Overview

Dataset statistics

Number of variables12
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory101.8 B

Variable types

Numeric1
Categorical6
Text5

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
협회 is highly imbalanced (50.7%)Imbalance
순번 has unique valuesUnique
도로명주소 has unique valuesUnique
성명 has unique valuesUnique
전화번호 has unique valuesUnique
마을명 has unique valuesUnique
특산물 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:09:38.561140
Analysis finished2024-03-14 01:09:39.431706
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-14T10:09:39.486632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2024-03-14T10:09:39.603664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
27 1
 
2.9%
28 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%

시군명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
고창군
5 
김제시
4 
익산시
3 
정읍시
3 
완주군
3 
Other values (8)
17 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row전주시
2nd row군산시
3rd row군산시
4th row익산시
5th row익산시

Common Values

ValueCountFrequency (%)
고창군 5
14.3%
김제시 4
11.4%
익산시 3
8.6%
정읍시 3
8.6%
완주군 3
8.6%
임실군 3
8.6%
순창군 3
8.6%
군산시 2
 
5.7%
진안군 2
 
5.7%
무주군 2
 
5.7%
Other values (3) 5
14.3%

Length

2024-03-14T10:09:39.705834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고창군 5
14.3%
김제시 4
11.4%
익산시 3
8.6%
정읍시 3
8.6%
완주군 3
8.6%
임실군 3
8.6%
순창군 3
8.6%
군산시 2
 
5.7%
진안군 2
 
5.7%
무주군 2
 
5.7%
Other values (3) 5
14.3%

도로명주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T10:09:39.987478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length15.628571
Min length14

Characters and Unicode

Total characters547
Distinct characters109
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 학전길 43(원당동)
2nd row군산시 성산면 깐치멀1길 27
3rd row군산시 옥도면 신시도길 83-6
4th row익산시 망성면 으랭이1길 27
5th row익산시 여산면 용기길 66
ValueCountFrequency (%)
고창군 5
 
3.6%
김제시 4
 
2.9%
임실군 3
 
2.2%
정읍시 3
 
2.2%
27 3
 
2.2%
익산시 3
 
2.2%
완주군 3
 
2.2%
순창군 3
 
2.2%
33 2
 
1.4%
무주군 2
 
1.4%
Other values (103) 108
77.7%
2024-03-14T10:09:40.407156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
 
19.0%
길 29
 
5.3%
면 28
 
5.1%
1 26
 
4.8%
군 24
 
4.4%
3 15
 
2.7%
시 14
 
2.6%
산 14
 
2.6%
2 14
 
2.6%
- 11
 
2.0%
Other values (99) 268
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
60.0%
Space Separator 104
 
19.0%
Decimal Number 102
 
18.6%
Dash Punctuation 11
 
2.0%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 29
 
8.8%
면 28
 
8.5%
군 24
 
7.3%
시 14
 
4.3%
산 14
 
4.3%
창 11
 
3.4%
읍 8
 
2.4%
정 7
 
2.1%
주 7
 
2.1%
안 7
 
2.1%
Other values (85) 179
54.6%
Decimal Number
ValueCountFrequency (%)
1 26
25.5%
3 15
14.7%
2 14
13.7%
5 9
 
8.8%
0 8
 
7.8%
4 8
 
7.8%
6 6
 
5.9%
8 6
 
5.9%
7 5
 
4.9%
9 5
 
4.9%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
60.0%
Common 219
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 29
 
8.8%
면 28
 
8.5%
군 24
 
7.3%
시 14
 
4.3%
산 14
 
4.3%
창 11
 
3.4%
읍 8
 
2.4%
정 7
 
2.1%
주 7
 
2.1%
안 7
 
2.1%
Other values (85) 179
54.6%
Common
ValueCountFrequency (%)
104
47.5%
1 26
 
11.9%
3 15
 
6.8%
2 14
 
6.4%
- 11
 
5.0%
5 9
 
4.1%
0 8
 
3.7%
4 8
 
3.7%
6 6
 
2.7%
8 6
 
2.7%
Other values (4) 12
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
60.0%
ASCII 219
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
104
47.5%
1 26
 
11.9%
3 15
 
6.8%
2 14
 
6.4%
- 11
 
5.0%
5 9
 
4.1%
0 8
 
3.7%
4 8
 
3.7%
6 6
 
2.7%
8 6
 
2.7%
Other values (4) 12
 
5.5%
Hangul
ValueCountFrequency (%)
길 29
 
8.8%
면 28
 
8.5%
군 24
 
7.3%
시 14
 
4.3%
산 14
 
4.3%
창 11
 
3.4%
읍 8
 
2.4%
정 7
 
2.1%
주 7
 
2.1%
안 7
 
2.1%
Other values (85) 179
54.6%

성명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T10:09:40.581998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters105
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row김종록
2nd row서헌익
3rd row박춘래
4th row소선영
5th row문형옥
ValueCountFrequency (%)
김종록 1
 
