Overview

Dataset statistics

Number of variables8
Number of observations37
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory69.6 B

Variable types

Numeric2
Text4
Categorical1
DateTime1

Dataset

Description인천광역시 서구 모범음식점 현황 (업소명, 유형, 주메뉴, 소재지, 주차대수, 전화번호 등) 에 관한 데이터를 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15068674&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
주차대수 has 1 (2.7%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-28 12:40:48.131491
Analysis finished2024-01-28 12:40:48.998670
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-28T21:40:49.052149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2024-01-28T21:40:49.164566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

업소명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-01-28T21:40:49.674398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length13
Mean length7.2432432
Min length2

Characters and Unicode

Total characters268
Distinct characters144
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

Unique37 ?
Unique (%)100.0%

Sample

1st row어부횟집
2nd row강선생막국수
3rd row인천그랜드CC클럽하우스
4th row희래등
5th row석남동함흥냉면
ValueCountFrequency (%)
어부횟집 1
 
2.3%
플러스 1
 
2.3%
권오길손국수본점 1
 
2.3%
드마리스 1
 
2.3%
청수한방횡계백숙 1
 
2.3%
섬진강 1
 
2.3%
교동찹쌀순대 1
 
2.3%
굴세상 1
 
2.3%
촌장골(주 1
 
2.3%
채선당 1
 
2.3%
Other values (33) 33
76.7%
2024-01-28T21:40:50.010890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 15
 
5.6%
점 9
 
3.4%
주 9
 
3.4%
( 8
 
3.0%
) 8
 
3.0%
6
 
2.2%
시 5
 
1.9%
가 5
 
1.9%
타 5
 
1.9%
이 4
 
1.5%
Other values (134) 194
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
91.0%
Open Punctuation 8
 
3.0%
Close Punctuation 8
 
3.0%
Space Separator 6
 
2.2%
Uppercase Letter 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 15
 
6.1%
점 9
 
3.7%
주 9
 
3.7%
시 5
 
2.0%
가 5
 
2.0%
타 5
 
2.0%
이 4
 
1.6%
템 4
 
1.6%
엔 4
 
1.6%
수 4
 
1.6%
Other values (130) 180
73.8%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
91.0%
Common 22
 
8.2%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 15
 
6.1%
점 9
 
3.7%
주 9
 
3.7%
시 5
 
2.0%
가 5
 
2.0%
타 5
 
2.0%
이 4
 
1.6%
템 4
 
1.6%
엔 4
 
1.6%
수 4
 
1.6%
Other values (130) 180
73.8%
Common
ValueCountFrequency (%)
( 8
36.4%
) 8
36.4%
6
27.3%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
91.0%
ASCII 24
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 15
 
6.1%
점 9
 
3.7%
주 9
 
3.7%
시 5
 
2.0%
가 5
 
2.0%
타 5
 
2.0%
이 4
 
1.6%
템 4
 
1.6%
엔 4
 
1.6%
수 4
 
1.6%
Other values (130) 180
73.8%
ASCII
ValueCountFrequency (%)
( 8
33.3%
) 8
33.3%
6
25.0%
C 2
 
8.3%

유형
Categorical

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
한식
28 
일식
3 
중식
 
2
뷔페
 
2
양식
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 28
75.7%
일식 3
 
8.1%
중식 2
 
5.4%
뷔페 2
 
5.4%
양식 2
 
5.4%

Length

2024-01-28T21:40:50.125621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:40:50.219725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 28
75.7%
일식 3
 
8.1%
중식 2
 
5.4%
뷔페 2
 
5.4%
양식 2
 
5.4%

주메뉴(가격)
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-01-28T21:40:50.419216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length26.432432
Min length15

Characters and Unicode

Total characters978
Distinct characters147
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

Unique35 ?
Unique (%)94.6%

Sample

1st row어부만선코스(170000)+어부A코스(130000)
2nd row막국수(7000)+만두전골(8000)
3rd row김치전골(4인)(80000)
4th row망고크림새우(소)(40000)+멘보샤(소)(28000)
5th row냉면(8000)+돼지갈비(14000)
ValueCountFrequency (%)
소양념왕갈비(38000)+돼지왕갈비(19000 2
 
5.3%
유니짜장(6000)+찹쌀탕수육(대)(25000 1
 
2.6%
막국수(7000)+만두전골(8000 1
 
2.6%
능이버섯소고기두부전골(4인)(90000)+메로매운탕(4인)(120000 1
 
2.6%
즉석칼국수(8000)+냉말이(7000 1
 
2.6%
평일런치(26400)+평일디너(38900)+주말공휴일(41900 1
 
2.6%
닭볶음탕(45000)+한방오리백숙(50000 1
 
2.6%
메기매운탕(대)(39000)+오리백숙(49000 1
 
2.6%
굴버섯돌솥밥(7000)+굴순두부(6000 1
 
2.6%
우삼겹정식(11000)+차돌된장찌개(6000 1
 
2.6%
Other values (27) 27
71.1%
2024-01-28T21:40:50.751726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 240
24.5%
) 87
 
