Overview

Dataset statistics

Number of variables9
Number of observations5926
Missing cells3101
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory422.6 KiB
Average record size in memory73.0 B

Variable types

Numeric1
Categorical2
Text3
DateTime3

Dataset

Description인천 광역시 서구 관내에 위치한 일반음식점 신고현황 (업종명, 업소명, 인허가일지, 소재지(도로명,지번), 전화번호, 영업자 시작, 지위승계)현행 데이터 입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089644&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 3082 (52.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 19:02:33.803368
Analysis finished2024-04-17 19:02:35.570320
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct5926
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2963.5
Minimum1
Maximum5926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.2 KiB
2024-04-18T04:02:35.624843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile297.25
Q11482.25
median2963.5
Q34444.75
95-th percentile5629.75
Maximum5926
Range5925
Interquartile range (IQR)2962.5

Descriptive statistics

Standard deviation1710.8332
Coefficient of variation (CV)0.57730156
Kurtosis-1.2
Mean2963.5
Median Absolute Deviation (MAD)1481.5
Skewness0
Sum17561701
Variance2926950.2
MonotonicityStrictly increasing
2024-04-18T04:02:35.730849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3949 1
 
< 0.1%
3958 1
 
< 0.1%
3957 1
 
< 0.1%
3956 1
 
< 0.1%
3955 1
 
< 0.1%
3954 1
 
< 0.1%
3953 1
 
< 0.1%
3952 1
 
< 0.1%
3951 1
 
< 0.1%
Other values (5916) 5916
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
5926 1
< 0.1%
5925 1
< 0.1%
5924 1
< 0.1%
5923 1
< 0.1%
5922 1
< 0.1%
5921 1
< 0.1%
5920 1
< 0.1%
5919 1
< 0.1%
5918 1
< 0.1%
5917 1
< 0.1%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
일반음식점
5926 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 5926
100.0%

Length

2024-04-18T04:02:35.834816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:35.909436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 5926
100.0%

업소명
Text

Distinct5599
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
2024-04-18T04:02:36.104712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length6.9454944
Min length1

Characters and Unicode

Total characters41159
Distinct characters1004
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5383 ?
Unique (%)90.8%

Sample

1st row예전
2nd row일미정
3rd row드럼통숯불구이
4th row효정통닭
5th row성원닭갈비식당
ValueCountFrequency (%)
청라점 151
 
2.0%
검단신도시점 85
 
1.1%
검단점 66
 
0.9%
루원시티점 41
 
0.5%
인천청라점 31
 
0.4%
가좌점 23
 
0.3%
검암점 22
 
0.3%
석남점 21
 
0.3%
검단아라점 21
 
0.3%
김밥천국 20
 
0.3%
Other values (5837) 7110
93.7%
2024-04-18T04:02:36.451568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1666
 
4.0%
점 1542
 
3.7%
라 814
 
2.0%
이 756
 
1.8%
청 575
 
1.4%
리 510
 
1.2%
스 489
 
1.2%
식 468
 
1.1%
천 461
 
1.1%
시 453
 
1.1%
Other values (994) 33425
81.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36344
88.3%
Space Separator 1666
 
4.0%
Uppercase Letter 1000
 
2.4%
Lowercase Letter 650
 
1.6%
Decimal Number 513
 
1.2%
Close Punctuation 394
 
1.0%
Open Punctuation 394
 
1.0%
Other Punctuation 189
 
0.5%
Dash Punctuation 6
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1542
 
4.2%
라 814
 
2.2%
이 756
 
2.1%
청 575
 
1.6%
리 510
 
1.4%
스 489
 
1.3%
식 468
 
1.3%
천 461
 
1.3%
시 453
 
1.2%
가 452
 
1.2%
Other values (915) 29824
82.1%
Uppercase Letter
ValueCountFrequency (%)
O 88
 
8.8%
E 85
 
8.5%
B 83
 
8.3%
C 80
 
8.0%
A 66
 
6.6%
H 48
 
4.8%
T 47
 
4.7%
S 47
 
4.7%
N 44
 
4.4%
F 42
 
4.2%
Other values (16) 370
37.0%
Lowercase Letter
ValueCountFrequency (%)
e 87
13.4%
o 59
 
