Overview

Dataset statistics

Number of variables10
Number of observations2030
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)0.2%
Total size in memory164.7 KiB
Average record size in memory83.1 B

Variable types

Categorical4
Text4
Numeric2

Dataset

Description경관직불 사업지구현황(마을별 경관작물 현황)
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220215000000001902

Alerts

사업년도 has constant value ""Constant
절기(동/하계) has constant value ""Constant
Dataset has 4 (0.2%) duplicate rowsDuplicates
참여자수(농가수) is highly overall correlated with 대상면적High correlation
대상면적 is highly overall correlated with 참여자수(농가수)High correlation
대상면적 has 104 (5.1%) zerosZeros

Reproduction

Analysis started2023-12-11 03:10:58.093718
Analysis finished2023-12-11 03:10:59.515078
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
2014
2030 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014
2nd row2014
3rd row2014
4th row2014
5th row2014

Common Values

ValueCountFrequency (%)
2014 2030
100.0%

Length

2023-12-11T12:10:59.584619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:10:59.703225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2014 2030
100.0%

시도
Categorical

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
전라남도
1002 
전라북도
541 
충청남도
300 
경상남도
102 
광주광역시
 
32
Other values (4)
 
53

Length

Max length7
Median length4
Mean length4.0413793
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 1002
49.4%
전라북도 541
26.7%
충청남도 300
 
14.8%
경상남도 102
 
5.0%
광주광역시 32
 
1.6%
울산광역시 27
 
1.3%
대전광역시 13
 
0.6%
경상북도 9
 
0.4%
제주특별자치도 4
 
0.2%

Length

2023-12-11T12:10:59.845613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:11:00.033271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 1002
49.4%
전라북도 541
26.7%
충청남도 300
 
14.8%
경상남도 102
 
5.0%
광주광역시 32
 
1.6%
울산광역시 27
 
1.3%
대전광역시 13
 
0.6%
경상북도 9
 
0.4%
제주특별자치도 4
 
0.2%

시군구
Text

Distinct53
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
2023-12-11T12:11:00.309790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9965517
Min length2

Characters and Unicode

Total characters6083
Distinct characters60
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

Unique3 ?
Unique (%)0.1%

Sample

1st row거제시
2nd row거제시
3rd row거제시
4th row거제시
5th row거제시
ValueCountFrequency (%)
서천군 283
13.9%
부안군 218
 
10.7%
영광군 199
 
9.8%
곡성군 184
 
9.1%
익산시 121
 
6.0%
영암군 118
 
5.8%
보성군 94
 
4.6%
고창군 82
 
4.0%
해남군 75
 
3.7%
화순군 66
 
3.3%
Other values (43) 590
29.1%
2023-12-11T12:11:00.727300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 1668
27.4%
천 372
 
6.1%
성 347
 
5.7%
시 343
 
5.6%
영 317
 
5.2%
서 283
 
4.7%
안 232
 
3.8%
광 224
 
3.7%
부 218
 
3.6%
곡 184
 
3.0%
Other values (50) 1895
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6083
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 1668
27.4%
천 372
 
6.1%
성 347
 
5.7%
시 343
 
5.6%
영 317
 
5.2%
서 283
 
4.7%
안 232
 
3.8%
광 224
 
3.7%
부 218
 
3.6%
곡 184
 
3.0%
Other values (50) 1895
31.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6083
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 1668
27.4%
천 372
 
6.1%
성 347
 
5.7%
시 343
 
5.6%
영 317
 
5.2%
서 283
 
4.7%
안 232
 
3.8%
광 224
 
3.7%
부 218
 
3.6%
곡 184
 
3.0%
Other values (50) 1895
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6083
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 1668
27.4%
천 372
 
6.1%
성 347
 
5.7%
시 343
 
5.6%
영 317
 
5.2%
서 283
 
4.7%
안 232
 
3.8%
광 224
 
3.7%
부 218
 
3.6%
곡 184
 
3.0%
Other values (50) 1895
31.2%

읍면동
Text

Distinct148
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
2023-12-11T12:11:01.122943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9985222
Min length2

