Overview

Dataset statistics

Number of variables7
Number of observations40
Missing cells31
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory60.3 B

Variable types

Numeric1
Text5
Categorical1

Dataset

Description영동군 와인 제조 판매 농가 인 와이너리 현황으로 법인명 및 농장명, 대표자, 상호, 읍 면, 주 소, 연락처가 제공됩니다.
Author충청북도 영동군
URLhttps://www.data.go.kr/data/3072323/fileData.do

Alerts

연락처 has 31 (77.5%) missing valuesMissing
순번 has unique valuesUnique
법인명및 농장명 has unique valuesUnique
대표자 has unique valuesUnique
상호 has unique valuesUnique
주 소 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:57:30.535226
Analysis finished2023-12-11 22:57:31.286411
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T07:57:31.365934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T07:57:31.512863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

법인명및 농장명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T07:57:31.746731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length6.2
Min length3

Characters and Unicode

Total characters248
Distinct characters106
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row와인코리아
2nd row비아들샤토영농조합법인
3rd row상모영농조합법인
4th rowAMS 영동미래농업㈜ 농업회사법인
5th row에덴농장
ValueCountFrequency (%)
농원 2
 
4.2%
와인코리아 1
 
2.1%
영농조합법인 1
 
2.1%
푸른농장 1
 
2.1%
토정식품 1
 
2.1%
추풍령사슴관광농원 1
 
2.1%
코리아엘리트와인 1
 
2.1%
co 1
 
2.1%
상촌농원 1
 
2.1%
영동 1
 
2.1%
Other values (37) 37
77.1%
2023-12-12T07:57:32.150591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 29
 
11.7%
원 15
 
6.0%
장 10
 
4.0%
인 9
 
3.6%
9
 
3.6%
영 8
 
3.2%
리 6
 
2.4%
와 6
 
2.4%
법 5
 
2.0%
산 5
 
2.0%
Other values (96) 146
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
94.0%
Space Separator 9
 
3.6%
Uppercase Letter 3
 
1.2%
Lowercase Letter 2
 
0.8%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 29
 
12.4%
원 15
 
6.4%
장 10
 
4.3%
인 9
 
3.9%
영 8
 
3.4%
리 6
 
2.6%
와 6
 
2.6%
법 5
 
2.1%
산 5
 
2.1%
동 4
 
1.7%
Other values (89) 136
58.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
M 1
33.3%
A 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 234
94.4%
Common 9
 
3.6%
Latin 5
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 29
 
12.4%
원 15
 
6.4%
장 10
 
4.3%
인 9
 
3.8%
영 8
 
3.4%
리 6
 
2.6%
와 6
 
2.6%
법 5
 
2.1%
산 5
 
2.1%
동 4
 
1.7%
Other values (90) 137
58.5%
Latin
ValueCountFrequency (%)
o 1
20.0%
c 1
20.0%
S 1
20.0%
M 1
20.0%
A 1
20.0%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
94.0%
ASCII 14
 
5.6%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 29
 
12.4%
원 15
 
6.4%
장 10
 
4.3%
인 9
 
3.9%
영 8
 
3.4%
리 6
 
2.6%
와 6
 
2.6%
법 5
 
2.1%
산 5
 
2.1%
동 4
 
1.7%
Other values (89) 136
58.4%
ASCII
ValueCountFrequency (%)
9
64.3%
o 1
 
7.1%
c 1
 
7.1%
S 1
 
7.1%
M 1
 
7.1%
A 1
 
7.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T07:57:32.373059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.05
Min length3

Characters and Unicode

Total characters122
Distinct characters68
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

Unique40 ?
Unique (%)100.0%

Sample

1st row윤태림
2nd row정상근
3rd row이은자
4th row이원근
5th row안재홍
ValueCountFrequency (%)
윤태림 1
 
