValueCountFrequency (%)
13
39.4%
, 12
36.4%
) 4
 
12.1%
( 4
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
83.2%
ASCII 33
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
39.4%
, 12
36.4%
) 4
 
12.1%
( 4
 
12.1%
Hangul
ValueCountFrequency (%)
11
 
6.7%
8
 
4.9%
6
 
3.7%
6
 
3.7%
6
 
3.7%
5
 
3.0%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (69) 105
64.0%
Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size173.0 B
True
41 
ValueCountFrequency (%)
True 41
100.0%
2023-12-12T15:13:48.895569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size173.0 B
True
38 
False
 
3
ValueCountFrequency (%)
True 38
92.7%
False 3
 
7.3%
2023-12-12T15:13:49.000494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

문화상품권 사용유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size173.0 B
False
37 
True
ValueCountFrequency (%)
False 37
90.2%
True 4
 
9.8%
2023-12-12T15:13:49.089412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전자상품권 사용유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size173.0 B
False
38 
True
 
3
ValueCountFrequency (%)
False 38
92.7%
True 3
 
7.3%
2023-12-12T15:13:49.170338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size173.0 B
True
26 
False
15 
ValueCountFrequency (%)
True 26
63.4%
False 15
36.6%
2023-12-12T15:13:49.249256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size173.0 B
False
33 
True
ValueCountFrequency (%)
False 33
80.5%
True 8
 
19.5%
2023-12-12T15:13:49.352245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

종업원 수
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
1
33 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 33
80.5%
2 8
 
19.5%

Length

2023-12-12T15:13:49.467718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:13:49.577285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 33
80.5%
2 8
 
19.5%

상점 홈페이지 주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing40
Missing (%)97.6%
Memory size460.0 B
2023-12-12T15:13:49.730070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowbabirangcoffee.modoo.at
ValueCountFrequency (%)
babirangcoffee.modoo.at 1
100.0%
2023-12-12T15:13:50.023932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 4
17.4%
a 3
13.0%
b 2
8.7%
f 2
8.7%
e 2
8.7%
. 2
8.7%
i 1
 
4.3%
r 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (4) 4
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21
91.3%
Other Punctuation 2
 
8.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
19.0%
a 3
14.3%
b 2
9.5%
f 2
9.5%
e 2
9.5%
i 1
 
4.8%
r 1
 
4.8%
n 1
 
4.8%
g 1
 
4.8%
c 1
 
4.8%
Other values (3) 3
14.3%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
91.3%
Common 2
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
19.0%
a 3
14.3%
b 2
9.5%
f 2
9.5%
e 2
9.5%
i 1
 
4.8%
r 1
 
4.8%
n 1
 
4.8%
g 1
 
4.8%
c 1
 
4.8%
Other values (3) 3
14.3%
Common
ValueCountFrequency (%)
. 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 4
17.4%
a 3
13.0%
b 2
8.7%
f 2
8.7%
e 2
8.7%
. 2
8.7%
i 1
 
4.3%
r 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (4) 4
17.4%

위도
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
35.921677
40 
35.921743
 
1

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row35.921677
2nd row35.921677
3rd row35.921677
4th row35.921677
5th row35.921677

Common Values

ValueCountFrequency (%)
35.921677 40
97.6%
35.921743 1
 
2.4%

Length

2023-12-12T15:13:50.157936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:13:50.249673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35.921677 40
97.6%
35.921743 1
 
2.4%

경도
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
128.544946
40 
128.545089
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row128.544946
2nd row128.544946
3rd row128.544946
4th row128.544946
5th row128.544946

Common Values

ValueCountFrequency (%)
128.544946 40
97.6%
128.545089 1
 
2.4%

Length

2023-12-12T15:13:50.342146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:13:50.432759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
128.544946 40
97.6%
128.545089 1
 