2.9%
정도화 1
 
2.9%
이재욱 1
 
2.9%
송병주 1
 
2.9%
조용훈 1
 
2.9%
오홍섭 1
 
2.9%
최현정 1
 
2.9%
김정현 1
 
2.9%
박희축 1
 
2.9%
라동주 1
 
2.9%
Other values (25) 25
71.4%
2024-03-14T10:09:40.855250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
7.6%
이 4
 
3.8%
박 4
 
3.8%
주 4
 
3.8%
재 3
 
2.9%
최 3
 
2.9%
정 3
 
2.9%
오 2
 
1.9%
기 2
 
1.9%
성 2
 
1.9%
Other values (53) 70
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
7.6%
이 4
 
3.8%
박 4
 
3.8%
주 4
 
3.8%
재 3
 
2.9%
최 3
 
2.9%
정 3
 
2.9%
오 2
 
1.9%
기 2
 
1.9%
성 2
 
1.9%
Other values (53) 70
66.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
7.6%
이 4
 
3.8%
박 4
 
3.8%
주 4
 
3.8%
재 3
 
2.9%
최 3
 
2.9%
정 3
 
2.9%
오 2
 
1.9%
기 2
 
1.9%
성 2
 
1.9%
Other values (53) 70
66.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
7.6%
이 4
 
3.8%
박 4
 
3.8%
주 4
 
3.8%
재 3
 
2.9%
최 3
 
2.9%
정 3
 
2.9%
오 2
 
1.9%
기 2
 
1.9%
성 2
 
1.9%
Other values (53) 70
66.7%

전화번호
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T10:09:41.059259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters420
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

Unique35 ?
Unique (%)100.0%

Sample

1st row063-221-4161
2nd row063-453-6186
3rd row063-463-4016
4th row063-859-3837
5th row063-831-1168
ValueCountFrequency (%)
063-221-4161 1
 
2.9%
063-322-9988 1
 
2.9%
063-351-3201 1
 
2.9%
063-351-3077 1
 
2.9%
063-624-1131 1
 
2.9%
063-642-7076 1
 
2.9%
063-643-3700 1
 
2.9%
063-653-0703 1
 
2.9%
063-322-8001 1
 
2.9%
063-652-0209 1
 
2.9%
Other values (25) 25
71.4%
2024-03-14T10:09:41.503090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 71
16.9%
- 70
16.7%
6 66
15.7%
0 60
14.3%
4 27
 
6.4%
5 26
 
6.2%
8 24
 
5.7%
2 22
 
5.2%
1 21
 
5.0%
7 17
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.3%
Dash Punctuation 70
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 71
20.3%
6 66
18.9%
0 60
17.1%
4 27
 
7.7%
5 26
 
7.4%
8 24
 
6.9%
2 22
 
6.3%
1 21
 
6.0%
7 17
 
4.9%
9 16
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 71
16.9%
- 70
16.7%
6 66
15.7%
0 60
14.3%
4 27
 
6.4%
5 26
 
6.2%
8 24
 
5.7%
2 22
 
5.2%
1 21
 
5.0%
7 17
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 71
16.9%
- 70
16.7%
6 66
15.7%
0 60
14.3%
4 27
 
6.4%
5 26
 
6.2%
8 24
 
5.7%
2 22
 
5.2%
1 21
 
5.0%
7 17
 
4.0%

마을명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T10:09:41.694138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.3714286
Min length2

Characters and Unicode

Total characters118
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row학전
2nd row깐치멀
3rd row신시도섬
4th row어량
5th row두여
ValueCountFrequency (%)
학전 1
 
2.9%
하늘땅 1
 
2.9%
별헤는 1
 
2.9%
풍물동동 1
 
2.9%
사선녀 1
 
2.9%
박사골 1
 
2.9%
임실치즈 1
 
2.9%
전통고추장 1
 
2.9%
호롱불 1
 
2.9%
물통골 1
 
2.9%
Other values (25) 25
71.4%
2024-03-14T10:09:41.961752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
골 5
 
4.2%
고 4
 
3.4%
산 4
 
3.4%
동 4
 
3.4%
전 3
 
2.5%
호 3
 
2.5%
정 3
 
2.5%
사 3
 
2.5%
두 3
 
2.5%
대 2
 
1.7%
Other values (71) 84
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 5
 