8.9%
( 87
 
8.9%
+ 37
 
3.8%
1 31
 
3.2%
5 18
 
1.8%
8 18
 
1.8%
4 17
 
1.7%
2 16
 
1.6%
탕 15
 
1.5%
Other values (137) 412
42.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 383
39.2%
Other Letter 378
38.7%
Close Punctuation 87
 
8.9%
Open Punctuation 87
 
8.9%
Math Symbol 41
 
4.2%
Uppercase Letter 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 15
 
4.0%
비 15
 
4.0%
갈 15
 
4.0%
지 14
 
3.7%
스 13
 
3.4%
왕 9
 
2.4%
코 8
 
2.1%
샤 8
 
2.1%
소 8
 
2.1%
돼 7
 
1.9%
Other values (121) 266
70.4%
Decimal Number
ValueCountFrequency (%)
0 240
62.7%
1 31
 
8.1%
5 18
 
4.7%
8 18
 
4.7%
4 17
 
4.4%
2 16
 
4.2%
9 14
 
3.7%
3 12
 
3.1%
7 10
 
2.6%
6 7
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 37
90.2%
~ 4
 
9.8%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 599
61.2%
Hangul 378
38.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 15
 
4.0%
비 15
 
4.0%
갈 15
 
4.0%
지 14
 
3.7%
스 13
 
3.4%
왕 9
 
2.4%
코 8
 
2.1%
샤 8
 
2.1%
소 8
 
2.1%
돼 7
 
1.9%
Other values (121) 266
70.4%
Common
ValueCountFrequency (%)
0 240
40.1%
) 87
 
14.5%
( 87
 
14.5%
+ 37
 
6.2%
1 31
 
5.2%
5 18
 
3.0%
8 18
 
3.0%
4 17
 
2.8%
2 16
 
2.7%
9 14
 
2.3%
Other values (5) 34
 
5.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
61.3%
Hangul 378
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 240
40.0%
) 87
 
14.5%
( 87
 
14.5%
+ 37
 
6.2%
1 31
 
5.2%
5 18
 
3.0%
8 18
 
3.0%
4 17
 
2.8%
2 16
 
2.7%
9 14
 
2.3%
Other values (6) 35
 
5.8%
Hangul
ValueCountFrequency (%)
탕 15
 
4.0%
비 15
 
4.0%
갈 15
 
4.0%
지 14
 
3.7%
스 13
 
3.4%
왕 9
 
2.4%
코 8
 
2.1%
샤 8
 
2.1%
소 8
 
2.1%
돼 7
 
1.9%
Other values (121) 266
70.4%

소재지
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-01-28T21:40:50.995291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length27.135135
Min length21

Characters and Unicode

Total characters1004
Distinct characters96
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 검단로 467, 201~202호 (왕길동, 다섬프라자)
2nd row인천광역시 서구 담지로86번길 20 (연희동)
3rd row인천광역시 서구 원석로 195 (원창동)
4th row인천광역시 서구 탁옥로86번길 6-1 (심곡동)
5th row인천광역시 서구 석남로 87 (석남동)
ValueCountFrequency (%)
인천광역시 37
 
17.6%
서구 37
 
17.6%
심곡동 12
 
5.7%
가좌동 6
 
2.9%
2층 6
 
2.9%
경서동 5
 
2.4%
1층 4
 
1.9%
서곶로 4
 
1.9%
884 3
 
1.4%
백범로 3
 
1.4%
Other values (81) 93
44.3%
2024-01-28T21:40:51.369452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
 
17.2%
서 50
 
5.0%
인 38
 
3.8%
로 38
 
3.8%
동 38
 
3.8%
광 37
 
3.7%
역 37
 
3.7%
시 37
 
3.7%
구 37
 
3.7%
천 37
 
3.7%
Other values (86) 482
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 564
56.2%
Space Separator 173
 
17.2%
Decimal Number 165
 
16.4%
Open Punctuation 37
 
3.7%
Close Punctuation 37
 
3.7%
Other Punctuation 21
 
2.1%
Dash Punctuation 3
 
0.3%
Math Symbol 3
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 50
 
8.9%
인 38
 
6.7%
로 38
 
6.7%
동 38
 
6.7%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
구 37
 
6.6%
천 37
 
6.6%
길 17
 
3.0%
Other values (69) 198
35.1%
Decimal Number
ValueCountFrequency (%)
2 34
20.6%
1 32
19.4%
6 16
9.7%
8 16
9.7%
3 15
9.1%
5 14
8.5%
0 13
 
