Overview

Dataset statistics

Number of variables11
Number of observations377
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.5 KiB
Average record size in memory88.3 B

Variable types

Categorical8
Text3

Dataset

Description농림업 생산량을 지수화하여 연도별 생산 동향을 측정하고, 농림업 생산금액을 측정하여 생산구조의 변화추이를 파악함
Author농림축산식품부
URLhttps://www.data.go.kr/data/3034961/fileData.do

Alerts

품목별(1) has constant value ""Constant
품목별(3) is highly overall correlated with 품목별(2) and 2 other fieldsHigh correlation
품목별(2) is highly overall correlated with 품목별(3) and 2 other fieldsHigh correlation
품목별(4) is highly overall correlated with 품목별(2) and 2 other fieldsHigh correlation
품목별(5) is highly overall correlated with 품목별(2) and 2 other fieldsHigh correlation
품목별(2) is highly imbalanced (50.4%)Imbalance
품목별(3) is highly imbalanced (50.4%)Imbalance
품목별(4) is highly imbalanced (53.2%)Imbalance
품목별(8) is highly imbalanced (68.3%)Imbalance

Reproduction

Analysis started2024-03-14 10:20:22.690634
Analysis finished2024-03-14 10:20:24.536354
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목별(1)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
농림업
377 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
농림업 377
100.0%

Length

2024-03-14T19:20:24.739807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:20:25.052367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농림업 377
100.0%

품목별(2)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
농업
296 
임업
79 
소계
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소계
2nd row소계
3rd row농업
4th row농업
5th row농업

Common Values

ValueCountFrequency (%)
농업 296
78.5%
임업 79
 
21.0%
소계 2
 
0.5%

Length

2024-03-14T19:20:25.386011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:20:25.713185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농업 296
78.5%
임업 79
 
21.0%
소계 2
 
0.5%

품목별(3)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
농업총계
296 
임업총계
79 
소계
 
2

Length

Max length4
Median length4
Mean length3.9893899
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소계
2nd row소계
3rd row농업총계
4th row농업총계
5th row농업총계

Common Values

ValueCountFrequency (%)
농업총계 296
78.5%
임업총계 79
 
21.0%
소계 2
 
0.5%

Length

2024-03-14T19:20:26.109971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:20:26.464486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농업총계 296
78.5%
임업총계 79
 
21.0%
소계 2
 
0.5%

품목별(4)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
재배업
249 
축잠업
45 
수실
25 
버섯
 
12
약용
 
8
Other values (14)
38 

Length

Max length9
Median length3
Mean length2.8647215
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row소계
2nd row소계
3rd row소계
4th row소계
5th row재배업

Common Values

ValueCountFrequency (%)
재배업 249
66.0%
축잠업 45
 
11.9%
수실 25
 
6.6%
버섯 12
 
3.2%
약용 8
 
2.1%
소계 6
 
1.6%
연료 6
 
1.6%
농용자재 6
 
1.6%
섬유원료(닥나무) 2
 
0.5%
칡뿌리 2
 
0.5%
Other values (9) 16
 
4.2%

Length

2024-03-14T19:20:26.858604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재배업 249
66.0%
축잠업 45
 
11.9%
수실 25
 
6.6%
버섯 12
 
3.2%
약용 8
 
2.1%
소계 6
 
1.6%
연료 6
 
1.6%
농용자재 6
 
1.6%
잔디 2
 
0.5%
산나물 2
 
0.5%
Other values (9) 16
 
4.2%

품목별(5)
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
채소
97 
소계
39 
축산업
37 
과실
36 
식량작물
34 
Other values (32)
134 

Length

Max length6
Median length2
Mean length2.6153846
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
채소 97
25.7%
소계 39
10.3%
축산업 37
 
9.8%
과실 36
 
9.5%
식량작물 34
 
9.0%
약용작물 32
 
8.5%
특용작물 14
 
3.7%
화훼류 14
 
3.7%
버섯 12
 
3.2%
양잠 6
 
1.6%
Other values (27) 56
14.9%

Length

2024-03-14T19:20:27.265196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
채소 97
25.7%
소계 39
10.3%
축산업 37
 