4.2%
고 4
 
3.4%
산 4
 
3.4%
동 4
 
3.4%
전 3
 
2.5%
호 3
 
2.5%
정 3
 
2.5%
사 3
 
2.5%
두 3
 
2.5%
대 2
 
1.7%
Other values (71) 84
71.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 5
 
4.2%
고 4
 
3.4%
산 4
 
3.4%
동 4
 
3.4%
전 3
 
2.5%
호 3
 
2.5%
정 3
 
2.5%
사 3
 
2.5%
두 3
 
2.5%
대 2
 
1.7%
Other values (71) 84
71.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
골 5
 
4.2%
고 4
 
3.4%
산 4
 
3.4%
동 4
 
3.4%
전 3
 
2.5%
호 3
 
2.5%
정 3
 
2.5%
사 3
 
2.5%
두 3
 
2.5%
대 2
 
1.7%
Other values (71) 84
71.2%

협회
Categorical

IMBALANCE 

Distinct10
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
-
26 
자문위원
 
1
군산, 익산 권역회의
 
1
김제, 정읍권 이사
 
1
총무 이사
 
1
Other values (5)
5 

Length

Max length11
Median length1
Mean length2.3428571
Min length1

Unique

Unique9 ?
Unique (%)25.7%

Sample

1st row-
2nd row자문위원
3rd row군산, 익산 권역회의
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 26
74.3%
자문위원 1
 
2.9%
군산, 익산 권역회의 1
 
2.9%
김제, 정읍권 이사 1
 
2.9%
총무 이사 1
 
2.9%
회장 1
 
2.9%
전북 협회 감사 1
 
2.9%
권역 이사 1
 
2.9%
고창, 부안 이사 1
 
2.9%
감사 1
 
2.9%

Length

2024-03-14T10:09:42.105802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:09:42.295865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26
57.8%
이사 4
 
8.9%
감사 2
 
4.4%
자문위원 1
 
2.2%
군산 1
 
2.2%
익산 1
 
2.2%
권역회의 1
 
2.2%
김제 1
 
2.2%
정읍권 1
 
2.2%
총무 1
 
2.2%
Other values (6) 6
 
13.3%

특산물
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T10:09:42.557610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length11.628571
Min length1

Characters and Unicode

Total characters407
Distinct characters126
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

Unique35 ?
Unique (%)100.0%

Sample

1st row청국장, 두부, 한과
2nd row주박장아찌, 메론, 장아찌
3rd row바지락, 꽃게장, 갯벌체험
4th row젓갈,장아찌, 강낭콩,고추
5th row메론, 파프리카, 목이버섯
ValueCountFrequency (%)
한과 5
 
5.1%
고추 3
 
3.1%
누룽지 3
 
3.1%
벌꿀 3
 
3.1%
배 3
 
3.1%
사과 3
 
3.1%
메론 2
 
2.0%
된장 2
 
2.0%
참기름 2
 
2.0%
고구마 2
 
2.0%
Other values (65) 70
71.4%
2024-03-14T10:09:42.865766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 65
 
16.0%
63
 
15.5%
과 11
 
2.7%
고 11
 
2.7%
장 9
 
2.2%
리 7
 
1.7%
자 6
 
1.5%
주 6
 
1.5%
한 6
 
1.5%
지 6
 
1.5%
Other values (116) 217
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 278
68.3%
Other Punctuation 65
 
16.0%
Space Separator 63
 
15.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 11
 
4.0%
고 11
 
4.0%
장 9
 
3.2%
리 7
 
2.5%
자 6
 
2.2%
주 6
 
2.2%
한 6
 
2.2%
지 6
 
2.2%
사 6
 
2.2%
추 5
 
1.8%
Other values (113) 205
73.7%
Other Punctuation
ValueCountFrequency (%)
, 65
100.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 278
68.3%
Common 129
31.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 11
 
4.0%
고 11
 
4.0%
장 9
 
3.2%
리 7
 
2.5%
자 6
 
2.2%
주 6
 
2.2%
한 6
 
2.2%
지 6
 
2.2%
사 6
 
2.2%
추 5
 
1.8%
Other values (113) 205
73.7%
Common
ValueCountFrequency (%)
, 65
50.4%
63
48.8%
- 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 278
68.3%
ASCII 129
31.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 65
50.4%
63
48.8%
- 1
 
0.8%
Hangul
ValueCountFrequency (%)
과 11
 
4.0%
고 11
 
4.0%
장 9
 
3.2%
리 7
 
2.5%
자 6
 
2.2%
주 6
 
2.2%
한 6
 
2.2%
지 6
 
2.2%
사 6
 
2.2%
추 5
 
1.8%
Other values (113) 205
73.7%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
정보화총괄과
35 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보화총괄과 35
100.0%

Length

2024-03-14T10:09:42.968500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:09:43.044099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보화총괄과 35
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
공개
35 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 35
100.0%