9.1%
a 57
 
8.8%
s 46
 
7.1%
c 42
 
6.5%
i 41
 
6.3%
n 38
 
5.8%
t 38
 
5.8%
r 30
 
4.6%
f 28
 
4.3%
Other values (16) 184
28.3%
Decimal Number
ValueCountFrequency (%)
1 116
22.6%
2 87
17.0%
0 73
14.2%
9 54
10.5%
3 38
 
7.4%
8 37
 
7.2%
7 36
 
7.0%
4 29
 
5.7%
5 22
 
4.3%
6 21
 
4.1%
Other Punctuation
ValueCountFrequency (%)
& 109
57.7%
. 30
 
15.9%
, 24
 
12.7%
' 9
 
4.8%
· 7
 
3.7%
: 4
 
2.1%
# 3
 
1.6%
? 1
 
0.5%
! 1
 
0.5%
; 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
1666
100.0%
Close Punctuation
ValueCountFrequency (%)
) 394
100.0%
Open Punctuation
ValueCountFrequency (%)
( 394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36309
88.2%
Common 3164
 
7.7%
Latin 1651
 
4.0%
Han 33
 
0.1%
Hiragana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1542
 
4.2%
라 814
 
2.2%
이 756
 
2.1%
청 575
 
1.6%
리 510
 
1.4%
스 489
 
1.3%
식 468
 
1.3%
천 461
 
1.3%
시 453
 
1.2%
가 452
 
1.2%
Other values (882) 29789
82.0%
Latin
ValueCountFrequency (%)
O 88
 
5.3%
e 87
 
5.3%
E 85
 
5.1%
B 83
 
5.0%
C 80
 
4.8%
A 66
 
4.0%
o 59
 
3.6%
a 57
 
3.5%
H 48
 
2.9%
T 47
 
2.8%
Other values (43) 951
57.6%
Han
ValueCountFrequency (%)
家 2
 
6.1%
酒 2
 
6.1%
好 1
 
3.0%
大 1
 
3.0%
沅 1
 
3.0%
鼎 1
 
3.0%
忠 1
 
3.0%
里 1
 
3.0%
香 1
 
3.0%
万 1
 
3.0%
Other values (21) 21
63.6%
Common
ValueCountFrequency (%)
1666
52.7%
) 394
 
12.5%
( 394
 
12.5%
1 116
 
3.7%
& 109
 
3.4%
2 87
 
2.7%
0 73
 
2.3%
9 54
 
1.7%
3 38
 
1.2%
8 37
 
1.2%
Other values (16) 196
 
6.2%
Hiragana
ValueCountFrequency (%)
び 1
50.0%
お 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36309
88.2%
ASCII 4807
 
11.7%
CJK 32
 
0.1%
None 7
 
< 0.1%
Hiragana 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1666
34.7%
) 394
 
8.2%
( 394
 
8.2%
1 116
 
2.4%
& 109
 
2.3%
O 88
 
1.8%
e 87
 
1.8%
2 87
 
1.8%
E 85
 
1.8%
B 83
 
1.7%
Other values (67) 1698
35.3%
Hangul
ValueCountFrequency (%)
점 1542
 
4.2%
라 814
 
2.2%
이 756
 
2.1%
청 575
 
1.6%
리 510
 
1.4%
스 489
 
1.3%
식 468
 
1.3%
천 461
 
1.3%
시 453
 
1.2%
가 452
 
1.2%
Other values (882) 29789
82.0%
None
ValueCountFrequency (%)
· 7
100.0%
CJK
ValueCountFrequency (%)
家 2
 
6.2%
酒 2
 
6.2%
好 1
 
3.1%
大 1
 
3.1%
沅 1
 
3.1%
鼎 1
 
3.1%
忠 1
 
3.1%
里 1
 
3.1%
香 1
 
3.1%
万 1
 
3.1%
Other values (20) 20
62.5%
Hiragana
ValueCountFrequency (%)
び 1
50.0%
お 1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
串 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

