Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells43
Missing cells (%)10.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory68.6 B

Variable types

Text4
Boolean2
Numeric2

Dataset

Description더술(https://thesool.com/)에서 제공하는 찾아가는양조장 정보 * 찾아가는 양조장은 농림축산식품부와 한국농수산식품유통공사에서 선정한 지역의 우수 전통주 양조장 입니다.
Author한국농수산식품유통공사
URLhttps://www.data.go.kr/data/15048756/fileData.do

Alerts

조회수 is highly overall correlated with 양조장 상시방문가능여부 and 1 other fieldsHigh correlation
찾아가는양조장넘버 is highly overall correlated with 양조장 상시방문가능여부 and 1 other fieldsHigh correlation
양조장 상시방문가능여부 is highly overall correlated with 조회수 and 1 other fieldsHigh correlation
양조장 예약방문가능여부 is highly overall correlated with 조회수 and 1 other fieldsHigh correlation
양조장 홈페이지 has 1 (2.0%) missing valuesMissing
양조장 상시방문가능여부 has 10 (20.0%) missing valuesMissing
양조장 예약방문가능여부 has 28 (56.0%) missing valuesMissing
조회수 has 4 (8.0%) missing valuesMissing
양조장 이름 has unique valuesUnique
양조장 주소 has unique valuesUnique
양조장 연락처 has unique valuesUnique
찾아가는양조장넘버 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:13:13.702061
Analysis finished2023-12-12 09:13:15.149744
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

양조장 이름
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T18:13:15.398533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.8
Min length2

Characters and Unicode

Total characters240
Distinct characters103
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row산머루농원
2nd row배상면주가
3rd row우리술
4th row그린영농조합
5th row배혜정도가
ValueCountFrequency (%)
산머루농원 1
 
1.9%
수도산와이너리 1
 
1.9%
산막와이너리 1
 
1.9%
국순당 1
 
1.9%
울진술도가 1
 
1.9%
오미나라 1
 
1.9%
문경주조 1
 
1.9%
명인안동소주 1
 
1.9%
한국애플리즈 1
 
1.9%
은척양조장 1
 
1.9%
Other values (44) 44
81.5%
2023-12-12T18:13:15.908265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 16
 
6.7%
주 12
 
5.0%
산 10
 
4.2%
양 9
 
3.8%
장 9
 
3.8%
술 8
 
3.3%
리 8
 
3.3%
도 6
 
2.5%
와 6
 
2.5%
인 6
 
2.5%
Other values (93) 150
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 236
98.3%
Space Separator 4
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 16
 
6.8%
주 12
 
5.1%
산 10
 
4.2%
양 9
 
3.8%
장 9
 
3.8%
술 8
 
3.4%
리 8
 
3.4%
도 6
 
2.5%
와 6
 
2.5%
인 6
 
2.5%
Other values (92) 146
61.9%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
98.3%
Common 4
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 16
 
6.8%
주 12
 
5.1%
산 10
 
4.2%
양 9
 
3.8%
장 9
 
3.8%
술 8
 
3.4%
리 8
 
3.4%
도 6
 
2.5%
와 6
 
2.5%
인 6
 
2.5%
Other values (92) 146
61.9%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 236
98.3%
ASCII 4
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 16
 
6.8%
주 12
 
5.1%
산 10
 
4.2%
양 9
 
3.8%
장 9
 
3.8%
술 8
 
3.4%
리 8
 
3.4%
도 6
 
2.5%
와 6
 
2.5%
인 6
 
2.5%
Other values (92) 146
61.9%
ASCII
ValueCountFrequency (%)
4
100.0%

양조장 주소
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T18:13:16.326591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24.5
Mean length19.9
Min length13

Characters and Unicode

Total characters995
Distinct characters152
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