7.9%
4 12
 
7.3%
7 9
 
5.5%
9 4
 
2.4%
Space Separator
ValueCountFrequency (%)
173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 564
56.2%
Common 439
43.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 50
 
8.9%
인 38
 
6.7%
로 38
 
6.7%
동 38
 
6.7%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
구 37
 
6.6%
천 37
 
6.6%
길 17
 
3.0%
Other values (69) 198
35.1%
Common
ValueCountFrequency (%)
173
39.4%
( 37
 
8.4%
) 37
 
8.4%
2 34
 
7.7%
1 32
 
7.3%
, 21
 
4.8%
6 16
 
3.6%
8 16
 
3.6%
3 15
 
3.4%
5 14
 
3.2%
Other values (6) 44
 
10.0%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 564
56.2%
ASCII 440
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
39.3%
( 37
 
8.4%
) 37
 
8.4%
2 34
 
7.7%
1 32
 
7.3%
, 21
 
4.8%
6 16
 
3.6%
8 16
 
3.6%
3 15
 
3.4%
5 14
 
3.2%
Other values (7) 45
 
10.2%
Hangul
ValueCountFrequency (%)
서 50
 
8.9%
인 38
 
6.7%
로 38
 
6.7%
동 38
 
6.7%
광 37
 
6.6%
역 37
 
6.6%
시 37
 
6.6%
구 37
 
6.6%
천 37
 
6.6%
길 17
 
3.0%
Other values (69) 198
35.1%

주차대수
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)61.1%
Missing1
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean60.611111
Minimum2
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-28T21:40:51.481782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q111.5
median26
Q350
95-th percentile208.5
Maximum500
Range498
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation95.568458
Coefficient of variation (CV)1.5767482
Kurtosis12.567088
Mean60.611111
Median Absolute Deviation (MAD)20.5
Skewness3.2376456
Sum2182
Variance9133.3302
MonotonicityNot monotonic
2024-01-28T21:40:51.595093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
50 5
13.5%
25 3
 
8.1%
30 3
 
8.1%
160 3
 
8.1%
15 2
 
5.4%
6 2
 
5.4%
4 2
 
5.4%
5 2
 
5.4%
20 1
 
2.7%
40 1
 
2.7%
Other values (12) 12
32.4%
ValueCountFrequency (%)
2 1
2.7%
4 2
5.4%
5 2
5.4%
6 2
5.4%
8 1
2.7%
10 1
2.7%
12 1
2.7%
15 2
5.4%
18 1
2.7%
20 1
2.7%
ValueCountFrequency (%)
500 1
 
2.7%
234 1
 
2.7%
200 1
 
2.7%
160 3
8.1%
70 1
 
2.7%
62 1
 
2.7%
50 5
13.5%
40 1
 
2.7%
30 3
8.1%
27 1
 
2.7%

전화번호
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-01-28T21:40:51.787045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.918919
Min length9

Characters and Unicode

Total characters441
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

Unique37 ?
Unique (%)100.0%

Sample

1st row032-568-2922
2nd row032-576-3939
3rd row032-579-1002
4th row032-565-5100
5th row032-583-8445
ValueCountFrequency (%)
032-568-2922 1
 
2.7%
032-563-0288 1
 
2.7%
032-562-4343 1
 
2.7%
032-564-7541 1
 
2.7%
1522-0115 1
 
2.7%
032-567-2446 1
 
2.7%
032-566-6121 1
 
2.7%
032-563-3838 1
 
2.7%
032-584-8292 1
 
2.7%
032-569-4112 1
 
2.7%
Other values (27) 27
73.0%
2024-01-28T21:40:52.086970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 73
16.6%
2 63
14.3%
0 55
12.5%
3 54
12.2%
5 49
11.1%
6 43
9.8%
7 26
 
5.9%
1 22
 
5.0%
4 22
 
5.0%
8 19
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 368
83.4%
Dash Punctuation 73
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 63
17.1%
0 55
14.9%
3 54
14.7%
5 49
13.3%
6 43
11.7%
7 26
7.1%
1 22
 
6.0%
4 22
 
6.0%
8 19
 
5.2%
9 15
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 73
16.6%
2 63
14.3%
0 55
12.5%
3 54
12.2%
5 49
11.1%
6 43
9.8%
7 26
 
5.9%
1 22
 
5.0%
4 22
 
5.0%
8 19
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 73
16.6%
2 63
14.3%
0 55
12.5%
3 54
12.2%
5 49
11.1%
6 43
9.8%
7 26
 
