Overview

Dataset statistics

Number of variables8
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory68.5 B

Variable types

Numeric2
Text4
Categorical2

Dataset

Description부산진구내 식당환경,서비스,좋은식단이행 등 우수한 음식점 지정 현황(업종명, 업소명, 소재지 주소, 소재지 전화번호 등을 제공합니다.)
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15055847/fileData.do

Alerts

연번 has unique valuesUnique
소재지(도로명) has unique valuesUnique
면적(제곱미터) has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:00:42.393485
Analysis finished2023-12-12 14:00:43.423647
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T23:00:43.500030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-12-12T23:00:43.664024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

업소명
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T23:00:43.886743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5
Min length2

Characters and Unicode

Total characters260
Distinct characters141
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)96.2%

Sample

1st row세연정
2nd row강원삼계탕
3rd row일품정가
4th row공감식당
5th row백양돼지국밥
ValueCountFrequency (%)
대서양식당 2
 
3.5%
외식일번가 1
 
1.8%
다원정 1
 
1.8%
정동진해물탕해물찜 1
 
1.8%
급행장 1
 
1.8%
도마위에 1
 
1.8%
암소 1
 
1.8%
춘하추동밀면 1
 
1.8%
용궁해물탕 1
 
1.8%
동해물회 1
 
1.8%
Other values (46) 46
80.7%
2023-12-12T23:00:44.264885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 8
 
3.1%
가 7
 
2.7%
정 7
 
2.7%
6
 
2.3%
탕 6
 
2.3%
일 5
 
1.9%
밥 5
 
1.9%
당 5
 
1.9%
양 5
 
1.9%
해 5
 
1.9%
Other values (131) 201
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 251
96.5%
Space Separator 6
 
2.3%
Uppercase Letter 1
 
0.4%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 8
 
3.2%
가 7
 
2.8%
정 7
 
2.8%
탕 6
 
2.4%
일 5
 
2.0%
밥 5
 
2.0%
당 5
 
2.0%
양 5
 
2.0%
해 5
 
2.0%
점 5
 
2.0%
Other values (127) 193
76.9%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 251
96.5%
Common 8
 
3.1%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 8
 
3.2%
가 7
 
2.8%
정 7
 
2.8%
탕 6
 
2.4%
일 5
 
2.0%
밥 5
 
2.0%
당 5
 
2.0%
양 5
 
2.0%
해 5
 
2.0%
점 5
 
2.0%
Other values (127) 193
76.9%
Common
ValueCountFrequency (%)
6
75.0%
) 1
 
12.5%
( 1
 
12.5%
Latin
ValueCountFrequency (%)
S 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 251
96.5%
ASCII 9
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 8
 
3.2%
가 7
 
2.8%
정 7
 
2.8%
탕 6
 
2.4%
일 5
 
2.0%
밥 5
 
2.0%
당 5
 
2.0%
양 5
 
2.0%
해 5
 
2.0%
점 5
 
2.0%
Other values (127) 193
76.9%
ASCII
ValueCountFrequency (%)
6
66.7%
S 1
 
11.1%
) 1
 
11.1%
( 1
 
11.1%

동별
Categorical

Distinct9
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size548.0 B
부전동
30 
당감동
5 
부암동
4 
전포동
4 
양정동
 
3
Other values (4)
6 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)5.8%

Sample

1st row가야동
2nd row개금동
3rd row당감동
4th row당감동
5th row당감동

Common Values

ValueCountFrequency (%)
부전동 30
57.7%
당감동 5
 
9.6%
부암동 4
 
7.7%
전포동 4
 
7.7%
양정동 3
 
5.8%
초읍동 3
 
5.8%
가야동 1
 
1.9%
개금동 1
 
1.9%
범천동 1
 
1.9%

Length

2023-12-12T23:00:44.439259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:00:44.541519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부전동 30
57.7%
당감동 5
 
9.6%
부암동 4
 
7.7%
전포동 4
 
7.7%
양정동 3
 
5.8%
초읍동 3
 
5.8%
가야동 1
 
1.9%
개금동 1
 
1.9%
범천동 1
 
1.9%

소재지(도로명)
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T23:00:44.767007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length29
Mean length19.538462
Min length12

Characters and Unicode

Total characters1016
Distinct characters99
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row 가야대로 554, 1층 (가야동)
2nd row 개금온정로 10 (개금동,796-1개금롯데캐슬상가2동제지1층 B117,B118,B119)
3rd row 가야대로703번길 25 (당감동)
4th row 동평로 81, 1층 (당감동)
5th row 백양관문로 84 (당감동)
ValueCountFrequency (%)
부전동 24
 