Unique50 ?
Unique (%)100.0%

Sample

1st row경기 파주시 적성면 객현리 67-1
2nd row경기도 포천시 화현면 화현리 512
3rd row경기 가평군 하면 대보간선로 26, 29
4th row경기도 안산시 단원구 뻐꾹산길 107
5th row경기도 화성시 정남면 서봉로 835
ValueCountFrequency (%)
충북 7
 
2.8%
경기 5
 
2.0%
경북 5
 
2.0%
경기도 5
 
2.0%
경상북도 4
 
1.6%
충남 4
 
1.6%
영동군 4
 
1.6%
전남 3
 
1.2%
충청북도 3
 
1.2%
청원구 3
 
1.2%
Other values (200) 210
83.0%
2023-12-12T18:13:16.904871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
203
 
20.4%
면 33
 
3.3%
1 31
 
3.1%
시 28
 
2.8%
2 28
 
2.8%
경 26
 
2.6%
북 22
 
2.2%
군 22
 
2.2%
로 20
 
2.0%
길 19
 
1.9%
Other values (142) 563
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 611
61.4%
Space Separator 203
 
20.4%
Decimal Number 160
 
16.1%
Dash Punctuation 18
 
1.8%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 33
 
5.4%
시 28
 
4.6%
경 26
 
4.3%
북 22
 
3.6%
군 22
 
3.6%
로 20
 
3.3%
길 19
 
3.1%
도 19
 
3.1%
산 18
 
2.9%
충 17
 
2.8%
Other values (127) 387
63.3%
Decimal Number
ValueCountFrequency (%)
1 31
19.4%
2 28
17.5%
4 18
11.2%
8 15
9.4%
5 14
8.8%
3 14
8.8%
6 13
8.1%
9 12
 
7.5%
7 8
 
5.0%
0 7
 
4.4%
Space Separator
ValueCountFrequency (%)
203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 611
61.4%
Common 384
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 33
 
5.4%
시 28
 
4.6%
경 26
 
4.3%
북 22
 
3.6%
군 22
 
3.6%
로 20
 
3.3%
길 19
 
3.1%
도 19
 
3.1%
산 18
 
2.9%
충 17
 
2.8%
Other values (127) 387
63.3%
Common
ValueCountFrequency (%)
203
52.9%
1 31
 
8.1%
2 28
 
7.3%
4 18
 
4.7%
- 18
 
4.7%
8 15
 
3.9%
5 14
 
3.6%
3 14
 
3.6%
6 13
 
3.4%
9 12
 
3.1%
Other values (5) 18
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 611
61.4%
ASCII 384
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
203
52.9%
1 31
 
8.1%
2 28
 
7.3%
4 18
 
4.7%
- 18
 
4.7%
8 15
 
3.9%
5 14
 
3.6%
3 14
 
3.6%
6 13
 
3.4%
9 12
 
3.1%
Other values (5) 18
 
4.7%
Hangul
ValueCountFrequency (%)
면 33
 
5.4%
시 28
 
4.6%
경 26
 
4.3%
북 22
 
3.6%
군 22
 
3.6%
로 20
 
3.3%
길 19
 
3.1%
도 19
 
3.1%
산 18
 
2.9%
충 17
 
2.8%
Other values (127) 387
63.3%

양조장 연락처
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T18:13:17.236228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02
Min length9

Characters and Unicode

Total characters601
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

Unique50 ?
Unique (%)100.0%

Sample

1st row031-958-4558
2nd row031-531-9300
3rd row031-585-8525
4th row032-886-9873
5th row031-354-9376
ValueCountFrequency (%)
031-958-4558 1
 
2.0%
054-439-1518 1
 
2.0%
043-745-3888 1
 
2.0%
033-340-4300 1
 
2.0%
054-782-1855 1
 
2.0%
054-572-0601 1
 
2.0%
054-552-8285 1
 
2.0%
054-856-6903 1
 
2.0%
054-834-7800 1
 
2.0%
054-541-6409 1
 
2.0%
Other values (40) 40
80.0%
2023-12-12T18:13:18.126868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 99
16.5%
0 94
15.6%
3 65
10.8%
4 65
10.8%
5 59
9.8%
1 49
8.2%
7 37
 