Characters and Unicode

Total characters6087
Distinct characters131
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

Unique14 ?
Unique (%)0.7%

Sample

1st row둔덕면
2nd row둔덕면
3rd row둔덕면
4th row둔덕면
5th row둔덕면
ValueCountFrequency (%)
서천읍 123
 
6.1%
군서면 93
 
4.6%
백수읍 92
 
4.5%
계화면 87
 
4.3%
오산면 76
 
3.7%
마서면 61
 
3.0%
겸백면 56
 
2.8%
석곡면 54
 
2.7%
화양면 46
 
2.3%
목사동면 41
 
2.0%
Other values (138) 1301
64.1%
2023-12-11T12:11:01.638183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 1579
25.9%
읍 402
 
6.6%
서 359
 
5.9%
산 257
 
4.2%
백 169
 
2.8%
천 147
 
2.4%
화 144
 
2.4%
동 139
 
2.3%
군 133
 
2.2%
계 117
 
1.9%
Other values (121) 2641
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6087
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 1579
25.9%
읍 402
 
6.6%
서 359
 
5.9%
산 257
 
4.2%
백 169
 
2.8%
천 147
 
2.4%
화 144
 
2.4%
동 139
 
2.3%
군 133
 
2.2%
계 117
 
1.9%
Other values (121) 2641
43.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6087
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 1579
25.9%
읍 402
 
6.6%
서 359
 
5.9%
산 257
 
4.2%
백 169
 
2.8%
천 147
 
2.4%
화 144
 
2.4%
동 139
 
2.3%
군 133
 
2.2%
계 117
 
1.9%
Other values (121) 2641
43.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6087
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 1579
25.9%
읍 402
 
6.6%
서 359
 
5.9%
산 257
 
4.2%
백 169
 
2.8%
천 147
 
2.4%
화 144
 
2.4%
동 139
 
2.3%
군 133
 
2.2%
계 117
 
1.9%
Other values (121) 2641
43.4%

대상지구명
Text

Distinct727
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
2023-12-11T12:11:01.962462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length4.8817734
Min length1

Characters and Unicode

Total characters9910
Distinct characters211
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

Unique331 ?
Unique (%)16.3%

Sample

1st row방하마을
2nd row방하마을
3rd row방하마을
4th row방하마을
5th row방하마을
ValueCountFrequency (%)
봉계 27
 
1.3%
대안 26
 
1.3%
십자뜰 23
 
1.1%
신기 19
 
0.9%
규동 17
 
0.8%
우산 16
 
0.8%
퇴래마을 16
 
0.8%
장동 15
 
0.7%
신흥 15
 
0.7%
진목 15
 
0.7%
Other values (719) 1848
90.7%
2023-12-11T12:11:02.568840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 606
 
6.1%
지 525
 
5.3%
구 476
 
4.8%
산 360
 
3.6%
마 356
 
3.6%
을 306
 
3.1%
경 251
 
2.5%
친 249
 
2.5%
환 249
 
2.5%
동 189
 
1.9%
Other values (201) 6343
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8750
88.3%
Other Punctuation 631
 
6.4%
Decimal Number 434
 
4.4%
Open Punctuation 44
 
0.4%
Close Punctuation 44
 
0.4%
Space Separator 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 525
 
6.0%
구 476
 
5.4%
산 360
 
4.1%
마 356
 
4.1%
을 306
 
3.5%
경 251
 
2.9%
친 249
 
2.8%
환 249
 
2.8%
동 189
 
2.2%
리 185
 
2.1%
Other values (190) 5604
64.0%
Decimal Number
ValueCountFrequency (%)
1 142
32.7%
2 104
24.0%
3 72
16.6%
4 57
13.1%
0 33
 
7.6%
5 26
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 606
96.0%
. 25
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8750
88.3%
Common 1160
 
