Overview

Dataset statistics

Number of variables7
Number of observations88
Missing cells4
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory60.5 B

Variable types

Numeric3
Text4

Dataset

Description일반음식점의 주방 및 객실 위생, 종업원의 서비스, 식문화개선이행 등 평가항목에 따라 모범음식점 지정하여 연번, 상호명, 도로명주소, 지번주소, 전화번호, 좌표값을 제공합니다.<br/>모범음식점 선정 사업 종료로 인해 모범음식점이 추가로 선정되지 않습니다. 추후 사업 재개 여부는 미정입니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3044793&srcSe=7661IVAWM27C61E190

Alerts

도로명주소 has 1 (1.1%) missing valuesMissing
전화번호 has 3 (3.4%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:42:16.349539
Analysis finished2024-04-06 09:42:19.769346
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.5
Minimum1
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T18:42:19.854396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.35
Q122.75
median44.5
Q366.25
95-th percentile83.65
Maximum88
Range87
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation25.547342
Coefficient of variation (CV)0.57409757
Kurtosis-1.2
Mean44.5
Median Absolute Deviation (MAD)22
Skewness0
Sum3916
Variance652.66667
MonotonicityStrictly increasing
2024-04-06T18:42:19.984736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
46 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (78) 78
88.6%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%
79 1
1.1%

상호명
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T18:42:20.239843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.2613636
Min length2

Characters and Unicode

Total characters551
Distinct characters206
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row(주)드림팰리스 뷔페
2nd row(주)아레나파크컨벤션
3rd row5.5닭갈비
4th row가마솥손두부
5th row감자탕을 만드는 형제들
ValueCountFrequency (%)
주안점 2
 
1.9%
주)드림팰리스 1
 
0.9%
조가네정육식당 1
 
0.9%
선어 1
 
0.9%
인하찹쌀순대 1
 
0.9%
설악추어탕 1
 
0.9%
이천쌀밥 1
 
0.9%
이가네동태탕 1
 
0.9%
육봉달 1
 
0.9%
원주추어탕 1
 
0.9%
Other values (96) 96
89.7%
2024-04-06T18:42:20.722475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
3.4%
탕 15
 
2.7%
가 13
 
2.4%
주 11
 
2.0%
원 10
 
1.8%
) 9
 
1.6%
식 9
 
1.6%
당 9
 
1.6%
점 9
 
1.6%
삼 8
 
1.5%
Other values (196) 439
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 505
91.7%
Space Separator 19
 
3.4%
Close Punctuation 9
 
1.6%
Open Punctuation 8
 
1.5%
Decimal Number 6
 
1.1%
Other Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 15
 
3.0%
가 13
 
2.6%
주 11
 
2.2%
원 10
 
2.0%
식 9
 
1.8%
당 9
 
1.8%
점 9
 
1.8%
삼 8
 
1.6%
이 8
 
1.6%
어 8
 
1.6%
Other values (187) 405
80.2%
Decimal Number
ValueCountFrequency (%)
5 2
33.3%
0 2
33.3%
1 1
16.7%
4 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 2
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
91.1%
Common 46
 
8.3%
Han 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 15
 
3.0%
가 13
 
2.6%
주 11
 
2.2%
원 10
 
2.0%
식 9
 
1.8%
당 9
 
1.8%
점 9
 
1.8%
삼 8
 
1.6%
이 8
 
1.6%
어 8
 
1.6%
Other values (185) 402
80.1%
Common
ValueCountFrequency (%)
19
41.3%
) 9
19.6%
( 8
17.4%
. 2
 
4.3%
5 2
 
4.3%
0 2
 
4.3%
& 2
 
4.3%
1 1
 
2.2%
4 1
 
2.2%
Han
ValueCountFrequency (%)
愛 2
66.7%
林 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
91.1%
ASCII 46
 
8.3%
CJK 3
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
41.3%
) 9
19.6%
( 8
17.4%
. 2
 
4.3%
5 2
 
4.3%
0 2
 
4.3%
& 2
 
4.3%
1 1
 
2.2%
4 1
 
2.2%
Hangul
ValueCountFrequency (%)
탕 15
 
3.0%
가 13
 
2.6%
주 11
 
2.2%
원 10
 
2.0%
식 9
 
1.8%
당 9
 
1.8%
점 9
 
1.8%
삼 8
 
1.6%
이 8
 
1.6%
어 8
 
1.6%
Other values (185) 402
80.1%
CJK
ValueCountFrequency (%)
愛 2
66.7%
林 1
33.3%