인허가일자
Date

Distinct3314
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
Minimum1972-02-12 00:00:00
Maximum2023-12-29 00:00:00
2024-04-18T04:02:36.561492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:02:36.672029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지(도로명)
Text

Distinct5723
Distinct (%)96.9%
Missing19
Missing (%)0.3%
Memory size46.4 KiB
2024-04-18T04:02:36.889062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length69
Mean length35.454207
Min length20

Characters and Unicode

Total characters209428
Distinct characters462
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5570 ?
Unique (%)94.3%

Sample

1st row인천광역시 서구 가정로98번길 9-4 (가좌동)
2nd row인천광역시 서구 방축로 335 (가좌동)
3rd row인천광역시 서구 길주로75번길 1 (석남동)
4th row인천광역시 서구 가정로126번길 16 (가좌동)
5th row인천광역시 서구 가정로98번길 6 (가좌동)
ValueCountFrequency (%)
인천광역시 5907
 
14.6%
서구 5907
 
14.6%
1층 1633
 
4.0%
청라동 975
 
2.4%
석남동 694
 
1.7%
일부호 558
 
1.4%
가정동 535
 
1.3%
가좌동 521
 
1.3%
마전동 400
 
1.0%
원당동 395
 
1.0%
Other values (4023) 22918
56.7%
2024-04-18T04:02:37.243117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34554
 
16.5%
1 11524
 
5.5%
, 7069
 
3.4%
동 6693
 
3.2%
서 6451
 
3.1%
시 6222
 
3.0%
로 6140
 
2.9%
) 6137
 
2.9%
( 6137
 
2.9%
인 6022
 
2.9%
Other values (452) 112479
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113354
54.1%
Decimal Number 39196
 
18.7%
Space Separator 34554
 
16.5%
Other Punctuation 7130
 
3.4%
Close Punctuation 6139
 
2.9%
Open Punctuation 6139
 
2.9%
Dash Punctuation 1440
 
0.7%
Uppercase Letter 1105
 
0.5%
Lowercase Letter 312
 
0.1%
Math Symbol 44
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6693
 
5.9%
서 6451
 
5.7%
시 6222
 
5.5%
로 6140
 
5.4%
인 6022
 
5.3%
천 6007
 
5.3%
광 5945
 
5.2%
역 5932
 
5.2%
구 5925
 
5.2%
호 4004
 
3.5%
Other values (399) 54013
47.6%
Uppercase Letter
ValueCountFrequency (%)
B 417
37.7%
A 156
 
14.1%
K 73
 
6.6%
S 71
 
6.4%
E 54
 
4.9%
W 52
 
4.7%
I 51
 
4.6%
V 49
 
4.4%
L 49
 
4.4%
M 42
 
3.8%
Other values (10) 91
 
8.2%
Decimal Number
ValueCountFrequency (%)
1 11524
29.4%
2 5443
13.9%
0 4964
12.7%
3 3257
 
8.3%
4 2820
 
7.2%
5 2559
 
6.5%
6 2267
 
5.8%
7 2233
 
5.7%
8 2158
 
5.5%
9 1971
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 102
32.7%
s 56
17.9%
a 49
15.7%
r 48
15.4%
d 48
15.4%
c 3
 
1.0%
b 3
 
1.0%
n 1
 
0.3%
p 1
 
0.3%
k 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 7069
99.1%
' 49
 
0.7%
. 7
 
0.1%
& 3
 
< 0.1%
* 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6137
> 99.9%
] 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6137
> 99.9%
[ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
34554
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1440
100.0%
Math Symbol
ValueCountFrequency (%)
~ 44
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113353
54.1%
Common 94642
45.2%
Latin 1432
 
0.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6693
 
5.9%
서 6451
 
5.7%
시 6222
 
5.5%
로 6140
 
5.4%
인 6022
 
5.3%
천 6007
 
5.3%
광 5945
 
5.2%
역 5932
 
5.2%
구 5925
 
5.2%
호 4004
 
3.5%
Other values (398) 54012
47.6%
Latin
ValueCountFrequency (%)
B 417
29.1%
A 156
 