11.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 525
 
6.0%
구 476
 
5.4%
산 360
 
4.1%
마 356
 
4.1%
을 306
 
3.5%
경 251
 
2.9%
친 249
 
2.8%
환 249
 
2.8%
동 189
 
2.2%
리 185
 
2.1%
Other values (190) 5604
64.0%
Common
ValueCountFrequency (%)
, 606
52.2%
1 142
 
12.2%
2 104
 
9.0%
3 72
 
6.2%
4 57
 
4.9%
( 44
 
3.8%
) 44
 
3.8%
0 33
 
2.8%
5 26
 
2.2%
. 25
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8750
88.3%
ASCII 1160
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 606
52.2%
1 142
 
12.2%
2 104
 
9.0%
3 72
 
6.2%
4 57
 
4.9%
( 44
 
3.8%
) 44
 
3.8%
0 33
 
2.8%
5 26
 
2.2%
. 25
 
2.2%
Hangul
ValueCountFrequency (%)
지 525
 
6.0%
구 476
 
5.4%
산 360
 
4.1%
마 356
 
4.1%
을 306
 
3.5%
경 251
 
2.9%
친 249
 
2.8%
환 249
 
2.8%
동 189
 
2.2%
리 185
 
2.1%
Other values (190) 5604
64.0%

법정리명
Text

Distinct752
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
2023-12-11T12:11:02.952216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.0133005
Min length2

Characters and Unicode

Total characters6117
Distinct characters240
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

Unique396 ?
Unique (%)19.5%

Sample

1st row방하마을
2nd row서정리
3rd row시목리
4th row거림리
5th row산방리
ValueCountFrequency (%)
창북리 57
 
2.8%
하사리 21
 
1.0%
월곡리 20
 
1.0%
삼산리 20
 
1.0%
화금리 20
 
1.0%
장신리 19
 
0.9%
상사리 18
 
0.9%
봉계 18
 
0.9%
석곡리 16
 
0.8%
청호리 16
 
0.8%
Other values (744) 1809
88.9%
2023-12-11T12:11:03.481625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 1876
30.7%
산 228
 
3.7%
동 157
 
2.6%
신 112
 
1.8%
사 109
 
1.8%
창 95
 
1.6%
곡 86
 
1.4%
마 86
 
1.4%
월 80
 
1.3%
계 78
 
1.3%
Other values (230) 3210
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6096
99.7%
Decimal Number 9
 
0.1%
Space Separator 4
 
0.1%
Other Punctuation 4
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1876
30.8%
산 228
 
3.7%
동 157
 
2.6%
신 112
 
1.8%
사 109
 
1.8%
창 95
 
1.6%
곡 86
 
1.4%
마 86
 
1.4%
월 80
 
1.3%
계 78
 
1.3%
Other values (223) 3189
52.3%
Decimal Number
ValueCountFrequency (%)
1 6
66.7%
2 2
 
22.2%
3 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6096
99.7%
Common 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1876
30.8%
산 228
 
3.7%
동 157
 
2.6%
신 112
 
1.8%
사 109
 
1.8%
창 95
 
1.6%
곡 86
 
1.4%
마 86
 
1.4%
월 80
 
1.3%
계 78
 
1.3%
Other values (223) 3189
52.3%
Common
ValueCountFrequency (%)
1 6
28.6%
4
19.0%
, 4
19.0%
) 2
 
9.5%
( 2
 
9.5%
2 2
 
9.5%
3 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6096
99.7%
ASCII 21
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 1876
30.8%
산 228
 
3.7%
동 157
 
2.6%
신 112
 
1.8%
사 109
 
1.8%
창 95
 
1.6%
곡 86
 
1.4%
마 86
 
1.4%
월 80
 
1.3%
계 78
 
1.3%
Other values (223) 3189
52.3%
ASCII
ValueCountFrequency (%)
1 6
28.6%
4
19.0%
, 4
19.0%
) 2
 
9.5%
( 2
 
9.5%
2 2
 
9.5%
3 1
 
4.8%

절기(동/하계)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
동계
2030 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동계 2030
100.0%

Length

2023-12-11T12:11:03.640306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:11:03.741251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동계 2030
100.0%