도로명주소
Text

MISSING 

Distinct87
Distinct (%)100.0%
Missing1
Missing (%)1.1%
Memory size836.0 B
2024-04-06T18:42:21.083064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length29.103448
Min length22

Characters and Unicode

Total characters2532
Distinct characters103
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

Unique87 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 주안로 103-18, 10층 (주안동)
2nd row인천광역시 미추홀구 석정로 51, 인천축국전용경기장 가동 (숭의동)
3rd row인천광역시 미추홀구 소성로 184 (학익동)
4th row인천광역시 미추홀구 주염로 9 (주안동)
5th row인천광역시 미추홀구 매소홀로 378 (학익동)
ValueCountFrequency (%)
인천광역시 87
18.6%
미추홀구 87
18.6%
주안동 29
 
6.2%
학익동 16
 
3.4%
용현동 13
 
2.8%
숭의동 11
 
2.4%
매소홀로 9
 
1.9%
미추홀대로 8
 
1.7%
도화동 8
 
1.7%
1층 6
 
1.3%
Other values (155) 194
41.5%
2024-04-06T18:42:21.617232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
381
 
15.0%
홀 109
 
4.3%
인 105
 
4.1%
미 102
 
4.0%
추 99
 
3.9%
) 91
 
3.6%
( 91
 
3.6%
동 89
 
3.5%
천 89
 
3.5%
시 87
 
3.4%
Other values (93) 1289
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1518
60.0%
Decimal Number 389
 
15.4%
Space Separator 381
 
15.0%
Close Punctuation 91
 
3.6%
Open Punctuation 91
 
3.6%
Other Punctuation 48
 
1.9%
Dash Punctuation 11
 
0.4%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홀 109
 
7.2%
인 105
 
6.9%
미 102
 
6.7%
추 99
 
6.5%
동 89
 
5.9%
천 89
 
5.9%
시 87
 
5.7%
역 87
 
5.7%
구 87
 
5.7%
광 87
 
5.7%
Other values (77) 577
38.0%
Decimal Number
ValueCountFrequency (%)
1 85
21.9%
2 46
11.8%
0 45
11.6%
4 41
10.5%
3 38
9.8%
6 33
 
8.5%
7 31
 
8.0%
8 29
 
7.5%
5 25
 
6.4%
9 16
 
4.1%
Space Separator
ValueCountFrequency (%)
381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1518
60.0%
Common 1014
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홀 109
 
7.2%
인 105
 
6.9%
미 102
 
6.7%
추 99
 
6.5%
동 89
 
5.9%
천 89
 
5.9%
시 87
 
5.7%
역 87
 
5.7%
구 87
 
5.7%
광 87
 
5.7%
Other values (77) 577
38.0%
Common
ValueCountFrequency (%)
381
37.6%
) 91
 
9.0%
( 91
 
9.0%
1 85
 
8.4%
, 48
 
4.7%
2 46
 
4.5%
0 45
 
4.4%
4 41
 
4.0%
3 38
 
3.7%
6 33
 
3.3%
Other values (6) 115
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1518
60.0%
ASCII 1014
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
381
37.6%
) 91
 
9.0%
( 91
 
9.0%
1 85
 
8.4%
, 48
 
4.7%
2 46
 
4.5%
0 45
 
4.4%
4 41
 
4.0%
3 38
 
3.7%
6 33
 
3.3%
Other values (6) 115
 
11.3%
Hangul
ValueCountFrequency (%)
홀 109
 
7.2%
인 105
 
6.9%
미 102
 
6.7%
추 99
 
6.5%
동 89
 
5.9%
천 89
 
5.9%
시 87
 
5.7%
역 87
 
5.7%
구 87
 
5.7%
광 87
 
5.7%
Other values (77) 577
38.0%

지번주소
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-04-06T18:42:21.996338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length43
Mean length23.079545
Min length19

Characters and Unicode

Total characters2031
Distinct characters63
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

Unique88 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 주안동 128-9
2nd row인천광역시 미추홀구 숭의동 393-4
3rd row인천광역시 미추홀구 학익동 250-9
4th row인천광역시 미추홀구 문학동 376-4
5th row인천광역시 미추홀구 주안동 24-75
ValueCountFrequency (%)
인천광역시 88
23.3%
미추홀구 88
23.3%
주안동 35
 
