Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory51.3 B

Variable types

Numeric1
Text3
Categorical1
DateTime1

Dataset

Description경상북도 영덕군에 등록되어 있는 농업 작목반 현황으로 작목반 명칭, 소재지, 주요생산품 등 정보를 제공하고자 합니다.
Author경상북도 영덕군
URLhttps://www.data.go.kr/data/15068307/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
번호 has unique valuesUnique
작목반명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:52:55.437760
Analysis finished2023-12-12 06:52:56.483616
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T15:52:56.561756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2023-12-12T15:52:56.707162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

작목반명칭
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T15:52:56.978466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.7017544
Min length4

Characters and Unicode

Total characters496
Distinct characters136
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

Unique57 ?
Unique (%)100.0%

Sample

1st row해풍고구마작목반
2nd row구미복숭아작목반
3rd row영덕단감작목반
4th row화림고구마작목반
5th row영덕과채작목반
ValueCountFrequency (%)
영덕군 2
 
3.3%
해풍고구마작목반 1
 
1.6%
장영탁(gap인증농가 1
 
1.6%
민속궐채작목반 1
 
1.6%
명동산과수작목반 1
 
1.6%
신안마을회영농조합법인 1
 
1.6%
영덕오십천포도작목반 1
 
1.6%
지품거봉포도작목반 1
 
1.6%
지품뫼들내포도작목반 1
 
1.6%
영덕사과발전연구회 1
 
1.6%
Other values (50) 50
82.0%
2023-12-12T15:52:57.479882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
작 36
 
7.3%
목 36
 
7.3%
반 36
 
7.3%
영 26
 
5.2%
덕 18
 
3.6%
농 13
 
2.6%
아 12
 
2.4%
복 11
 
2.2%
숭 11
 
2.2%
사 10
 
2.0%
Other values (126) 287
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 476
96.0%
Uppercase Letter 9
 
1.8%
Space Separator 6
 
1.2%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
작 36
 
7.6%
목 36
 
7.6%
반 36
 
7.6%
영 26
 
5.5%
덕 18
 
3.8%
농 13
 
2.7%
아 12
 
2.5%
복 11
 
2.3%
숭 11
 
2.3%
사 10
 
2.1%
Other values (117) 267
56.1%
Uppercase Letter
ValueCountFrequency (%)
P 3
33.3%
G 2
22.2%
A 2
22.2%
M 1
 
11.1%
I 1
 
11.1%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 476
96.0%
Common 11
 
2.2%
Latin 9
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
작 36
 
7.6%
목 36
 
7.6%
반 36
 
7.6%
영 26
 
5.5%
덕 18
 
3.8%
농 13
 
2.7%
아 12
 
2.5%
복 11
 
2.3%
숭 11
 
2.3%
사 10
 
2.1%
Other values (117) 267
56.1%
Latin
ValueCountFrequency (%)
P 3
33.3%
G 2
22.2%
A 2
22.2%
M 1
 
11.1%
I 1
 
11.1%
Common
ValueCountFrequency (%)
6
54.5%
) 2
 
18.2%
( 2
 
18.2%
1 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 476
96.0%
ASCII 20
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
작 36
 
7.6%
목 36
 
7.6%
반 36
 
7.6%
영 26
 
5.5%
덕 18
 
3.8%
농 13
 
2.7%
아 12
 
2.5%
복 11
 
2.3%
숭 11
 
2.3%
사 10
 
2.1%
Other values (117) 267
56.1%
ASCII
ValueCountFrequency (%)
6
30.0%
P 3
15.0%
) 2
 
10.0%
( 2
 
10.0%
G 2
 
10.0%
A 2
 
10.0%
1 1
 
5.0%
M 1
 
5.0%
I 1
 
5.0%

대표자
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T15:52:57.772452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0175439
Min length2

Characters and Unicode

Total characters172
Distinct characters79
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

Unique55 ?
Unique (%)96.5%

Sample

1st row권찬기
2nd row함수광
3rd row김석기
4th row강창호
5th row이춘욱
ValueCountFrequency (%)
박임식 2
 