2.4%
조순희 1
 
2.4%
박병일 1
 
2.4%
최성숙 1
 
2.4%
배지열 1
 
2.4%
정이근 1
 
2.4%
고계옥 1
 
2.4%
진창원 1
 
2.4%
정재운 1
 
2.4%
전인기 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T07:57:32.726403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
6.6%
이 6
 
4.9%
정 5
 
4.1%
성 5
 
4.1%
박 4
 
3.3%
순 4
 
3.3%
근 4
 
3.3%
재 3
 
2.5%
3
 
2.5%
남 3
 
2.5%
Other values (58) 77
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119
97.5%
Space Separator 3
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
6.7%
이 6
 
5.0%
정 5
 
4.2%
성 5
 
4.2%
박 4
 
3.4%
순 4
 
3.4%
근 4
 
3.4%
재 3
 
2.5%
남 3
 
2.5%
식 3
 
2.5%
Other values (57) 74
62.2%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119
97.5%
Common 3
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
6.7%
이 6
 
5.0%
정 5
 
4.2%
성 5
 
4.2%
박 4
 
3.4%
순 4
 
3.4%
근 4
 
3.4%
재 3
 
2.5%
남 3
 
2.5%
식 3
 
2.5%
Other values (57) 74
62.2%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119
97.5%
ASCII 3
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
6.7%
이 6
 
5.0%
정 5
 
4.2%
성 5
 
4.2%
박 4
 
3.4%
순 4
 
3.4%
근 4
 
3.4%
재 3
 
2.5%
남 3
 
2.5%
식 3
 
2.5%
Other values (57) 74
62.2%
ASCII
ValueCountFrequency (%)
3
100.0%

상호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T07:57:32.952168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.375
Min length3

Characters and Unicode

Total characters175
Distinct characters82
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

Unique40 ?
Unique (%)100.0%

Sample

1st row샤토마니
2nd row샤또비아들
3rd row르보까쥬
4th row원와인
5th row에덴와인
ValueCountFrequency (%)
샤토마니 1
 
2.4%
천고와인 1
 
2.4%
봉황와인 1
 
2.4%
필와인 1
 
2.4%
용와인 1
 
2.4%
코리아엘리트와인 1
 
2.4%
산너울 1
 
2.4%
베리와인 1
 
2.4%
비단숲와인 1
 
2.4%
미르아토 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T07:57:33.294463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
와 26
 
14.9%
인 26
 
14.9%
비 6
 
3.4%
리 6
 
3.4%
마 5
 
2.9%
토 5
 
2.9%
샤 4
 
2.3%
산 4
 
2.3%
아 4
 
2.3%
베 3
 
1.7%
Other values (72) 86
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
99.4%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
와 26
 
14.9%
인 26
 
14.9%
비 6
 
3.4%
리 6
 
3.4%
마 5
 
2.9%
토 5
 
2.9%
샤 4
 
2.3%
산 4
 
2.3%
아 4
 
2.3%
베 3
 
1.7%
Other values (71) 85
48.9%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
99.4%
Common 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
와 26
 
14.9%
인 26
 
14.9%
비 6
 
3.4%
리 6
 
3.4%
마 5
 
2.9%
토 5
 
2.9%
샤 4
 
2.3%
산 4
 
2.3%
아 4
 
2.3%
베 3
 
1.7%
Other values (71) 85
48.9%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
99.4%
ASCII 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
와 26
 
14.9%
인 26
 
14.9%
비 6
 
3.4%
리 6
 
3.4%
마 5
 
2.9%
토 5
 
2.9%
샤 4
 
2.3%
산 4
 
2.3%
아 4
 
2.3%
베 3
 
1.7%
Other values (71) 85
48.9%
ASCII
ValueCountFrequency (%)
1
100.0%

읍 면
Categorical

Distinct11
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
영동
12 
학산
10 
황간
5 
용화
3 
매곡
2 
Other values (6)
8 