9.3%
학익동 18
 
4.8%
용현동 14
 
3.7%
숭의동 11
 
2.9%
도화동 8
 
2.1%
1층 5
 
1.3%
939-19 3
 
0.8%
1필지 2
 
0.5%
Other values (102) 106
28.0%
2024-04-06T18:42:22.621356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
377
18.6%
미 90
 
4.4%
인 89
 
4.4%
광 88
 
4.3%
역 88
 
4.3%
시 88
 
4.3%
추 88
 
4.3%
홀 88
 
4.3%
구 88
 
4.3%
천 88
 
4.3%
Other values (53) 859
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1111
54.7%
Decimal Number 436
 
21.5%
Space Separator 377
 
18.6%
Dash Punctuation 85
 
4.2%
Other Punctuation 14
 
0.7%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 90
 
8.1%
인 89
 
8.0%
광 88
 
7.9%
역 88
 
7.9%
시 88
 
7.9%
추 88
 
7.9%
홀 88
 
7.9%
구 88
 
7.9%
천 88
 
7.9%
동 88
 
7.9%
Other values (38) 228
20.5%
Decimal Number
ValueCountFrequency (%)
1 88
20.2%
2 48
11.0%
6 45
10.3%
3 45
10.3%
9 44
10.1%
4 42
9.6%
0 37
8.5%
7 33
 
7.6%
5 30
 
6.9%
8 24
 
5.5%
Space Separator
ValueCountFrequency (%)
377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1111
54.7%
Common 920
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 90
 
8.1%
인 89
 
8.0%
광 88
 
7.9%
역 88
 
7.9%
시 88
 
7.9%
추 88
 
7.9%
홀 88
 
7.9%
구 88
 
7.9%
천 88
 
7.9%
동 88
 
7.9%
Other values (38) 228
20.5%
Common
ValueCountFrequency (%)
377
41.0%
1 88
 
9.6%
- 85
 
9.2%
2 48
 
5.2%
6 45
 
4.9%
3 45
 
4.9%
9 44
 
4.8%
4 42
 
4.6%
0 37
 
4.0%
7 33
 
3.6%
Other values (5) 76
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1111
54.7%
ASCII 920
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
377
41.0%
1 88
 
9.6%
- 85
 
9.2%
2 48
 
5.2%
6 45
 
4.9%
3 45
 
4.9%
9 44
 
4.8%
4 42
 
4.6%
0 37
 
4.0%
7 33
 
3.6%
Other values (5) 76
 
8.3%
Hangul
ValueCountFrequency (%)
미 90
 
8.1%
인 89
 
8.0%
광 88
 
7.9%
역 88
 
7.9%
시 88
 
7.9%
추 88
 
7.9%
홀 88
 
7.9%
구 88
 
7.9%
천 88
 
7.9%
동 88
 
7.9%
Other values (38) 228
20.5%

전화번호
Text

MISSING 

Distinct84
Distinct (%)98.8%
Missing3
Missing (%)3.4%
Memory size836.0 B
2024-04-06T18:42:22.911067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1020
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

Unique83 ?
Unique (%)97.6%

Sample

1st row032-437-9999
2nd row032-881-5000
3rd row032-867-6161
4th row032-426-7270
5th row032-872-3970
ValueCountFrequency (%)
032-421-4181 2
 
2.4%
032-891-0777 1
 
1.2%
032-766-1320 1
 
1.2%
032-867-6880 1
 
1.2%
032-885-2662 1
 
1.2%
032-885-5009 1
 
1.2%
032-864-2360 1
 
1.2%
032-873-6507 1
 
1.2%
032-866-9045 1
 
1.2%
032-864-9396 1
 
1.2%
Other values (74) 74
87.1%
2024-04-06T18:42:23.300502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 170
16.7%
3 146
14.3%
0 142
13.9%
2 127
12.5%
8 111
10.9%
7 68
 
6.7%
4 66
 
6.5%
6 58
 
5.7%
5 54
 
5.3%
1 44
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 850
83.3%
Dash Punctuation 170
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 146
17.2%
0 142
16.7%
2 127
14.9%
8 111
13.1%
7 68
8.0%
4 66
7.8%
6 58
 