Length

2024-03-14T10:09:43.121144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:09:43.194290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 35
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2017.03
35 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017.03
2nd row2017.03
3rd row2017.03
4th row2017.03
5th row2017.03

Common Values

ValueCountFrequency (%)
2017.03 35
100.0%

Length

2024-03-14T10:09:43.279735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:09:43.369683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017.03 35
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
1년
35 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 35
100.0%

Length

2024-03-14T10:09:43.478342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:09:43.559220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 35
100.0%

Interactions

2024-03-14T10:09:38.922251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:09:43.610433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명도로명주소성명전화번호마을명협회특산물
순번1.0000.8871.0001.0001.0001.0000.0001.000
시군명0.8871.0001.0001.0001.0001.0000.4261.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
성명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
마을명1.0001.0001.0001.0001.0001.0001.0001.000
협회0.0000.4261.0001.0001.0001.0001.0001.000
특산물1.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T10:09:43.698577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명협회
시군명1.0000.138
협회0.1381.000
2024-03-14T10:09:43.787677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명협회
순번1.0000.6330.000
시군명0.6331.0000.138
협회0.0000.1381.000

Missing values

2024-03-14T10:09:39.263525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:09:39.382662image/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

순번시군명도로명주소성명전화번호마을명협회특산물자료출처공개여부작성일갱신주기
01전주시전주시 완산구 학전길 43(원당동)김종록063-221-4161학전-청국장, 두부, 한과정보화총괄과공개2017.031년
12군산시군산시 성산면 깐치멀1길 27서헌익063-453-6186깐치멀자문위원주박장아찌, 메론, 장아찌정보화총괄과공개2017.031년
23군산시군산시 옥도면 신시도길 83-6박춘래063-463-4016신시도섬군산, 익산 권역회의바지락, 꽃게장, 갯벌체험정보화총괄과공개2017.031년
34익산시익산시 망성면 으랭이1길 27소선영063-859-3837어량-젓갈,장아찌, 강낭콩,고추정보화총괄과공개2017.031년
45익산시익산시 여산면 용기길 66문형옥063-831-1168두여-메론, 파프리카, 목이버섯정보화총괄과공개2017.031년
56익산시익산시 성당면 두동길 15박재열063-862-8600두동-편백베게, 친환경쌀, 숙박정보화총괄과공개2017.031년
67정읍시정읍시 대석1길 13-16최경렬063-532-5949내장산김제, 정읍권 이사복분자주, 와인, 한과정보화총괄과공개2017.031년
78정읍시정읍시 산내면 능교3길 12허재원063-538-6442옥정호청정총무 이사벌꿀, 표고버섯, 참기름정보화총괄과공개2017.031년
89정읍시정읍시 정우면 대정1길 27이기오063-537-8608대정유기농녹색-여주차, 여주환, 한과정보화총괄과공개2017.031년
910김제시김제시 용지면 예촌3길 33이철용063-545-8750황토-군고구마말랭이, 포도정보화총괄과공개2017.031년
순번시군명도로명주소성명전화번호마을명협회특산물자료출처공개여부작성일갱신주기
2526순창군순창군 순창읍 민속마을길 55김정현063-653-0703전통고추장-고추장, 된장, 장아찌정보화총괄과공개2017.031년
2627순창군순창군 구림면 이암길 18-10라동주063-652-0209물통골-밤, 한우, 블루베리정보화총괄과공개2017.031년
2728순창군순창군 쌍치면 청정로 580강춘성063-652-4321산내들-고추, 여주, 단호박정보화총괄과공개2017.031년
2829고창군고창군 심원면 서전길 30권영주063-564-8831하전-참기름, 참께, 갯벌체험정보화총괄과공개2017.031년
2930고창군고창군 아산면 성기길 80-5김병선063-564-2499성기복분자고창, 부안 이사복분자, 고구마, 검정콩정보화총괄과공개2017.031년
3031고창군고창군 공음면 두암안길 9최종훈063-563-8066고사리-벌꿀, 찰보리, 미숫가루정보화총괄과공개2017.031년
3132고창군고창군 고창읍 도산1길 42김형택063-563-7299고인동--정보화총괄과공개2017.031년
3233고창군고창군 아산면 반암안길 23-7김상신063-564-1153반암감사블루베리즙, 잼, 요거트종균정보화총괄과공개2017.031년
3334부안군부안군 진서면 운호길 29김성구063-584-7366구름호수-돼지감자, 여주, 울금정보화총괄과공개2017.031년
3435부안군부안군 줄포면 후촌길 67조순길063-583-3099후촌갈대숲-젓갈, 고추, 미니양파정보화총괄과공개2017.031년