2.4%

Interactions

2023-12-12T15:13:45.548834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:13:50.513404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수위도경도
상점코드1.0001.0000.9110.0000.3700.9550.5700.5970.0000.0000.4990.3560.0000.000
상점명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지 도로명 주소0.9111.0001.0001.0000.0000.9921.0001.0001.0001.0001.0001.0001.0001.000
소재지 지번주소0.0001.0001.0001.0000.000NaN0.0000.0000.0000.0000.0000.0000.6700.670
상점업종분류0.3701.0000.0000.0001.0000.0000.0000.1170.0710.0000.2540.0000.0000.000
대표품목0.9551.0000.992NaN0.0001.0001.0001.0001.0001.0001.0001.000NaNNaN
온누리 상품권 사용유무0.5701.0001.0000.0000.0001.0001.0000.0000.0000.3480.0000.0000.0000.000
문화상품권 사용유무0.5971.0001.0000.0000.1171.0000.0001.0000.5250.0820.0000.0000.0000.000
전자상품권 사용유무0.0001.0001.0000.0000.0711.0000.0000.5251.0000.0000.0000.0000.0000.000
카드단말기 유무0.0001.0001.0000.0000.0001.0000.3480.0820.0001.0000.1490.4440.0000.000
택배서비스 유무0.4991.0001.0000.0000.2541.0000.0000.0000.0000.1491.0000.0000.0000.000
종업원 수0.3561.0001.0000.0000.0001.0000.0000.0000.0000.4440.0001.0000.0000.000
위도0.0001.0001.0000.6700.000NaN0.0000.0000.0000.0000.0000.0001.0000.670
경도0.0001.0001.0000.6700.000NaN0.0000.0000.0000.0000.0000.0000.6701.000
2023-12-12T15:13:50.689653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카드단말기 유무경도문화상품권 사용유무소재지 지번주소온누리 상품권 사용유무종업원 수전자상품권 사용유무상점업종분류위도택배서비스 유무
카드단말기 유무1.0000.0000.0460.0000.2250.2920.0000.0000.0000.092
경도0.0001.0000.0000.4670.0000.0000.0000.0000.4670.000
문화상품권 사용유무0.0460.0001.0000.0000.0000.0000.3510.1880.0000.000
소재지 지번주소0.0000.4670.0001.0000.0000.0000.0000.0000.4670.000
온누리 상품권 사용유무0.2250.0000.0000.0001.0000.0000.0000.0000.0000.000
종업원 수0.2920.0000.0000.0000.0001.0000.0000.0000.0000.000
전자상품권 사용유무0.0000.0000.3510.0000.0000.0001.0000.1100.0000.000
상점업종분류0.0000.0000.1880.0000.0000.0000.1101.0000.0000.408
위도0.0000.4670.0000.4670.0000.0000.0000.0001.0000.000
택배서비스 유무0.0920.0000.0000.0000.0000.0000.0000.4080.0001.000
2023-12-12T15:13:50.817030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상점코드소재지 지번주소상점업종분류온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수위도경도
상점코드1.0000.0000.2030.3860.4060.0000.0000.3360.2330.0000.000
소재지 지번주소0.0001.0000.0000.0000.0000.0000.0000.0000.0000.4670.467
상점업종분류0.2030.0001.0000.0000.1880.1100.0000.4080.0000.0000.000
온누리 상품권 사용유무0.3860.0000.0001.0000.0000.0000.2250.0000.0000.0000.000
문화상품권 사용유무0.4060.0000.1880.0001.0000.3510.0460.0000.0000.0000.000
전자상품권 사용유무0.0000.0000.1100.0000.3511.0000.0000.0000.0000.0000.000
카드단말기 유무0.0000.0000.0000.2250.0460.0001.0000.0920.2920.0000.000
택배서비스 유무0.3360.0000.4080.0000.0000.0000.0921.0000.0000.0000.000
종업원 수0.2330.0000.0000.0000.0000.0000.2920.0001.0000.0000.000
위도0.0000.4670.0000.0000.0000.0000.0000.0000.0001.0000.467
경도0.0000.4670.0000.0000.0000.0000.0000.0000.0000.4671.000

