Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory972.0 B
Average record size in memory46.3 B

Variable types

Text4
Categorical1

Dataset

Description광주광역시 광산구 농업 작목반 현황(작목반명, 소재지주소, 생산품, 생산량 등) 입니다.
Author광주광역시 광산구
URLhttps://www.data.go.kr/data/15068540/fileData.do

Alerts

기준일자 has constant value ""Constant
작목반명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:13:22.449640
Analysis finished2023-12-12 03:13:22.961319
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

작목반명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T12:13:23.140206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.4285714
Min length4

Characters and Unicode

Total characters135
Distinct characters51
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

Unique21 ?
Unique (%)100.0%

Sample

1st row팽팽이가지공선출하회
2nd row토마토공선출하회
3rd row고추공선출하회
4th row산동교 작목반
5th row신창 작목반
ValueCountFrequency (%)
작목반 3
 
12.5%
팽팽이가지공선출하회 1
 
4.2%
돌미나리작목반 1
 
4.2%
삼오작목반 1
 
4.2%
죽산작목반 1
 
4.2%
빛찬들가지공선회 1
 
4.2%
빛찬들토마토공선회 1
 
4.2%
평지작목반 1
 
4.2%
평동작목반 1
 
4.2%
친농작목반 1
 
4.2%
Other values (12) 12
50.0%
2023-12-12T12:13:23.609196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
목 16
 
11.9%
작 16
 
11.9%
반 15
 
11.1%
회 6
 
4.4%
공 5
 
3.7%
선 5
 
3.7%
토 4
 
3.0%
쌀 3
 
2.2%
3
 
2.2%
하 3
 
2.2%
Other values (41) 59
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
97.8%
Space Separator 3
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
목 16
 
12.1%
작 16
 
12.1%
반 15
 
11.4%
회 6
 
4.5%
공 5
 
3.8%
선 5
 
3.8%
토 4
 
3.0%
쌀 3
 
2.3%
하 3
 
2.3%
출 3
 
2.3%
Other values (40) 56
42.4%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132
97.8%
Common 3
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
목 16
 
12.1%
작 16
 
12.1%
반 15
 
11.4%
회 6
 
4.5%
공 5
 
3.8%
선 5
 
3.8%
토 4
 
3.0%
쌀 3
 
2.3%
하 3
 
2.3%
출 3
 
2.3%
Other values (40) 56
42.4%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132
97.8%
ASCII 3
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
목 16
 
12.1%
작 16
 
12.1%
반 15
 
11.4%
회 6
 
4.5%
공 5
 
3.8%
선 5
 
3.8%
토 4
 
3.0%
쌀 3
 
2.3%
하 3
 
2.3%
출 3
 
2.3%
Other values (40) 56
42.4%
ASCII
ValueCountFrequency (%)
3
100.0%

소재지주소
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T12:13:23.848094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.761905
Min length15

Characters and Unicode

Total characters394
Distinct characters41
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

Unique9 ?
Unique (%)42.9%

Sample

1st row광주광역시 광산구 내상로 3
2nd row광주광역시 광산구 내상로 3
3rd row광주광역시 광산구 내상로 3
4th row광주광역시 광산구 장신로 153
5th row광주광역시 광산구 장신로 153
ValueCountFrequency (%)
광주광역시 21
23.3%
광산구 21
23.3%
평동로 5
 
5.6%
800번길 5
 
5.6%
16 4
 
4.4%
내상로 3
 
3.3%
3 3
 
3.3%
장신로 3
 
3.3%
153 3
 
3.3%
대촌길 2
 
2.2%
Other values (18) 20
22.2%
2023-12-12T12:13:24.254581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
17.5%
광 63
16.0%
산 23
 
5.8%
구 21
 
5.3%
주 21
 
5.3%
시 21
 
5.3%
역 21
 
5.3%
로 15
 
3.8%
1 15
 
3.8%
0 13
 
3.3%
Other values (31) 112
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 249
63.2%
Decimal Number 70
 
17.8%
Space Separator 69
 
17.5%
Dash Punctuation 6
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 63
25.3%
산 23
 
9.2%
구 21
 
8.4%
주 21
 
8.4%
시 21
 
8.4%
역 21
 
8.4%
로 15
 
6.0%
길 12
 
4.8%
동 6
 
2.4%
번 6
 
2.4%
Other values (20) 40
16.1%
Decimal Number
ValueCountFrequency (%)
1 15
21.4%
0 13
18.6%
3 10
14.3%
8 10
14.3%
2 6
 