9.8%
과실 36
 
9.5%
식량작물 34
 
9.0%
약용작물 32
 
8.5%
특용작물 14
 
3.7%
화훼류 14
 
3.7%
버섯 12
 
3.2%
양잠 6
 
1.6%
Other values (27) 56
14.9%

품목별(6)
Categorical

Distinct48
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
소계
109 
과채류
34 
엽채류
30 
과실(감제외)
28 
가축
21 
Other values (43)
155 

Length

Max length7
Median length2
Mean length2.862069
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
소계 109
28.9%
과채류 34
 
9.0%
엽채류 30
 
8.0%
과실(감제외) 28
 
7.4%
가축 21
 
5.6%
근채류 17
 
4.5%
축산물 14
 
3.7%
조미채소 12
 
3.2%
맥류 10
 
2.7%
두류 8
 
2.1%
Other values (38) 94
24.9%

Length

2024-03-14T19:20:27.670097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소계 109
28.9%
과채류 34
 
9.0%
엽채류 30
 
8.0%
과실(감제외 28
 
7.4%
가축 21
 
5.6%
근채류 17
 
4.5%
축산물 14
 
3.7%
조미채소 12
 
3.2%
맥류 10
 
2.7%
유지작물 8
 
2.1%
Other values (38) 94
24.9%

품목별(7)
Text

Distinct56
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-14T19:20:28.396501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length2
Mean length3.2997347
Min length1

Characters and Unicode

Total characters1244
Distinct characters86
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

Unique1 ?
Unique (%)0.3%

Sample

1st row소계
2nd row소계
3rd row소계
4th row소계
5th row소계
ValueCountFrequency (%)
소계 201
53.3%
과채류시설재배계 22
 
5.8%
엽채류노지재배계 16
 
4.2%
엽채류시설재배계 12
 
3.2%
근채류노지재배계 11
 
2.9%
과채류노지재배계 10
 
2.7%
한육우 6
 
1.6%
근채류시설재배계 4
 
1.1%
젖소 2
 
0.5%
차 2
 
0.5%
Other values (46) 91
24.1%
2024-03-14T19:20:29.552312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 278
22.3%
소 205
16.5%
배 77
 
6.2%
채 75
 
6.0%
류 75
 
6.0%
재 75
 
6.0%
지 39
 
3.1%
시 38
 
3.1%
설 38
 
3.1%
노 37
 
3.0%
Other values (76) 307
24.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1236
99.4%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 278
22.5%
소 205
16.6%
배 77
 
6.2%
채 75
 
6.1%
류 75
 
6.1%
재 75
 
6.1%
지 39
 
3.2%
시 38
 
3.1%
설 38
 
3.1%
노 37
 
3.0%
Other values (74) 299
24.2%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1236
99.4%
Common 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 278
22.5%
소 205
16.6%
배 77
 
6.2%
채 75
 
6.1%
류 75
 
6.1%
재 75
 
6.1%
지 39
 
3.2%
시 38
 
3.1%
설 38
 
3.1%
노 37
 
3.0%
Other values (74) 299
24.2%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1236
99.4%
ASCII 8
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 278
22.5%
소 205
16.6%
배 77
 
6.2%
채 75
 
6.1%
류 75
 
6.1%
재 75
 
6.1%
지 39
 
3.2%
시 38
 
3.1%
설 38
 
3.1%
노 37
 
3.0%
Other values (74) 299
24.2%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

품목별(8)
Categorical

IMBALANCE 

Distinct25
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
소계
310 
오이
 
4
시금치
 
4
무
 
4
배추
 
4
Other values (20)
51 

Length

Max length4
Median length2
Mean length2.0371353
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
소계 310
82.2%
오이 4
 
1.1%
시금치 4
 
1.1%
무 4
 
1.1%
배추 4
 
1.1%
호박 4
 
1.1%
가지 4
 
1.1%
수박 4
 
1.1%
부추 4
 
1.1%
미나리 4
 
1.1%
Other values (15) 31
 
8.2%

Length

2024-03-14T19:20:29.985889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소계 310
82.2%
가지 4
 
1.1%
오이 4
 
1.1%
상추 4
 
1.1%
미나리 4
 
1.1%
수박 4
 
1.1%
부추 4
 
1.1%
호박 4
 
1.1%
배추 4
 
1.1%
무 4
 
1.1%
Other values (15) 31
 
8.2%

항목
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
생산금액 (십억원)
192 
생산지수
185 