5.9%
1 22
 
5.0%
4 22
 
5.0%
8 19
 
4.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
Minimum2022-09-06 00:00:00
Maximum2022-09-06 00:00:00
2024-01-28T21:40:52.189323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:40:52.280014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T21:40:48.662922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:40:48.503040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:40:48.742486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:40:48.590623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:40:52.347788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명유형주메뉴(가격)소재지주차대수전화번호
연번1.0001.0000.0000.9161.0000.0001.000
업소명1.0001.0001.0001.0001.0001.0001.000
유형0.0001.0001.0001.0001.0000.4621.000
주메뉴(가격)0.9161.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.000
주차대수0.0001.0000.4621.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
2024-01-28T21:40:52.454024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주차대수유형
연번1.000-0.0390.000
주차대수-0.0391.0000.178
유형0.0000.1781.000

Missing values

2024-01-28T21:40:48.838028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:40:48.952745image/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

연번업소명유형주메뉴(가격)소재지주차대수전화번호데이터기준일자
01어부횟집일식어부만선코스(170000)+어부A코스(130000)인천광역시 서구 검단로 467, 201~202호 (왕길동, 다섬프라자)25032-568-29222022-09-06
12강선생막국수한식막국수(7000)+만두전골(8000)인천광역시 서구 담지로86번길 20 (연희동)4032-576-39392022-09-06
23인천그랜드CC클럽하우스한식김치전골(4인)(80000)인천광역시 서구 원석로 195 (원창동)200032-579-10022022-09-06
34희래등중식망고크림새우(소)(40000)+멘보샤(소)(28000)인천광역시 서구 탁옥로86번길 6-1 (심곡동)12032-565-51002022-09-06
45석남동함흥냉면한식냉면(8000)+돼지갈비(14000)인천광역시 서구 석남로 87 (석남동)30032-583-84452022-09-06
56경복궁가좌점(주)엔타스시스템한식한정식코스(45000)+소양념갈비(38000)인천광역시 서구 원적로 132 (가좌동)50032-583-77672022-09-06
67경복궁송림점점(주)엔타스시스템한식한정식코스(55000)+쿠이코스(55000~90000)인천광역시 서구 백범로 884, 201호 (가좌동)160032-574-77672022-09-06
78참조은복집일식복지리탕(1인분)(25000)+복지리(10000)인천광역시 서구 서곶로315번길 23-1 (심곡동)6032-563-70192022-09-06
89김생곤의 육해공한식전복낙지갈비탕(25000)+갈비탕(12000)인천광역시 서구 원창로64번길 16-8, 1층 (원창동)62032-565-84442022-09-06
910샤브홀리 검단점뷔페소고기샤브샤브(13900~16900)+오리샤브샤브(14900~17900)인천광역시 서구 원당대로 644, G동 2층 (당하동, 패션타운파티)27032-564-91132022-09-06
연번업소명유형주메뉴(가격)소재지주차대수전화번호데이터기준일자
2728굴세상한식굴버섯돌솥밥(7000)+굴순두부(6000)인천광역시 서구 새오개로 36 (석남동)2032-584-82922022-09-06
2829촌장골(주)한식소양념왕갈비(38000)+돼지왕갈비(19000)인천광역시 서구 서곶로 850 (당하동)50032-569-41122022-09-06
2930채선당 플러스한식스페셜소고기샤브샤브 점심(14800)+저녁(18800)인천광역시 서구 서곶로 277, 2층 (심곡동)30032-562-75772022-09-06
3031한라담 제주돼지숯불구이한식돼지갈비(15000)+제주오겹살(16000)인천광역시 서구 경명대로 401, 1층 (경서동)70032-565-00922022-09-06
3132두리문설렁탕한식돼지왕갈비(12000)+갈비탕(9000)인천광역시 서구 가정로 221 (석남동)30032-574-24742022-09-06
3233종가집한식한우꽃등심(17000)+한방왕갈비탕(12000)인천광역시 서구 검단로 505, 115~116호 (마전동, 이지화인프라자)50032-562-06212022-09-06
3334이대감 전통음식점 청라점한식전통육개장(7000)+양지물냉면(7000)인천광역시 서구 푸른로7번길 12 (경서동)4032-568-62662022-09-06
3435미가원한식왕생양념갈비(25000)+왕갈비탕(10000)인천광역시 서구 서곶로 872 (마전동)40032-564-32912022-09-06
3536본가한식우삼겹정식(11000)+차돌된장찌개(6000)인천광역시 서구 완정로 113, 2~3층 (왕길동)50032-566-74412022-09-06
3637육대장한식육개장(8000)+보쌈(중)(30000)인천광역시 서구 서곶로301번길 16, 112호 (심곡동)20032-562-30072022-09-06