3.5%
권찬기 1
 
1.8%
김태유 1
 
1.8%
권영해 1
 
1.8%
김진철 1
 
1.8%
정진태 1
 
1.8%
김인식 1
 
1.8%
민경호 1
 
1.8%
신무남 1
 
1.8%
김종성 1
 
1.8%
Other values (46) 46
80.7%
2023-12-12T15:52:58.221837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
8.1%
박 7
 
4.1%
신 7
 
4.1%
이 6
 
3.5%
상 5
 
2.9%
영 5
 
2.9%
권 4
 
2.3%
진 4
 
2.3%
임 4
 
2.3%
태 3
 
1.7%
Other values (69) 113
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
98.8%
Space Separator 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
8.2%
박 7
 
4.1%
신 7
 
4.1%
이 6
 
3.5%
상 5
 
2.9%
영 5
 
2.9%
권 4
 
2.4%
진 4
 
2.4%
임 4
 
2.4%
태 3
 
1.8%
Other values (68) 111
65.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
98.8%
Common 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
8.2%
박 7
 
4.1%
신 7
 
4.1%
이 6
 
3.5%
상 5
 
2.9%
영 5
 
2.9%
권 4
 
2.4%
진 4
 
2.4%
임 4
 
2.4%
태 3
 
1.8%
Other values (68) 111
65.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
98.8%
ASCII 2
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
8.2%
박 7
 
4.1%
신 7
 
4.1%
이 6
 
3.5%
상 5
 
2.9%
영 5
 
2.9%
권 4
 
2.4%
진 4
 
2.4%
임 4
 
2.4%
태 3
 
1.8%
Other values (68) 111
65.3%
ASCII
ValueCountFrequency (%)
2
100.0%

소재지주소
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T15:52:58.597727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length19.140351
Min length17

Characters and Unicode

Total characters1091
Distinct characters88
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

Unique55 ?
Unique (%)96.5%

Sample

1st row경북 영덕군 영덕읍 화수길 12-14
2nd row경북 영덕군 영덕읍 경동로 8078
3rd row경북 영덕군 영덕읍 덕곡길 53-3
4th row경북 영덕군 영덕읍 우곡길 43-1
5th row경북 영덕군 영덕읍 덕곡2길 24-1
ValueCountFrequency (%)
경북 57
19.9%
영덕군 57
19.9%
지품면 15
 
5.2%
영덕읍 11
 
3.8%
창수면 9
 
3.1%
경동로 6
 
2.1%
달산면 6
 
2.1%
강구면 5
 
1.7%
병곡면 3
 
1.0%
영해면 3
 
1.0%
Other values (100) 115
40.1%
2023-12-12T15:52:59.057520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
230
21.1%
영 73
 
6.7%
덕 71
 
6.5%
경 63
 
5.8%
군 57
 
5.2%
북 57
 
5.2%
1 48
 
4.4%
면 46
 
4.2%
길 39
 
3.6%
2 30
 
2.7%
Other values (78) 377
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
59.0%
Space Separator 230
 
21.1%
Decimal Number 194
 
17.8%
Dash Punctuation 23
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 73
 
11.3%
덕 71
 
11.0%
경 63
 
9.8%
군 57
 
8.9%
북 57
 
8.9%
면 46
 
7.1%
길 39
 
6.1%
지 16
 
2.5%
품 15
 
2.3%
로 14
 
2.2%
Other values (66) 193
30.0%
Decimal Number
ValueCountFrequency (%)
1 48
24.7%
2 30
15.5%
3 19
 
9.8%
8 18
 
9.3%
7 16
 
8.2%
6 16
 
8.2%
4 14
 
7.2%
5 13
 
6.7%
0 12
 
6.2%
9 8
 
4.1%
Space Separator
ValueCountFrequency (%)
230
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
59.0%
Common 447
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 73
 
11.3%
덕 71
 
11.0%
경 63
 
9.8%
군 57
 
8.9%
북 57
 
8.9%
면 46
 
7.1%
길 39
 
6.1%
지 16
 
2.5%
품 15
 
2.3%
로 14
 
2.2%
Other values (66) 193
30.0%
Common
ValueCountFrequency (%)
230
51.5%
1 48
 
10.7%
2 30
 
6.7%
- 23
 
5.1%
3 19
 
4.3%
8 18
 
4.0%
7 16
 
3.6%
6 16
 
3.6%
4 14
 
3.1%
5 13
 
2.9%
Other values (2) 20
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
59.0%
ASCII 447
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
230
51.5%
1 48
 