14.5%
서면문화로 10
 
6.0%
당감동 4
 
2.4%
부암동 4
 
2.4%
1층 3
 
1.8%
52 3
 
1.8%
초읍동 3
 
1.8%
부전로96번길 3
 
1.8%
전포동 3
 
1.8%
25 3
 
1.8%
Other values (96) 106
63.9%
2023-12-12T23:00:45.168057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
 
15.0%
동 60
 
5.9%
) 58
 
5.7%
( 58
 
5.7%
로 51
 
5.0%
1 50
 
4.9%
전 45
 
4.4%
부 41
 
4.0%
2 39
 
3.8%
, 28
 
2.8%
Other values (89) 434
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 485
47.7%
Decimal Number 221
21.8%
Space Separator 152
 
15.0%
Close Punctuation 58
 
5.7%
Open Punctuation 58
 
5.7%
Other Punctuation 29
 
2.9%
Dash Punctuation 8
 
0.8%
Uppercase Letter 3
 
0.3%
Lowercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 60
 
12.4%
로 51
 
10.5%
전 45
 
9.3%
부 41
 
8.5%
길 24
 
4.9%
번 23
 
4.7%
서 16
 
3.3%
층 15
 
3.1%
대 14
 
2.9%
문 13
 
2.7%
Other values (70) 183
37.7%
Decimal Number
ValueCountFrequency (%)
1 50
22.6%
2 39
17.6%
6 22
10.0%
5 19
 
8.6%
4 17
 
7.7%
9 17
 
7.7%
7 15
 
6.8%
0 14
 
6.3%
3 14
 
6.3%
8 14
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 28
96.6%
. 1
 
3.4%
Space Separator
ValueCountFrequency (%)
152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 527
51.9%
Hangul 485
47.7%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 60
 
12.4%
로 51
 
10.5%
전 45
 
9.3%
부 41
 
8.5%
길 24
 
4.9%
번 23
 
4.7%
서 16
 
3.3%
층 15
 
3.1%
대 14
 
2.9%
문 13
 
2.7%
Other values (70) 183
37.7%
Common
ValueCountFrequency (%)
152
28.8%
) 58
 
11.0%
( 58
 
11.0%
1 50
 
9.5%
2 39
 
7.4%
, 28
 
5.3%
6 22
 
4.2%
5 19
 
3.6%
4 17
 
3.2%
9 17
 
3.2%
Other values (7) 67
12.7%
Latin
ValueCountFrequency (%)
B 3
75.0%
c 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 531
52.3%
Hangul 485
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
28.6%
) 58
 
10.9%
( 58
 
10.9%
1 50
 
9.4%
2 39
 
7.3%
, 28
 
5.3%
6 22
 
4.1%
5 19
 
3.6%
4 17
 
3.2%
9 17
 
3.2%
Other values (9) 71
13.4%
Hangul
ValueCountFrequency (%)
동 60
 
12.4%
로 51
 
10.5%
전 45
 
9.3%
부 41
 
8.5%
길 24
 
4.9%
번 23
 
4.7%
서 16
 
3.3%
층 15
 
3.1%
대 14
 
2.9%
문 13
 
2.7%
Other values (70) 183
37.7%

음식의유형
Categorical

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
한식
37 
일식
5 
중식
4 
분식
 
2
생선회
 
2

Length

Max length3
Median length2
Mean length2.0384615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 37
71.2%
일식 5
 
9.6%
중식 4
 
7.7%
분식 2
 
3.8%
생선회 2
 
3.8%
뷔페 2
 
3.8%

Length

2023-12-12T23:00:45.299656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:00:45.419575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 37
71.2%
일식 5
 
9.6%
중식 4
 
7.7%
분식 2
 
3.8%
생선회 2
 
3.8%
뷔페 2
 
3.8%

주된음식
Text

Distinct45
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T23:00:45.622492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length4.6923077
Min length2

Characters and Unicode

Total characters244
Distinct characters79
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)73.1%

Sample

1st row오리고기
2nd row삼계탕,곰탕류
3rd row삼겹살
4th row삼겹살
5th row돼지국밥
ValueCountFrequency (%)
삼겹살 3
 