8.6%
5 4
 
5.7%
4 4
 
5.7%
7 4
 
5.7%
6 4
 
5.7%
Space Separator
ValueCountFrequency (%)
69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 249
63.2%
Common 145
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 63
25.3%
산 23
 
9.2%
구 21
 
8.4%
주 21
 
8.4%
시 21
 
8.4%
역 21
 
8.4%
로 15
 
6.0%
길 12
 
4.8%
동 6
 
2.4%
번 6
 
2.4%
Other values (20) 40
16.1%
Common
ValueCountFrequency (%)
69
47.6%
1 15
 
10.3%
0 13
 
9.0%
3 10
 
6.9%
8 10
 
6.9%
- 6
 
4.1%
2 6
 
4.1%
5 4
 
2.8%
4 4
 
2.8%
7 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 249
63.2%
ASCII 145
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
47.6%
1 15
 
10.3%
0 13
 
9.0%
3 10
 
6.9%
8 10
 
6.9%
- 6
 
4.1%
2 6
 
4.1%
5 4
 
2.8%
4 4
 
2.8%
7 4
 
2.8%
Hangul
ValueCountFrequency (%)
광 63
25.3%
산 23
 
9.2%
구 21
 
8.4%
주 21
 
8.4%
시 21
 
8.4%
역 21
 
8.4%
로 15
 
6.0%
길 12
 
4.8%
동 6
 
2.4%
번 6
 
2.4%
Other values (20) 40
16.1%

주요생산품
Text

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T12:13:24.441253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.2380952
Min length1

Characters and Unicode

Total characters110
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)66.7%

Sample

1st row가지
2nd row방울토마토
3rd row청양
4th row고추
5th row고추, 토마토
ValueCountFrequency (%)
친환경 4
11.4%
가지 4
11.4%
토마토 4
11.4%
고추 4
11.4%
벼 3
8.6%
쌀 3
8.6%
방울토마토 3
8.6%
애호박 2
 
5.7%
딸기 2
 
5.7%
흑토마토 1
 
2.9%
Other values (5) 5
14.3%
2023-12-12T12:13:24.769710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
토 16
14.5%
14
 
12.7%
, 9
 
8.2%
마 8
 
7.3%
친 4
 
3.6%
추 4
 
3.6%
고 4
 
3.6%
울 4
 
3.6%
환 4
 
3.6%
방 4
 
3.6%
Other values (21) 39
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
79.1%
Space Separator 14
 
12.7%
Other Punctuation 9
 
8.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
토 16
18.4%
마 8
 
9.2%
친 4
 
4.6%
추 4
 
4.6%
고 4
 
4.6%
울 4
 
4.6%
환 4
 
4.6%
방 4
 
4.6%
지 4
 
4.6%
가 4
 
4.6%
Other values (19) 31
35.6%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
79.1%
Common 23
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
토 16
18.4%
마 8
 
9.2%
친 4
 
4.6%
추 4
 
4.6%
고 4
 
4.6%
울 4
 
4.6%
환 4
 
4.6%
방 4
 
4.6%
지 4
 
4.6%
가 4
 
4.6%
Other values (19) 31
35.6%
Common
ValueCountFrequency (%)
14
60.9%
, 9
39.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
79.1%
ASCII 23
 
20.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
토 16
18.4%
마 8
 
9.2%
친 4
 
4.6%
추 4
 
4.6%
고 4
 
4.6%
울 4
 
4.6%
환 4
 
4.6%
방 4
 
4.6%
지 4
 
4.6%
가 4
 
4.6%
Other values (19) 31
35.6%
ASCII
ValueCountFrequency (%)
14
60.9%
, 9
39.1%

생산량(t)
Text

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T12:13:24.917344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.9047619
Min length2

Characters and Unicode

Total characters82
Distinct characters15
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

Unique13 ?
Unique (%)61.9%

Sample

1st row 미집계
2nd row 미집계
3rd row 미집계
4th row 미집계
5th row 미집계
ValueCountFrequency (%)
미집계 8
38.1%
800 1
 
4.8%
127 1
 
4.8%
1,473 1
 
4.8%
1,694 1
 
4.8%
192 1
 
4.8%
358 1
 
4.8%
207 1
 
4.8%
306 1
 
4.8%
497 1
 
4.8%
Other values (4) 4
19.0%
2023-12-12T12:13:25.224461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
19.5%
미 8
9.8%
집 8
9.8%
계 8
9.8%
7 6
 