10.9%
e 102
 
7.1%
K 73
 
5.1%
S 71
 
5.0%
s 56
 
3.9%
E 54
 
3.8%
W 52
 
3.6%
I 51
 
3.6%
V 49
 
3.4%
Other values (21) 351
24.5%
Common
ValueCountFrequency (%)
34554
36.5%
1 11524
 
12.2%
, 7069
 
7.5%
) 6137
 
6.5%
( 6137
 
6.5%
2 5443
 
5.8%
0 4964
 
5.2%
3 3257
 
3.4%
4 2820
 
3.0%
5 2559
 
2.7%
Other values (12) 10178
 
10.8%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113298
54.1%
ASCII 96059
45.9%
Compat Jamo 55
 
< 0.1%
Number Forms 15
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34554
36.0%
1 11524
 
12.0%
, 7069
 
7.4%
) 6137
 
6.4%
( 6137
 
6.4%
2 5443
 
5.7%
0 4964
 
5.2%
3 3257
 
3.4%
4 2820
 
2.9%
5 2559
 
2.7%
Other values (42) 11595
 
12.1%
Hangul
ValueCountFrequency (%)
동 6693
 
5.9%
서 6451
 
5.7%
시 6222
 
5.5%
로 6140
 
5.4%
인 6022
 
5.3%
천 6007
 
5.3%
광 5945
 
5.2%
역 5932
 
5.2%
구 5925
 
5.2%
호 4004
 
3.5%
Other values (397) 53957
47.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 55
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 15
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

소재지전화
Text

MISSING 

Distinct2805
Distinct (%)98.6%
Missing3082
Missing (%)52.0%
Memory size46.4 KiB
2024-04-18T04:02:37.525630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.981716
Min length3

Characters and Unicode

Total characters39764
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

Unique2776 ?
Unique (%)97.6%

Sample

1st row032 -584 -4661
2nd row 032- 577-7932
3rd row032 -576 -0521
4th row 032- 572-9331
5th row 032- 582-4069
ValueCountFrequency (%)
032 2675
36.9%
566 137
 
1.9%
562 122
 
1.7%
565 119
 
1.6%
561 112
 
1.5%
567 108
 
1.5%
568 100
 
1.4%
563 93
 
1.3%
564 88
 
1.2%
577 82
 
1.1%
Other values (2702) 3606
49.8%
2024-04-18T04:02:37.901948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5688
14.3%
5541
13.9%
2 4608
11.6%
0 4317
10.9%
3 4194
10.5%
5 4169
10.5%
6 2836
7.1%
7 2414
6.1%
8 1842
 
4.6%
9 1507
 
3.8%
Other values (2) 2648
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28535
71.8%
Dash Punctuation 5688
 
14.3%
Space Separator 5541
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4608
16.1%
0 4317
15.1%
3 4194
14.7%
5 4169
14.6%
6 2836
9.9%
7 2414
8.5%
8 1842
 
6.5%
9 1507
 
5.3%
1 1474
 
5.2%
4 1174
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 5688
100.0%
Space Separator
ValueCountFrequency (%)
5541
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39764
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5688
14.3%
5541
13.9%
2 4608
11.6%
0 4317
10.9%
3 4194
10.5%
5 4169
10.5%
6 2836
7.1%
7 2414
6.1%
8 1842
 
4.6%
9 1507
 
3.8%
Other values (2) 2648
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5688
14.3%
5541
13.9%
2 4608
11.6%
0 4317
10.9%
3 4194
10.5%
5 4169
10.5%
6 2836
7.1%
7 2414
6.1%
8 1842
 
4.6%
9 1507
 
3.8%
Other values (2) 2648
6.7%

영업자시작일
Date

Distinct2393
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
Minimum1981-11-12 00:00:00
Maximum2024-01-15 00:00:00
2024-04-18T04:02:38.021122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:02:38.132875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지위승계 여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
승계
3068 
신규
2858 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승계
2nd row승계
3rd row승계
4th row신규
5th row승계