Length

Max length10
Median length10
Mean length7.0557029
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생산지수
2nd row생산금액 (십억원)
3rd row생산지수
4th row생산금액 (십억원)
5th row생산지수

Common Values

ValueCountFrequency (%)
생산금액 (십억원) 192
50.9%
생산지수 185
49.1%

Length

2024-03-14T19:20:30.392623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:20:30.716705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생산금액 192
33.7%
십억원 192
33.7%
생산지수 185
32.5%

2021
Text

Distinct309
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-14T19:20:32.308581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.2228117
Min length1

Characters and Unicode

Total characters1592
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)69.0%

Sample

1st row101.3
2nd row61380
3rd row101.5
4th row59203.7
5th row101.5
ValueCountFrequency (%)
101.5 5
 
1.3%
101.9 4
 
1.1%
4
 
1.1%
92.6 4
 
1.1%
92.3 4
 
1.1%
92.5 3
 
0.8%
103.2 3
 
0.8%
93.5 3
 
0.8%
0 3
 
0.8%
53.6 3
 
0.8%
Other values (299) 341
90.5%
2024-03-14T19:20:34.350907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 325
20.4%
1 245
15.4%
9 137
8.6%
0 123
 
7.7%
5 119
 
7.5%
3 119
 
7.5%
2 109
 
6.8%
4 107
 
6.7%
6 103
 
6.5%
7 103
 
6.5%
Other values (2) 102
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1263
79.3%
Other Punctuation 325
 
20.4%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 245
19.4%
9 137
10.8%
0 123
9.7%
5 119
9.4%
3 119
9.4%
2 109
8.6%
4 107
8.5%
6 103
8.2%
7 103
8.2%
8 98
 
7.8%
Other Punctuation
ValueCountFrequency (%)
. 325
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1592
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 325
20.4%
1 245
15.4%
9 137
8.6%
0 123
 
7.7%
5 119
 
7.5%
3 119
 
7.5%
2 109
 
6.8%
4 107
 
6.7%
6 103
 
6.5%
7 103
 
6.5%
Other values (2) 102
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 325
20.4%
1 245
15.4%
9 137
8.6%
0 123
 
7.7%
5 119
 
7.5%
3 119
 
7.5%
2 109
 
6.8%
4 107
 
6.7%
6 103
 
6.5%
7 103
 
6.5%
Other values (2) 102
 
6.4%

2022
Text

Distinct329
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-03-14T19:20:36.346104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.2599469
Min length1

Characters and Unicode

Total characters1606
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)77.2%

Sample

1st row100.3
2nd row60058.5
3rd row100.5
4th row57904.6
5th row99.3
ValueCountFrequency (%)
7
 
1.9%
0 4
 
1.1%
97.1 3
 
0.8%
86.7 3
 
0.8%
109.7 3
 
0.8%
0.9 2
 
0.5%
0.4 2
 
0.5%
101.9 2
 
0.5%
108.4 2
 
0.5%
96.6 2
 
0.5%
Other values (319) 347
92.0%
2024-03-14T19:20:38.668927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 330
20.5%
1 235
14.6%
9 145
9.0%
2 122
 
7.6%
7 118
 
7.3%
6 113
 
7.0%
5 113
 
7.0%
0 108
 
6.7%
8 108
 
6.7%
3 108
 
6.7%
Other values (2) 106
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1269
79.0%
Other Punctuation 330
 
20.5%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 235
18.5%
9 145
11.4%
2 122
9.6%
7 118
9.3%
6 113
8.9%
5 113
8.9%
0 108
8.5%
8 108
8.5%
3 108
8.5%
4 99
7.8%
Other Punctuation
ValueCountFrequency (%)
. 330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1606
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 330
20.5%
1 235
14.6%
9 145
9.0%
2 122
 
7.6%
7 118
 
7.3%
6 113
 
7.0%
5 113
 
7.0%
0 108
 
6.7%
8 108
 
6.7%
3 108
 
6.7%
Other values (2) 106
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 330
20.5%
1 235
14.6%
9 145
9.0%
2 122
 