7.3%
1 5
 
6.1%
2 5
 
6.1%
4 5
 
6.1%
0 4
 
4.9%
3 4
 
4.9%
Other values (5) 13
15.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
48.8%
Other Letter 24
29.3%
Space Separator 16
 
19.5%
Other Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 6
15.0%
1 5
12.5%
2 5
12.5%
4 5
12.5%
0 4
10.0%
3 4
10.0%
9 4
10.0%
6 3
7.5%
8 2
 
5.0%
5 2
 
5.0%
Other Letter
ValueCountFrequency (%)
미 8
33.3%
집 8
33.3%
계 8
33.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
70.7%
Hangul 24
29.3%

Most frequent character per script

Common
ValueCountFrequency (%)
16
27.6%
7 6
 
10.3%
1 5
 
8.6%
2 5
 
8.6%
4 5
 
8.6%
0 4
 
6.9%
3 4
 
6.9%
9 4
 
6.9%
6 3
 
5.2%
8 2
 
3.4%
Other values (2) 4
 
6.9%
Hangul
ValueCountFrequency (%)
미 8
33.3%
집 8
33.3%
계 8
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
70.7%
Hangul 24
29.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
27.6%
7 6
 
10.3%
1 5
 
8.6%
2 5
 
8.6%
4 5
 
8.6%
0 4
 
6.9%
3 4
 
6.9%
9 4
 
6.9%
6 3
 
5.2%
8 2
 
3.4%
Other values (2) 4
 
6.9%
Hangul
ValueCountFrequency (%)
미 8
33.3%
집 8
33.3%
계 8
33.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2019-12-31
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-12-31
2nd row2019-12-31
3rd row2019-12-31
4th row2019-12-31
5th row2019-12-31

Common Values

ValueCountFrequency (%)
2019-12-31 21
100.0%

Length

2023-12-12T12:13:25.409342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:13:25.898890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-12-31 21
100.0%

Correlations

2023-12-12T12:13:25.988764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작목반명소재지주소주요생산품생산량(t)
작목반명1.0001.0001.0001.000
소재지주소1.0001.0000.9630.888
주요생산품1.0000.9631.0000.000
생산량(t)1.0000.8880.0001.000

Missing values

2023-12-12T12:13:22.762177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:13:22.902325image/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

작목반명소재지주소주요생산품생산량(t)기준일자
0팽팽이가지공선출하회광주광역시 광산구 내상로 3가지미집계2019-12-31
1토마토공선출하회광주광역시 광산구 내상로 3방울토마토미집계2019-12-31
2고추공선출하회광주광역시 광산구 내상로 3청양미집계2019-12-31
3산동교 작목반광주광역시 광산구 장신로 153고추미집계2019-12-31
4신창 작목반광주광역시 광산구 장신로 153고추, 토마토미집계2019-12-31
5운남 작목반광주광역시 광산구 장신로 153토마토, 딸기미집계2019-12-31
6과수작목반광주광역시 광산구 목련로 21번길 20과수미집계2019-12-31
7시설작목반광주광역시 광산구 비아로 185채소미집계2019-12-31
8쌀작목반광주광역시 광산구 고봉로 807쌀8002019-12-31
9딸기작목반광주광역시 광산구 고봉로 807딸기1272019-12-31
작목반명소재지주소주요생산품생산량(t)기준일자
11돌미나리작목반광주광역시 광산구 팽호길 148돌미나리1,6942019-12-31
12친환경쌀작목반광주광역시 광산구 대촌길 27-4친환경 쌀1922019-12-31
13친농작목반광주광역시 광산구 평동로 800번길 16친환경 벼3582019-12-31
14평동작목반광주광역시 광산구 평동로 800번길 16친환경 벼2072019-12-31
15평지작목반광주광역시 광산구 평동로 800번길 16친환경 벼3062019-12-31
16빛찬들토마토공선회광주광역시 광산구 평동로 800번길 41-1방울 토마토4972019-12-31
17빛찬들가지공선회광주광역시 광산구 평동로 800번길 16가지612019-12-31
18죽산작목반광주광역시 광산구 삼도죽산안길 3-3토마토, 고추, 가지2942019-12-31
19삼오작목반광주광역시 광산구 신동산길 131-4가지, 방울토마토, 애호박, 고추5242019-12-31
20삼도친환경쌀재배작목반광주광역시 광산구 삼도봉정길 22-13쌀3772019-12-31