6.2%
8 36
 
6.0%
2 36
 
6.0%
6 31
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 502
83.5%
Dash Punctuation 99
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
18.7%
3 65
12.9%
4 65
12.9%
5 59
11.8%
1 49
9.8%
7 37
 
7.4%
8 36
 
7.2%
2 36
 
7.2%
6 31
 
6.2%
9 30
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 99
16.5%
0 94
15.6%
3 65
10.8%
4 65
10.8%
5 59
9.8%
1 49
8.2%
7 37
 
6.2%
8 36
 
6.0%
2 36
 
6.0%
6 31
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 99
16.5%
0 94
15.6%
3 65
10.8%
4 65
10.8%
5 59
9.8%
1 49
8.2%
7 37
 
6.2%
8 36
 
6.0%
2 36
 
6.0%
6 31
 
5.2%

양조장 홈페이지
Text

MISSING 

Distinct49
Distinct (%)100.0%
Missing1
Missing (%)2.0%
Memory size532.0 B
2023-12-12T18:13:18.466600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length33
Mean length25.061224
Min length15

Characters and Unicode

Total characters1228
Distinct characters46
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st rowhttp://www.sanmeoru.com
2nd rowhttp://www.sansawon.co.kr
3rd rowhttp://www.woorisool.kr
4th rowhttp://www.grandcoteau.co.kr
5th rowhttp://www.baedoga.co.kr/
ValueCountFrequency (%)
http://www.sanmeoru.com 1
 
2.0%
http://www.ye-sul.co.kr 1
 
2.0%
http://www.ksdb.co.kr 1
 
2.0%
http://www.uljinsuldoga.com/index.php 1
 
2.0%
http://www.omynara.com 1
 
2.0%
https://mgomijasul.modoo.at 1
 
2.0%
http://www.adsoju.com 1
 
2.0%
http://www.applewine.co.kr 1
 
2.0%
https://takbaeki.modoo.at 1
 
2.0%
http://www.vincoree.com 1
 
2.0%
Other values (39) 39
79.6%
2023-12-12T18:13:18.990349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 128
 
10.4%
w 126
 
10.3%
. 111
 
9.0%
t 108
 
8.8%
o 104
 
8.5%
h 60
 
4.9%
p 56
 
4.6%
: 48
 
3.9%
c 47
 
3.8%
a 46
 
3.7%
Other values (36) 394
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 913
74.3%
Other Punctuation 287
 
23.4%
Other Letter 13
 
1.1%
Decimal Number 9
 
0.7%
Dash Punctuation 5
 
0.4%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 126
13.8%
t 108
11.8%
o 104
11.4%
h 60
 
6.6%
p 56
 
6.1%
c 47
 
5.1%
a 46
 
5.0%
m 45
 
4.9%
s 43
 
4.7%
r 37
 
4.1%
Other values (15) 241
26.4%
Other Letter
ValueCountFrequency (%)
인 2
15.4%
조 1
7.7%
와 1
7.7%
리 1
7.7%
도 1
7.7%
고 1
7.7%
장 1
7.7%
태 1
7.7%
양 1
7.7%
청 1
7.7%
Other values (2) 2
15.4%
Decimal Number
ValueCountFrequency (%)
3 3
33.3%
4 3
33.3%
1 2
22.2%
9 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 128
44.6%
. 111
38.7%
: 48
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 913
74.3%
Common 302
 
24.6%
Hangul 13
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 126
13.8%
t 108
11.8%
o 104
11.4%
h 60
 
6.6%
p 56
 
6.1%
c 47
 
5.1%
a 46
 
5.0%
m 45
 
4.9%
s 43
 
4.7%
r 37
 
4.1%
Other values (15) 241
26.4%
Hangul
ValueCountFrequency (%)
인 2
15.4%
조 1
7.7%
와 1
7.7%
리 1
7.7%
도 1
7.7%
고 1
7.7%
장 1
7.7%
태 1
7.7%
양 1
7.7%
청 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
/ 128
42.4%
. 111
36.8%
: 48
 