Length

Max length3
Median length2
Mean length2.025
Min length2

Unique

Unique4 ?
Unique (%)10.0%

Sample

1st row영동
2nd row학산
3rd row학산
4th row영동
5th row영동

Common Values

ValueCountFrequency (%)
영동 12
30.0%
학산 10
25.0%
황간 5
12.5%
용화 3
 
7.5%
매곡 2
 
5.0%
심천 2
 
5.0%
양산 2
 
5.0%
추풍령 1
 
2.5%
양강 1
 
2.5%
상촌 1
 
2.5%

Length

2023-12-12T07:57:33.415864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영동 12
30.0%
학산 10
25.0%
황간 5
12.5%
용화 3
 
7.5%
매곡 2
 
5.0%
심천 2
 
5.0%
양산 2
 
5.0%
추풍령 1
 
2.5%
양강 1
 
2.5%
상촌 1
 
2.5%

주 소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T07:57:33.653237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length8.125
Min length6

Characters and Unicode

Total characters325
Distinct characters79
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row영동황간로 662
2nd row서산동길 76
3rd row모산길 126
4th row대학로 310 창업보육센터 1층
5th row중가길 30-12
ValueCountFrequency (%)
서산동길 2
 
2.4%
죽촌리길 2
 
2.4%
대학로 2
 
2.4%
유전장척길 2
 
2.4%
산막골길 2
 
2.4%
영동황간로 1
 
1.2%
50-42 1
 
1.2%
53-23 1
 
1.2%
호탄길 1
 
1.2%
45 1
 
1.2%
Other values (67) 67
81.7%
2023-12-12T07:57:34.003367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
12.9%
길 33
 
10.2%
1 32
 
9.8%
2 25
 
7.7%
3 16
 
4.9%
- 14
 
4.3%
4 10
 
3.1%
0 10
 
3.1%
5 9
 
2.8%
6 8
 
2.5%
Other values (69) 126
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146
44.9%
Decimal Number 123
37.8%
Space Separator 42
 
12.9%
Dash Punctuation 14
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 33
22.6%
산 7
 
4.8%
동 5
 
3.4%
리 5
 
3.4%
로 5
 
3.4%
서 4
 
2.7%
곡 4
 
2.7%
촌 3
 
2.1%
대 3
 
2.1%
유 3
 
2.1%
Other values (57) 74
50.7%
Decimal Number
ValueCountFrequency (%)
1 32
26.0%
2 25
20.3%
3 16
13.0%
4 10
 
8.1%
0 10
 
8.1%
5 9
 
7.3%
6 8
 
6.5%
9 6
 
4.9%
7 5
 
4.1%
8 2
 
1.6%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 179
55.1%
Hangul 146
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 33
22.6%
산 7
 
4.8%
동 5
 
3.4%
리 5
 
3.4%
로 5
 
3.4%
서 4
 
2.7%
곡 4
 
2.7%
촌 3
 
2.1%
대 3
 
2.1%
유 3
 
2.1%
Other values (57) 74
50.7%
Common
ValueCountFrequency (%)
42
23.5%
1 32
17.9%
2 25
14.0%
3 16
 
8.9%
- 14
 
7.8%
4 10
 
5.6%
0 10
 
5.6%
5 9
 
5.0%
6 8
 
4.5%
9 6
 
3.4%
Other values (2) 7
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 179
55.1%
Hangul 146
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
23.5%
1 32
17.9%
2 25
14.0%
3 16
 
8.9%
- 14
 
7.8%
4 10
 
5.6%
0 10
 
5.6%
5 9
 
5.0%
6 8
 
4.5%
9 6
 
3.4%
Other values (2) 7
 
3.9%
Hangul
ValueCountFrequency (%)
길 33
22.6%
산 7
 
4.8%
동 5
 
3.4%
리 5
 
3.4%
로 5
 
3.4%
서 4
 
2.7%
곡 4
 
2.7%
촌 3
 
2.1%
대 3
 
2.1%
유 3
 
2.1%
Other values (57) 74
50.7%

연락처
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing31
Missing (%)77.5%
Memory size452.0 B
2023-12-12T07:57:34.157593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.666667
Min length9