경관작물명
Categorical

Distinct40
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size16.0 KiB
헤어리베치
692 
유채
373 
보리(겉보리,쌀보리,맥주보리,청보리 등)
289 
이탈리안라이그라스
188 
밀
90 
Other values (35)
398 

Length

Max length38
Median length37
Mean length8.646798
Min length1

Unique

Unique10 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
헤어리베치 692
34.1%
유채 373
18.4%
보리(겉보리,쌀보리,맥주보리,청보리 등) 289
14.2%
이탈리안라이그라스 188
 
9.3%
밀 90
 
4.4%
보리(겉보리,쌀보리,맥주보리,청보리 등),유채 87
 
4.3%
호밀 87
 
4.3%
자운영 64
 
3.2%
보리(겉보리,쌀보리,맥주보리,청보리 등),이탈리안라이그라스 20
 
1.0%
유채,자운영 18
 
0.9%
Other values (30) 122
 
6.0%

Length

2023-12-11T12:11:03.912927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
헤어리베치 692
28.1%
보리(겉보리,쌀보리,맥주보리,청보리 425
17.2%
유채 373
15.1%
등 291
11.8%
이탈리안라이그라스 188
 
7.6%
등),유채 92
 
3.7%
밀 90
 
3.6%
호밀 87
 
3.5%
자운영 64
 
2.6%
등),이탈리안라이그라스 21
 
0.9%
Other values (28) 144
 
5.8%

참여자수(농가수)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.064532
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 KiB
2023-12-11T12:11:04.072281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile17
Maximum85
Range84
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.5358151
Coefficient of variation (CV)1.6080117
Kurtosis27.198356
Mean4.064532
Median Absolute Deviation (MAD)0
Skewness4.1245631
Sum8251
Variance42.716878
MonotonicityNot monotonic
2023-12-11T12:11:04.238462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1116
55.0%
2 248
 
12.2%
3 123
 
6.1%
4 82
 
4.0%
6 55
 
2.7%
5 55
 
2.7%
7 47
 
2.3%
8 33
 
1.6%
9 26
 
1.3%
10 26
 
1.3%
Other values (34) 219
 
10.8%
ValueCountFrequency (%)
1 1116
55.0%
2 248
 
12.2%
3 123
 
6.1%
4 82
 
4.0%
5 55
 
2.7%
6 55
 
2.7%
7 47
 
2.3%
8 33
 
1.6%
9 26
 
1.3%
10 26
 
1.3%
ValueCountFrequency (%)
85 1
< 0.1%
67 1
< 0.1%
66 1
< 0.1%
56 1
< 0.1%
48 1
< 0.1%
41 1
< 0.1%
40 2
0.1%
39 1
< 0.1%
38 2
0.1%
36 2
0.1%

대상면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1886
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51517.925
Minimum0
Maximum1459616.5
Zeros104
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size18.0 KiB
2023-12-11T12:11:04.450320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15595.75
median18828.95
Q357122.5
95-th percentile201181.95
Maximum1459616.5
Range1459616.5
Interquartile range (IQR)51526.75

Descriptive statistics

Standard deviation93861.134
Coefficient of variation (CV)1.8219122
Kurtosis50.589915
Mean51517.925
Median Absolute Deviation (MAD)15654.1
Skewness5.4864607
Sum1.0458139 × 108
Variance8.8099125 × 109
MonotonicityNot monotonic
2023-12-11T12:11:04.644153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 104
 