10.7%
2 30
 
6.7%
- 23
 
5.1%
3 19
 
4.3%
8 18
 
4.0%
7 16
 
3.6%
6 16
 
3.6%
4 14
 
3.1%
5 13
 
2.9%
Other values (2) 20
 
4.5%
Hangul
ValueCountFrequency (%)
영 73
 
11.3%
덕 71
 
11.0%
경 63
 
9.8%
군 57
 
8.9%
북 57
 
8.9%
면 46
 
7.1%
길 39
 
6.1%
지 16
 
2.5%
품 15
 
2.3%
로 14
 
2.2%
Other values (66) 193
30.0%

주요생산품
Categorical

Distinct25
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Memory size588.0 B
복숭아
14 
사과
8 
포도
4 
고구마
3 
단감
3 
Other values (20)
25 

Length

Max length7
Median length5
Mean length2.6666667
Min length1

Unique

Unique17 ?
Unique (%)29.8%

Sample

1st row고구마
2nd row복숭아
3rd row단감
4th row고구마
5th row호박

Common Values

ValueCountFrequency (%)
복숭아 14
24.6%
사과 8
14.0%
포도 4
 
7.0%
고구마 3
 
5.3%
단감 3
 
5.3%
토마토 3
 
5.3%
배 3
 
5.3%
고사리 2
 
3.5%
비트 1
 
1.8%
호박 1
 
1.8%
Other values (15) 15
26.3%

Length

2023-12-12T15:52:59.201727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
복숭아 14
24.1%
사과 8
13.8%
포도 4
 
6.9%
고구마 3
 
5.2%
단감 3
 
5.2%
토마토 3
 
5.2%
배 3
 
5.2%
고사리 2
 
3.4%
한과 1
 
1.7%
절임배추 1
 
1.7%
Other values (16) 16
27.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2022-08-25 00:00:00
Maximum2022-08-25 00:00:00
2023-12-12T15:52:59.300438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:52:59.399699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:52:55.825882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:52:59.467547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호작목반명칭대표자소재지주소주요생산품
번호1.0001.0000.9280.9280.392
작목반명칭1.0001.0001.0001.0001.000
대표자0.9281.0001.0001.0000.993
소재지주소0.9281.0001.0001.0000.993
주요생산품0.3921.0000.9930.9931.000
2023-12-12T15:52:59.570444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호주요생산품
번호1.0000.127
주요생산품0.1271.000

Missing values

2023-12-12T15:52:56.285369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:52:56.420469image/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

번호작목반명칭대표자소재지주소주요생산품데이터기준일자
01해풍고구마작목반권찬기경북 영덕군 영덕읍 화수길 12-14고구마2022-08-25
12구미복숭아작목반함수광경북 영덕군 영덕읍 경동로 8078복숭아2022-08-25
23영덕단감작목반김석기경북 영덕군 영덕읍 덕곡길 53-3단감2022-08-25
34화림고구마작목반강창호경북 영덕군 영덕읍 우곡길 43-1고구마2022-08-25
45영덕과채작목반이춘욱경북 영덕군 영덕읍 덕곡2길 24-1호박2022-08-25
56화개복숭아작목반신영오경북 영덕군 영덕읍 구미1길 16-17복숭아2022-08-25
67덕곡리복숭아작목반안창희경북 영덕군 영덕읍 덕곡길 34복숭아2022-08-25
78영덕사과작목반신만섭경북 영덕군 영덕읍 경동로 8295-10사과2022-08-25
89영덕군버섯발전연구회김무한경북 영덕군 영덕읍 천전길 86-11느타리버섯2022-08-25
910해오름자두작목반윤점락경북 영덕군 영덕읍 우곡리 개나리아파트 가동 407호자두2022-08-25
번호작목반명칭대표자소재지주소주요생산품데이터기준일자
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