Characters and Unicode

Total characters105
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

Unique9 ?
Unique (%)100.0%

Sample

1st row1577-3203
2nd row043-742-4989
3rd row043-745-4574
4th row043-745-7445
5th row043-744-4680
ValueCountFrequency (%)
1577-3203 1
11.1%
043-742-4989 1
11.1%
043-745-4574 1
11.1%
043-745-7445 1
11.1%
043-744-4680 1
11.1%
043-742-2095 1
11.1%
043-743-2109 1
11.1%
043-744-7702 1
11.1%
043-743-4047 1
11.1%
2023-12-12T07:57:34.432398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 26
24.8%
- 17
16.2%
7 15
14.3%
0 14
13.3%
3 12
11.4%
5 6
 
5.7%
2 6
 
5.7%
9 4
 
3.8%
1 2
 
1.9%
8 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
83.8%
Dash Punctuation 17
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 26
29.5%
7 15
17.0%
0 14
15.9%
3 12
13.6%
5 6
 
6.8%
2 6
 
6.8%
9 4
 
4.5%
1 2
 
2.3%
8 2
 
2.3%
6 1
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 26
24.8%
- 17
16.2%
7 15
14.3%
0 14
13.3%
3 12
11.4%
5 6
 
5.7%
2 6
 
5.7%
9 4
 
3.8%
1 2
 
1.9%
8 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 26
24.8%
- 17
16.2%
7 15
14.3%
0 14
13.3%
3 12
11.4%
5 6
 
5.7%
2 6
 
5.7%
9 4
 
3.8%
1 2
 
1.9%
8 2
 
1.9%

Interactions

2023-12-12T07:57:30.955122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:57:34.526063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번법인명및 농장명대표자상호읍 면주 소연락처
순번1.0001.0001.0001.0000.5411.0001.000
법인명및 농장명1.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.000
상호1.0001.0001.0001.0001.0001.0001.000
읍 면0.5411.0001.0001.0001.0001.0001.000
주 소1.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.000
2023-12-12T07:57:34.614997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번읍 면
순번1.0000.246
읍 면0.2461.000

Missing values

2023-12-12T07:57:31.091213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:57:31.238513image/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

순번법인명및 농장명대표자상호읍 면주 소연락처
01와인코리아윤태림샤토마니영동영동황간로 6621577-3203
12비아들샤토영농조합법인정상근샤또비아들학산서산동길 76043-742-4989
23상모영농조합법인이은자르보까쥬학산모산길 126043-745-4574
34AMS 영동미래농업㈜ 농업회사법인이원근원와인영동대학로 310 창업보육센터 1층043-745-7445
45에덴농장안재홍에덴와인영동중가길 30-12043-744-4680
56컨츄리 농원김마정컨츄리와인영동조현길 30043-742-2095
67도란원안남락샤토미소와인매곡유전장척길 143043-743-2109
78추풍령가족농장조영희추풍령와인추풍령작점로 321-1<NA>
89늘푸른농원박상윤둘레와인학산지내리 1126<NA>
910유스팜유성국포블루와인학산죽촌리길 21<NA>
순번법인명및 농장명대표자상호읍 면주 소연락처
3031매곡유통김진용비노만추매곡유전장척길 99<NA>
3132난곡농장이순덕비노플로리안황간소난곡2길 25<NA>
3233월류원박천명베베와인황간남성동3길 4-14<NA>
3334곡천농장전순표스마일해피학산서곡길 27<NA>
3435영동와인농산물김기성우리와인학산서산동길 62<NA>
3536산막와이너리안성분산막와인영동산막골길 31-31<NA>
3637비가원박현주샤토비가황간황간동로 28<NA>
3738달궁농원김홍식궁와인용화용화1길 92-10<NA>
3839마미농장와이너리정환식추와인영동대학로 221-9<NA>
3940은비식품김종현은비주영동산막골길 39<NA>