7.6%
7 118
 
7.3%
6 113
 
7.0%
5 113
 
7.0%
0 108
 
6.7%
8 108
 
6.7%
3 108
 
6.7%
Other values (2) 106
 
6.6%

Correlations

2024-03-14T19:20:39.049470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별(2)품목별(3)품목별(4)품목별(5)품목별(6)품목별(7)품목별(8)항목
품목별(2)1.0001.0000.9110.8460.7520.0000.0000.000
품목별(3)1.0001.0000.9110.8460.7520.0000.0000.000
품목별(4)0.9110.9111.0000.9270.0000.0000.0000.000
품목별(5)0.8460.8460.9271.0000.8920.0000.0000.000
품목별(6)0.7520.7520.0000.8921.0000.8950.0000.000
품목별(7)0.0000.0000.0000.0000.8951.0000.4180.000
품목별(8)0.0000.0000.0000.0000.0000.4181.0000.000
항목0.0000.0000.0000.0000.0000.0000.0001.000
2024-03-14T19:20:39.250091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목품목별(3)품목별(2)품목별(8)품목별(6)품목별(4)품목별(5)
항목1.0000.0000.0000.0000.0000.0000.000
품목별(3)0.0001.0001.0000.0000.4610.7820.619
품목별(2)0.0001.0001.0000.0000.4610.7820.619
품목별(8)0.0000.0000.0001.0000.0000.0000.000
품목별(6)0.0000.4610.4610.0001.0000.0000.349
품목별(4)0.0000.7820.7820.0000.0001.0000.527
품목별(5)0.0000.6190.6190.0000.3490.5271.000
2024-03-14T19:20:39.520295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별(2)품목별(3)품목별(4)품목별(5)품목별(6)품목별(8)항목
품목별(2)1.0001.0000.7820.6190.4610.0000.000
품목별(3)1.0001.0000.7820.6190.4610.0000.000
품목별(4)0.7820.7821.0000.5270.0000.0000.000
품목별(5)0.6190.6190.5271.0000.3490.0000.000
품목별(6)0.4610.4610.0000.3491.0000.0000.000
품목별(8)0.0000.0000.0000.0000.0001.0000.000
항목0.0000.0000.0000.0000.0000.0001.000

Missing values

2024-03-14T19:20:23.836330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:20:24.335628image/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

품목별(1)품목별(2)품목별(3)품목별(4)품목별(5)품목별(6)품목별(7)품목별(8)항목20212022
0농림업소계소계소계소계소계소계소계생산지수101.3100.3
1농림업소계소계소계소계소계소계소계생산금액 (십억원)6138060058.5
2농림업농업농업총계소계소계소계소계소계생산지수101.5100.5
3농림업농업농업총계소계소계소계소계소계생산금액 (십억원)59203.757904.6
4농림업농업농업총계재배업소계소계소계소계생산지수101.599.3
5농림업농업농업총계재배업소계소계소계소계생산금액 (십억원)34606.132662.5
6농림업농업농업총계재배업식량작물소계소계소계생산지수103.8101.5
7농림업농업농업총계재배업식량작물소계소계소계생산금액 (십억원)11949.510219.1
8농림업농업농업총계재배업식량작물미곡소계소계생산지수104.6101.4
9농림업농업농업총계재배업식량작물미곡소계소계생산금액 (십억원)9526.37875.2
품목별(1)품목별(2)품목별(3)품목별(4)품목별(5)품목별(6)품목별(7)품목별(8)항목20212022
367농림업임업임업총계잔디소계소계소계소계생산지수133.393.8
368농림업임업임업총계잔디소계소계소계소계생산금액 (십억원)26.524.4
369농림업임업임업총계수액소계소계소계소계생산지수105.3105.5
370농림업임업임업총계수액소계소계소계소계생산금액 (십억원)18.912.7
371농림업임업임업총계톱밥소계소계소계소계생산지수115.272.7
372농림업임업임업총계톱밥소계소계소계소계생산금액 (십억원)32.118.6
373농림업임업임업총계목초액소계소계소계소계생산지수7650.5
374농림업임업임업총계목초액소계소계소계소계생산금액 (십억원)0.70.4
375농림업임업임업총계칡뿌리소계소계소계소계생산지수42.623.1
376농림업임업임업총계칡뿌리소계소계소계소계생산금액 (십억원)0.30.2