6.8%
5 54
 
6.4%
1 44
 
5.2%
9 34
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 170
16.7%
3 146
14.3%
0 142
13.9%
2 127
12.5%
8 111
10.9%
7 68
 
6.7%
4 66
 
6.5%
6 58
 
5.7%
5 54
 
5.3%
1 44
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 170
16.7%
3 146
14.3%
0 142
13.9%
2 127
12.5%
8 111
10.9%
7 68
 
6.7%
4 66
 
6.5%
6 58
 
5.7%
5 54
 
5.3%
1 44
 
4.3%

위도
Real number (ℝ)

Distinct85
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455172
Minimum37.437488
Maximum37.479891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T18:42:23.479564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437488
5-th percentile37.43928
Q137.447268
median37.458611
Q337.462582
95-th percentile37.466355
Maximum37.479891
Range0.04240303
Interquartile range (IQR)0.015313592

Descriptive statistics

Standard deviation0.009875146
Coefficient of variation (CV)0.0002636524
Kurtosis-0.678542
Mean37.455172
Median Absolute Deviation (MAD)0.005542055
Skewness-0.37684236
Sum3296.0551
Variance9.7518509 × 10-5
MonotonicityNot monotonic
2024-04-06T18:42:23.689089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45956503 3
 
3.4%
37.43978679 2
 
2.3%
37.46266853 1
 
1.1%
37.46427758 1
 
1.1%
37.45888293 1
 
1.1%
37.45727103 1
 
1.1%
37.44241672 1
 
1.1%
37.4491909 1
 
1.1%
37.47491982 1
 
1.1%
37.43795366 1
 
1.1%
Other values (75) 75
85.2%
ValueCountFrequency (%)
37.43748799 1
1.1%
37.43779842 1
1.1%
37.43781801 1
1.1%
37.43795366 1
1.1%
37.4390068 1
1.1%
37.43978679 2
2.3%
37.43988652 1
1.1%
37.44010027 1
1.1%
37.44012573 1
1.1%
37.44014984 1
1.1%
ValueCountFrequency (%)
37.47989102 1
1.1%
37.47491982 1
1.1%
37.46792368 1
1.1%
37.4671443 1
1.1%
37.46640128 1
1.1%
37.46626944 1
1.1%
37.46558683 1
1.1%
37.46547629 1
1.1%
37.46544207 1
1.1%
37.46539379 1
1.1%

경도
Real number (ℝ)

Distinct85
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66784
Minimum126.63305
Maximum126.6933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-04-06T18:42:23.874465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63305
5-th percentile126.63995
Q1126.65321
median126.67177
Q3126.68044
95-th percentile126.68961
Maximum126.6933
Range0.0602479
Interquartile range (IQR)0.0272347

Descriptive statistics

Standard deviation0.016257115
Coefficient of variation (CV)0.00012834446
Kurtosis-0.85691496
Mean126.66784
Median Absolute Deviation (MAD)0.00977775
Skewness-0.54912712
Sum11146.77
Variance0.0002642938
MonotonicityNot monotonic
2024-04-06T18:42:24.081758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6902005 3
 
3.4%
126.6650959 2
 
2.3%
126.6459249 1
 
1.1%
126.6817257 1
 
1.1%
126.6607542 1
 
1.1%
126.6422124 1
 
1.1%
126.6717344 1
 
1.1%
126.6347668 1
 
1.1%
126.668999 1
 
1.1%
126.6624919 1
 
1.1%
Other values (75) 75
85.2%
ValueCountFrequency (%)
126.6330509 1
1.1%
126.633172 1
1.1%
126.6343652 1
1.1%
126.6347668 1
1.1%
126.6398051 1
1.1%
126.6402273 1
1.1%
126.6422124 1
1.1%
126.6422756 1
1.1%
126.6435082 1
1.1%
126.6441745 1
1.1%
ValueCountFrequency (%)
126.6932988 1
 