5.5%
중화요리 2
 
3.6%
참치회 2
 
3.6%
일식요리 2
 
3.6%
뷔페 2
 
3.6%
생선회 2
 
3.6%
생선회,초밥 2
 
3.6%
복국 1
 
1.8%
오리고기 1
 
1.8%
재첩국 1
 
1.8%
Other values (37) 37
67.3%
2023-12-12T23:00:45.976079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 19
 
7.8%
비 13
 
5.3%
갈 12
 
4.9%
탕 11
 
4.5%
밥 8
 
3.3%
삼 8
 
3.3%
생 8
 
3.3%
회 7
 
2.9%
리 6
 
2.5%
겹 6
 
2.5%
Other values (69) 146
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
91.0%
Other Punctuation 19
 
7.8%
Space Separator 3
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 13
 
5.9%
갈 12
 
5.4%
탕 11
 
5.0%
밥 8
 
3.6%
삼 8
 
3.6%
생 8
 
3.6%
회 7
 
3.2%
리 6
 
2.7%
겹 6
 
2.7%
살 6
 
2.7%
Other values (67) 137
61.7%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
91.0%
Common 22
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 13
 
5.9%
갈 12
 
5.4%
탕 11
 
5.0%
밥 8
 
3.6%
삼 8
 
3.6%
생 8
 
3.6%
회 7
 
3.2%
리 6
 
2.7%
겹 6
 
2.7%
살 6
 
2.7%
Other values (67) 137
61.7%
Common
ValueCountFrequency (%)
, 19
86.4%
3
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
91.0%
ASCII 22
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 19
86.4%
3
 
13.6%
Hangul
ValueCountFrequency (%)
비 13
 
5.9%
갈 12
 
5.4%
탕 11
 
5.0%
밥 8
 
3.6%
삼 8
 
3.6%
생 8
 
3.6%
회 7
 
3.2%
리 6
 
2.7%
겹 6
 
2.7%
살 6
 
2.7%
Other values (67) 137
61.7%

면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365.18885
Minimum42.32
Maximum4808.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T23:00:46.153497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.32
5-th percentile59.5575
Q1107.485
median173.84
Q3298.6825
95-th percentile881.0175
Maximum4808.49
Range4766.17
Interquartile range (IQR)191.1975

Descriptive statistics

Standard deviation718.55275
Coefficient of variation (CV)1.9676197
Kurtosis30.143518
Mean365.18885
Median Absolute Deviation (MAD)88.015
Skewness5.1879971
Sum18989.82
Variance516318.06
MonotonicityNot monotonic
2023-12-12T23:00:46.377881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
522.52 1
 
1.9%
320.4 1
 
1.9%
716.04 1
 
1.9%
163.68 1
 
1.9%
193.15 1
 
1.9%
242.52 1
 
1.9%
142.83 1
 
1.9%
124.0 1
 
1.9%
88.6 1
 
1.9%
2251.2 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
42.32 1
1.9%
54.34 1
1.9%
56.12 1
1.9%
62.37 1
1.9%
62.9 1
1.9%
68.3 1
1.9%
74.6 1
1.9%
75.89 1
1.9%
85.71 1
1.9%
85.77 1
1.9%
ValueCountFrequency (%)
4808.49 1
1.9%
2251.2 1
1.9%
995.06 1
1.9%
787.71 1
1.9%
769.06 1
1.9%
716.04 1
1.9%
688.97 1
1.9%
522.52 1
1.9%
410.0 1
1.9%
335.15 1
1.9%

전화번호
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T23:00:46.709040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters624
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

Unique52 ?
Unique (%)100.0%

Sample

1st row051-867-2000
2nd row051-502-9116
3rd row051-891-9136
4th row051-891-2041
5th row051-898-0505
ValueCountFrequency (%)
051-867-2000 1
 
1.9%
051-502-9116 1
 
1.9%
051-806-1585 1
 
1.9%
051-805-6290 1
 
1.9%
051-809-8208 1
 
1.9%
051-809-2100 1
 
1.9%
051-805-0073 1
 
1.9%
051-809-8659 1
 
1.9%
051-808-4711 1
 
1.9%
051-809-3305 1
 
1.9%
Other values (42) 42
80.8%
2023-12-12T23:00:47.148607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137
22.0%
- 104
16.7%
8 82
13.1%
1 81
13.0%
5 79
12.7%
9 34
 
5.4%
6 29
 
4.6%
7 25
 
4.0%
3 25
 
4.0%
2 19
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137
26.3%
8 82
15.8%
1 81
15.6%
5 79
15.2%
9 34
 