Missing values

2023-12-12T15:13:45.663737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:13:45.859831image/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.
2023-12-12T15:13:45.983223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목전통시장 상가번영회 가입유무온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수상점 홈페이지 주소위도경도
01세종찌짐이대구광역시 북구 태전로 15 (세종찌짐이)대구광역시 북구 태전동 156-1음식점전, 제사음식YYNNNN1<NA>35.921677128.544946
12소문난김밥대구광역시 북구 태전로 15 (소문난김밥)대구광역시 북구 태전동 156-1음식점분식YYNNYN1<NA>35.921677128.544946
23태전돼지국밥대구광역시 북구 태전로 15 (태전돼지국밥)대구광역시 북구 태전동 156-1음식점국밥YYNNYN1<NA>35.921677128.544946
34청우원 일등 한우 쇠고기대구광역시 북구 태전로 15 (청우원 일등 한우 쇠고기)대구광역시 북구 태전동 156-1기타정육점(한우)YYNNYN1<NA>35.921677128.544946
45동원장식대구광역시 북구 태전로 15 (동원장식)대구광역시 북구 태전동 156-1기타인테리어 (도배 장판)YYNNYY1<NA>35.921677128.544946
56합천식당대구광역시 북구 태전로 15 (합천식당)대구광역시 북구 태전동 156-1음식점국밥YYNNYN1<NA>35.921677128.544946
67태전분식대구광역시 북구 태전로 15 (태전분식)대구광역시 북구 태전동 156-1음식점국수YYYNYN1<NA>35.921677128.544946
79똘똘이식당대구광역시 북구 태전로 15 (똘똘이식당)대구광역시 북구 태전동 156-1음식점한정식YYNNNN1<NA>35.921677128.544946
811만남의장대구광역시 북구 태전로 15 (만남의장)대구광역시 북구 태전동 156-1음식점콩국수YYYNYN1<NA>35.921677128.544946
912옷이날개대구광역시 북구 태전로 15 (옷이날개)대구광역시 북구 태전동 156-1기타개인 사무실YNNNNN1<NA>35.921677128.544946
상점코드상점명소재지 도로명 주소소재지 지번주소상점업종분류대표품목전통시장 상가번영회 가입유무온누리 상품권 사용유무문화상품권 사용유무전자상품권 사용유무카드단말기 유무택배서비스 유무종업원 수상점 홈페이지 주소위도경도
3143(주)맛찬들 창진푸드대구광역시 북구 태전로 15 (창진푸드)대구광역시 북구 태전동 156-1음식점제사음식, 튀김류YYNNNN2<NA>35.921677128.544946
3244(주)맛찬들 창진푸드_2대구광역시 북구 태전로 15 (창진푸드)대구광역시 북구 태전동 156-1음식점제사음식, 튀김류YYNNNN2<NA>35.921677128.544946
3345고향식당대구광역시 북구 태전로 15 (고향식당)대구광역시 북구 태전동 156-1음식점제사음식,튀김류,순대,전YYNNYN1<NA>35.921677128.544946
3446바비랑커피대구광역시 북구 태전로 15 1층 (바비랑커피)대구광역시 북구 태전동 156-1음식점김밥, 커피YYNYYY1babirangcoffee.modoo.at35.921677128.544946
3548중앙족발_2대구광역시 북구 태전로 15 (중앙족발)대구광역시 북구 태전동 156-1쇼핑시설족발YYNNYN1<NA>35.921677128.544946
3649양지식당대구광역시 북구 태전로 15 (다동 122호)대구광역시 북구 태전동 156-1 (다동 122호)음식점<NA>YYNNYN1<NA>35.921743128.545089
3750성진고기마트_1대구광역시 북구 태전로 15 (성진고기마트)대구광역시 북구 태전동 156-1기타정육점YYNNYY2<NA>35.921677128.544946
3851성진고기마트_2대구광역시 북구 태전로 15 (성진고기마트)대구광역시 북구 태전동 156-1기타정육점YYNNYY2<NA>35.921677128.544946
3952맵시나옷수선대구광역시 북구 태전로 15 (맵시나옷수선)대구광역시 북구 태전동 156-1기타옷수선YYNNNY2<NA>35.921677128.544946
4054세종찌짐이2대구광역시 북구 태전로 15 (세종찌짐이)대구광역시 북구 태전동 156-1음식점찌짐YYNNNN1<NA>35.921677128.544946