1.1%
126.6906843 1
 
1.1%
126.6902005 3
3.4%
126.6885125 1
 
1.1%
126.6883476 1
 
1.1%
126.6864207 1
 
1.1%
126.6863433 1
 
1.1%
126.6847833 1
 
1.1%
126.6842409 1
 
1.1%
126.6833198 1
 
1.1%

Interactions

2024-04-06T18:42:19.230419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:18.608731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:18.919695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:19.311964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:18.754615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:19.002446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:19.397716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:18.832799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:42:19.087251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:42:24.245243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명도로명주소지번주소전화번호위도경도
연번1.0001.0001.0001.0000.9380.4350.205
상호명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.000
전화번호0.9381.0001.0001.0001.0000.9800.980
위도0.4351.0001.0001.0000.9801.0000.796
경도0.2051.0001.0001.0000.9800.7961.000
2024-04-06T18:42:24.432033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.326-0.092
위도0.3261.0000.099
경도-0.0920.0991.000

Missing values

2024-04-06T18:42:19.514495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:42:19.625225image/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.
2024-04-06T18:42:19.724080image/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

연번상호명도로명주소지번주소전화번호위도경도
01(주)드림팰리스 뷔페인천광역시 미추홀구 주안로 103-18, 10층 (주안동)인천광역시 미추홀구 주안동 128-9032-437-999937.464576126.681678
12(주)아레나파크컨벤션인천광역시 미추홀구 석정로 51, 인천축국전용경기장 가동 (숭의동)인천광역시 미추홀구 숭의동 393-4032-881-500037.465587126.643508
235.5닭갈비인천광역시 미추홀구 소성로 184 (학익동)인천광역시 미추홀구 학익동 250-9032-867-616137.441025126.668428
34가마솥손두부<NA>인천광역시 미추홀구 문학동 376-4032-426-727037.437488126.68332
45감자탕을 만드는 형제들인천광역시 미추홀구 주염로 9 (주안동)인천광역시 미추홀구 주안동 24-75032-872-397037.466401126.681532
56경복궁학익점(주)엔타스시스템인천광역시 미추홀구 매소홀로 378 (학익동)인천광역시 미추홀구 학익동 689-5032-873-200037.439887126.663823
67고려한방삼계탕인천광역시 미추홀구 인주대로 404 (주안동,,16,13)인천광역시 미추홀구 주안동 1468-24 ,16,13032-431-113337.451055126.68145
78고목정인천광역시 미추홀구 한나루로358번길 7 (학익동)인천광역시 미추홀구 학익동 690-3032-876-697537.440234126.662715
89곤드레愛찬인천광역시 미추홀구 매소홀로 407, 예지빌딩 1층 (학익동)인천광역시 미추홀구 학익동 227-24 외 1필지, 1층032-876-632237.440219126.667247
910굴세상인천광역시 미추홀구 매소홀로 355 (학익동)인천광역시 미추홀구 학익동 209-3032-864-803037.441451126.661976
연번상호명도로명주소지번주소전화번호위도경도
7879태원인천광역시 미추홀구 매소홀로 388, 2층 204호 (학익동)인천광역시 미추홀구 학익동 684-1032-862-080637.439787126.665096
7980풍전식당인천광역시 미추홀구 제일로 41 (도화동)인천광역시 미추홀구 도화동 442-5032-866-871037.45904126.67479
8081하림인천광역시 미추홀구 주안서로 51 (주안동,1층)인천광역시 미추홀구 주안동 272-3 1층032-868-370037.463345126.67754
8182한우 평인천광역시 미추홀구 석정로 496, 1,2층 (주안동)인천광역시 미추홀구 주안동 35-2032-442-077437.465476126.690684
8283한우마을인천광역시 미추홀구 인주대로 448 (주안동)인천광역시 미추홀구 주안동 1517-2032-423-807437.45056126.686343
8384함흥관인천광역시 미추홀구 인중로 1, 1~3층 (숭의동)인천광역시 미추홀구 숭의동 342-1032-889-400437.462031126.642276
8485해바라기 정육식당인천광역시 미추홀구 주안로 77 (주안동)인천광역시 미추홀구 주안동 239-2032-421-418137.46436126.678276
8586홍콩반점 0410인천광역시 미추홀구 미추홀대로734번길 17, 수창빌딩 2층 (주안동)인천광역시 미추홀구 주안동 138-4 수창빌딩 2층032-433-785337.463106126.681445
8687화진원인천광역시 미추홀구 인주대로128번길 30 (용현동)인천광역시 미추홀구 용현동 450-160032-763-181837.454984126.651119
8788황성얼큰오징어찌개인천광역시 미추홀구 아암대로107번길 13 (용현동)인천광역시 미추홀구 용현동 630-27032-888-455737.452233126.633051