6.5%
6 29
 
5.6%
7 25
 
4.8%
3 25
 
4.8%
2 19
 
3.7%
4 9
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 137
22.0%
- 104
16.7%
8 82
13.1%
1 81
13.0%
5 79
12.7%
9 34
 
5.4%
6 29
 
4.6%
7 25
 
4.0%
3 25
 
4.0%
2 19
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137
22.0%
- 104
16.7%
8 82
13.1%
1 81
13.0%
5 79
12.7%
9 34
 
5.4%
6 29
 
4.6%
7 25
 
4.0%
3 25
 
4.0%
2 19
 
3.0%

Interactions

2023-12-12T23:00:43.045218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:42.881445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:43.121870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:00:42.965701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:00:47.281227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명동별소재지(도로명)음식의유형주된음식면적(제곱미터)전화번호
연번1.0001.0000.7831.0000.5070.8750.1241.000
업소명1.0001.0001.0001.0001.0001.0001.0001.000
동별0.7831.0001.0001.0000.0000.9770.0761.000
소재지(도로명)1.0001.0001.0001.0001.0001.0001.0001.000
음식의유형0.5071.0000.0001.0001.0000.9900.4921.000
주된음식0.8751.0000.9771.0000.9901.0000.0001.000
면적(제곱미터)0.1241.0000.0761.0000.4920.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T23:00:47.416824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별음식의유형
동별1.0000.000
음식의유형0.0001.000
2023-12-12T23:00:47.543460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)동별음식의유형
연번1.0000.0660.4970.277
면적(제곱미터)0.0661.0000.0000.329
동별0.4970.0001.0000.000
음식의유형0.2770.3290.0001.000

Missing values

2023-12-12T23:00:43.234933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:00:43.376194image/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

연번업소명동별소재지(도로명)음식의유형주된음식면적(제곱미터)전화번호
01세연정가야동가야대로 554, 1층 (가야동)한식오리고기522.52051-867-2000
12강원삼계탕개금동개금온정로 10 (개금동,796-1개금롯데캐슬상가2동제지1층 B117,B118,B119)한식삼계탕,곰탕류238.61051-502-9116
23일품정가당감동가야대로703번길 25 (당감동)한식삼겹살135.52051-891-9136
34공감식당당감동동평로 81, 1층 (당감동)한식삼겹살123.12051-891-2041
45백양돼지국밥당감동백양관문로 84 (당감동)한식돼지국밥194.9051-898-0505
56진가네추어탕당감동백양순환로 9, 1층 (당감동, 동남주상복합아파트)한식추어탕225.8051-891-4458
67진수밥상당감동백양관문로111(당감동)한식한정식295.08051-895-1511
78중앙숯불갈비범천동골드테마길 65 (범천동)한식돼지갈비,삼겹살62.9051-632-2008
89백향만두부암동당감로 118 (부암동)중식우동,자장면56.12051-816-6970
910미락부암동당감서로 90 (부암동)일식생선회,초밥139.88051-809-8077
연번업소명동별소재지(도로명)음식의유형주된음식면적(제곱미터)전화번호
4243전통음식점 원양양정동동평로420번길 23 (양정동)한식생갈비,쌈밥62.37051-864-0773
4344현대가든양정동범양로125번길 12 (양정동)한식생갈비,삼겹살410.0051-852-8866
4445갤러리움웨딩홀부페양정동중앙대로969번길 11, c201호 (양정동,양정롯데갤러리움아파트(2층))뷔페뷔페688.97051-852-6776
4546건양정홍삼삼계탕서면점전포동동성로 147 (전포동,외1필지(1.2층))한식삼계탕207.88051-817-3317
4647S서울깍뚜기전포동서전로 49 (전포동)한식설렁탕,곰탕273.0051-816-3950
4748정가네 샤브샤브전포동중앙대로 786 (전포동)한식샤브샤브309.49051-808-1238
4849이바돔감자탕전포동중앙대로 808 (전포동)한식감자탕326.25051-805-3330
4950조방낙지초읍점초읍동성지곡로 17 (초읍동, 지상1층전체)한식낙지볶음201.15051-804-8600
5051돌쇠본가초읍동성지곡로12번길 25 (초읍동)한식전복갈비찜,돌솥밥124.6051-804-7980
5152사랑채초읍동월드컵대로472번길 24 (초읍동)한식돌솥밥85.77051-805-3832