Common Values

ValueCountFrequency (%)
승계 3068
51.8%
신규 2858
48.2%

Length

2024-04-18T04:02:38.229843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:38.301643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승계 3068
51.8%
신규 2858
48.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.4 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-04-18T04:02:38.362471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:02:38.442116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T04:02:35.187371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T04:02:38.509518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지위승계 여부
연번1.0000.273
지위승계 여부0.2731.000
2024-04-18T04:02:38.576313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지위승계 여부
연번1.0000.209
지위승계 여부0.2091.000

Missing values

2024-04-18T04:02:35.322995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T04:02:35.441311image/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.
2024-04-18T04:02:35.529789image/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

연번업종명업소명인허가일자소재지(도로명)소재지전화영업자시작일지위승계 여부데이터기준일
01일반음식점예전1974-06-30인천광역시 서구 가정로98번길 9-4 (가좌동)032 -584 -46612006-03-30승계2023-12-31
12일반음식점일미정1980-09-04인천광역시 서구 방축로 335 (가좌동)032- 577-79322010-04-22승계2023-12-31
23일반음식점드럼통숯불구이1980-10-29인천광역시 서구 길주로75번길 1 (석남동)<NA>2006-06-15승계2023-12-31
34일반음식점효정통닭1981-11-12인천광역시 서구 가정로126번길 16 (가좌동)032 -576 -05211981-11-12신규2023-12-31
45일반음식점성원닭갈비식당1983-08-27인천광역시 서구 가정로98번길 6 (가좌동)032- 572-93311993-04-02승계2023-12-31
56일반음식점본죽1984-05-14인천광역시 서구 가정로 187 (석남동)032- 582-40692007-05-07승계2023-12-31
67일반음식점여명1985-09-02인천광역시 서구 염곡로 349 (신현동)032- 579-87291997-03-18승계2023-12-31
78일반음식점신태양식당1985-09-16인천광역시 서구 건지로 273 (석남동)032 -573 -78191989-05-24승계2023-12-31
89일반음식점의정부식당1985-12-21인천광역시 서구 원적로27번길 19-2 (가좌동)<NA>1985-12-21신규2023-12-31
910일반음식점백령면옥1986-09-10인천광역시 서구 서곶로255번길 4 (심곡동)032- 561-33622004-04-08승계2023-12-31
연번업종명업소명인허가일자소재지(도로명)소재지전화영업자시작일지위승계 여부데이터기준일
59165917일반음식점맛찜랭킹 청라점2023-12-22인천광역시 서구 청라커낼로288번길 26, 현대썬앤빌 더 테라스 1층 145호 (청라동)<NA>2023-12-22신규2023-12-31
59175918일반음식점6단지부대찌개2023-12-26인천광역시 서구 청라한내로100번길 8-28, 청라레이크봄 129호 (청라동)<NA>2023-12-26신규2023-12-31
59185919일반음식점강남다방2023-12-26인천광역시 서구 가정로 294, 지하1층 (석남동)<NA>2023-12-26신규2023-12-31
59195920일반음식점크레이지92 가정직영점2023-12-26인천광역시 서구 석곶로 17, 2층 일부호 (가정동)<NA>2023-12-26신규2023-12-31
59205921일반음식점백리향2023-12-27인천광역시 서구 한중1로 14, 센트럴빌딩 2층 203호 (백석동)<NA>2023-12-27신규2023-12-31
59215922일반음식점로뎀 도시락.반찬2023-12-27인천광역시 서구 이음대로 378, 로뎀타워 120호 (원당동)<NA>2023-12-27신규2023-12-31
59225923일반음식점장미막창 석남점2023-12-28인천광역시 서구 석남로 98, 1층 일부호 (석남동)<NA>2023-12-28신규2023-12-31
59235924일반음식점대림한식뷔페2023-12-28인천광역시 서구 이음1로 389, A플러스 타워 301,302,303호 (원당동)<NA>2023-12-28신규2023-12-31
59245925일반음식점스텔라떡볶이 인천청라점2023-12-29인천광역시 서구 청라커낼로 300, 판매3동 103호 (청라동, 청라센트럴에일린의뜰)<NA>2023-12-29신규2023-12-31
59255926일반음식점어나더플러스2023-12-29인천광역시 서구 건지로334번길 18, 1층 일부호 (가좌동)<NA>2023-12-29신규2023-12-31