15.9%
- 5
 
1.7%
3 3
 
1.0%
4 3
 
1.0%
1 2
 
0.7%
9 1
 
0.3%
_ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1215
98.9%
Hangul 13
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 128
 
10.5%
w 126
 
10.4%
. 111
 
9.1%
t 108
 
8.9%
o 104
 
8.6%
h 60
 
4.9%
p 56
 
4.6%
: 48
 
4.0%
c 47
 
3.9%
a 46
 
3.8%
Other values (24) 381
31.4%
Hangul
ValueCountFrequency (%)
인 2
15.4%
조 1
7.7%
와 1
7.7%
리 1
7.7%
도 1
7.7%
고 1
7.7%
장 1
7.7%
태 1
7.7%
양 1
7.7%
청 1
7.7%
Other values (2) 2
15.4%

양조장 상시방문가능여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)5.0%
Missing10
Missing (%)20.0%
Memory size232.0 B
True
35 
False
5 
(Missing)
10 
ValueCountFrequency (%)
True 35
70.0%
False 5
 
10.0%
(Missing) 10
 
20.0%
2023-12-12T18:13:19.151183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

양조장 예약방문가능여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)9.1%
Missing28
Missing (%)56.0%
Memory size232.0 B
True
19 
False
3 
(Missing)
28 
ValueCountFrequency (%)
True 19
38.0%
False 3
 
6.0%
(Missing) 28
56.0%
2023-12-12T18:13:19.281562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조회수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)95.7%
Missing4
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean164.69565
Minimum55
Maximum372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-12T18:13:19.432167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55
5-th percentile80.25
Q1112.5
median151
Q3189.5
95-th percentile337.5
Maximum372
Range317
Interquartile range (IQR)77

Descriptive statistics

Standard deviation74.230233
Coefficient of variation (CV)0.45071155
Kurtosis1.6223878
Mean164.69565
Median Absolute Deviation (MAD)40.5
Skewness1.2236739
Sum7576
Variance5510.1275
MonotonicityNot monotonic
2023-12-12T18:13:19.622596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
159 2
 
4.0%
131 2
 
4.0%
220 1
 
2.0%
226 1
 
2.0%
169 1
 
2.0%
133 1
 
2.0%
188 1
 
2.0%
273 1
 
2.0%
93 1
 
2.0%
206 1
 
2.0%
Other values (34) 34
68.0%
(Missing) 4
 
8.0%
ValueCountFrequency (%)
55 1
2.0%
59 1
2.0%
79 1
2.0%
84 1
2.0%
88 1
2.0%
89 1
2.0%
93 1
2.0%
97 1
2.0%
105 1
2.0%
106 1
2.0%
ValueCountFrequency (%)
372 1
2.0%
367 1
2.0%
359 1
2.0%
273 1
2.0%
254 1
2.0%
240 1
2.0%
236 1
2.0%
226 1
2.0%
220 1
2.0%
213 1
2.0%

찾아가는양조장넘버
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-12T18:13:19.798691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2023-12-12T18:13:19.971522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