5.1%
4000.0 15
 
0.7%
3967.0 4
 
0.2%
10000.0 3
 
0.1%
3000.0 3
 
0.1%
2985.0 2
 
0.1%
6615.0 2
 
0.1%
6004.0 2
 
0.1%
8000.0 2
 
0.1%
5052.0 2
 
0.1%
Other values (1876) 1891
93.2%
ValueCountFrequency (%)
0.0 104
5.1%
441.0 1
 
< 0.1%
734.0 1
 
< 0.1%
797.0 1
 
< 0.1%
823.0 1
 
< 0.1%
860.0 1
 
< 0.1%
872.0 1
 
< 0.1%
873.0 1
 
< 0.1%
977.0 1
 
< 0.1%
1000.9 1
 
< 0.1%
ValueCountFrequency (%)
1459616.5 1
< 0.1%
1167024.4 1
< 0.1%
1062946.1 1
< 0.1%
794733.3 1
< 0.1%
739842.0 1
< 0.1%
690338.9 1
< 0.1%
668764.0 1
< 0.1%
651669.1 1
< 0.1%
556054.0 1
< 0.1%
543208.0 1
< 0.1%

Interactions

2023-12-11T12:10:59.010274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:10:58.770136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:10:59.106637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:10:58.881251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:11:04.765572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도시군구경관작물명참여자수(농가수)대상면적
시도1.0001.0000.7710.2060.000
시군구1.0001.0000.9200.2910.000
경관작물명0.7710.9201.0000.0000.000
참여자수(농가수)0.2060.2910.0001.0000.840
대상면적0.0000.0000.0000.8401.000
2023-12-11T12:11:04.877616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도경관작물명
시도1.0000.407
경관작물명0.4071.000
2023-12-11T12:11:04.999737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참여자수(농가수)대상면적시도경관작물명
참여자수(농가수)1.0000.6110.0670.000
대상면적0.6111.0000.0000.000
시도0.0670.0001.0000.407
경관작물명0.0000.0000.4071.000

Missing values

2023-12-11T12:10:59.242865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:10:59.444388image/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

사업년도시도시군구읍면동대상지구명법정리명절기(동/하계)경관작물명참여자수(농가수)대상면적
02014경상남도거제시둔덕면방하마을방하마을동계코스모스36300.0
12014경상남도거제시둔덕면방하마을서정리동계코스모스12216.0
22014경상남도거제시둔덕면방하마을시목리동계코스모스11695.0
32014경상남도거제시둔덕면방하마을거림리동계코스모스831026.0
42014경상남도거제시둔덕면방하마을산방리동계코스모스23481.0
52014경상남도거제시둔덕면방하마을방하리동계코스모스847997.0
62014경상남도거창군가조면화곡,도산당도리동계호밀11172621.0
72014경상남도거창군마리면상율율리동계호밀9134359.0
82014경상남도거창군마리면상율월계리동계호밀12740.0
92014경상남도거창군위천면호밀꽃향기마을상림리동계호밀1152874.0
사업년도시도시군구읍면동대상지구명법정리명절기(동/하계)경관작물명참여자수(농가수)대상면적
20202014충청남도아산시송악면평촌리평촌리동계자운영24210856.0
20212014충청남도아산시송악면평촌리외암리동계자운영311850.0
20222014충청남도아산시송악면평촌리종곡리동계자운영15219.0
20232014충청남도아산시송악면평촌리수곡리동계자운영11313.0
20242014충청남도아산시송악면평촌리동화리동계자운영25250.0
20252014충청남도청양군화성면수정마을화암리동계보리(겉보리,쌀보리,맥주보리,청보리 등)116893.0
20262014충청남도청양군화성면수정마을기덕리동계보리(겉보리,쌀보리,맥주보리,청보리 등)317434.0
20272014충청남도청양군화성면수정마을수정리동계보리(겉보리,쌀보리,맥주보리,청보리 등)635508.2
20282014충청남도홍성군서부면하리광리동계유채121736.0
20292014충청남도홍성군서부면하리궁리동계유채66886.0

Duplicate rows

Most frequently occurring

사업년도시도시군구읍면동대상지구명법정리명절기(동/하계)경관작물명참여자수(농가수)대상면적# duplicates
02014경상남도김해시한림면장방마을장방마을동계호밀10.03
22014대전광역시유성구진잠동대정마을대정마을동계유채10.03
12014광주광역시광산구삼도동도림마을도림마을동계유채10.02
32014전라북도군산시나포면십자뜰십자뜰동계헤어리베치14000.02