Interactions

2023-12-12T18:13:14.409919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:13:14.190295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:13:14.513077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:13:14.321083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:13:20.098916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
양조장 이름양조장 주소양조장 연락처양조장 홈페이지양조장 상시방문가능여부양조장 예약방문가능여부조회수찾아가는양조장넘버
양조장 이름1.0001.0001.0001.0001.0001.0001.0001.000
양조장 주소1.0001.0001.0001.0001.0001.0001.0001.000
양조장 연락처1.0001.0001.0001.0001.0001.0001.0001.000
양조장 홈페이지1.0001.0001.0001.0001.0001.0001.0001.000
양조장 상시방문가능여부1.0001.0001.0001.0001.0000.6371.0000.754
양조장 예약방문가능여부1.0001.0001.0001.0000.6371.0000.9001.000
조회수1.0001.0001.0001.0001.0000.9001.0000.690
찾아가는양조장넘버1.0001.0001.0001.0000.7541.0000.6901.000
2023-12-12T18:13:20.229871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
양조장 상시방문가능여부양조장 예약방문가능여부
양조장 상시방문가능여부1.0000.433
양조장 예약방문가능여부0.4331.000
2023-12-12T18:13:20.332700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회수찾아가는양조장넘버양조장 상시방문가능여부양조장 예약방문가능여부
조회수1.000-0.4770.9100.577
찾아가는양조장넘버-0.4771.0000.5230.806
양조장 상시방문가능여부0.9100.5231.0000.433
양조장 예약방문가능여부0.5770.8060.4331.000

Missing values

2023-12-12T18:13:14.686865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:13:14.894258image/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.
2023-12-12T18:13:15.067279image/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

양조장 이름양조장 주소양조장 연락처양조장 홈페이지양조장 상시방문가능여부양조장 예약방문가능여부조회수찾아가는양조장넘버
0산머루농원경기 파주시 적성면 객현리 67-1031-958-4558http://www.sanmeoru.com<NA>Y3721
1배상면주가경기도 포천시 화현면 화현리 512031-531-9300http://www.sansawon.co.krY<NA>3672
2우리술경기 가평군 하면 대보간선로 26, 29031-585-8525http://www.woorisool.krY<NA>3593
3그린영농조합경기도 안산시 단원구 뻐꾹산길 107032-886-9873http://www.grandcoteau.co.krY<NA>2364
4배혜정도가경기도 화성시 정남면 서봉로 835031-354-9376http://www.baedoga.co.kr/<NA>Y2545
5밝은세상영농조합경기도 평택시 포승읍 충열길 37031-683-0981http://www.tigercalyx.com/<NA>Y1776
6좋은술경기 평택시 오성면 숙성뜰길 108031-681-8929https://jsul.modoo.at/Y<NA>1257
7술샘경기도 용인시 처인구 양지면 죽양대로 2298-1070-4218-5225http://www.sulseam.comY<NA>1598
8신평양조장충남 당진시 신평면 신평로 813041-362-6080http://www.koreansul.co.krY<NA>1599
9예산사과와인충남 예산군 고덕면 대몽로 107-25041-337-9584http://www.chusawine.comY<NA>14110
양조장 이름양조장 주소양조장 연락처양조장 홈페이지양조장 상시방문가능여부양조장 예약방문가능여부조회수찾아가는양조장넘버
40제주샘주제주 제주시 애월읍 애언로 283064-799-4225http://www.jejusaemju.co.krY<NA>9741
41제주고소리술익는집제주도 서귀포시 표선면 중산간동로 4726064-787-5046http://jejugosorisul.com/Y<NA>12842
42모월강원 원주시 판부면 판부신촌길 84033-748-8008http://www.mowall.co.kr/NN7943
43술아원경기 여주 점봉길 93-12070-8776-0043https://soolawon.modoo.at/NN5944
44장희충북 청주 청원구 내수읍 미원초정로 1275070-4415-6567https://jhdg3491.modoo.at/NN5545
45하미앙경남 함양군 함양읍 삼봉로 442-14055-964-2500www.sanmuru.comNY8446
46금풍양조인천 강화군 길상면 삼랑성길 8070-4400-1931https://www.instagram.com/on_sul/YY<NA>47
47오산양조경기 오산시 시장길 63031-374-2139https://www.osansool.com/<NA><NA><NA>48
48산막와이너리충북 영동군 영동읍 산막골길 31-45043-745-3888http://www.sanmacwine.com/web/main/YY<NA>49
49맑은내일경남 창원시 성산구 삼귀로 411-8 (귀산동)055-264-0996https://www.good-tomorrow.co.kr/NY<NA>50