Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory84.3 B

Variable types

Categorical7
Text1
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
시군구 is highly overall correlated with 시도 and 3 other fieldsHigh correlation
읍면동 is highly overall correlated with 시도 and 3 other fieldsHigh correlation
대상지구명 is highly overall correlated with 시도 and 3 other fieldsHigh correlation
시도 is highly overall correlated with 시군구 and 2 other fieldsHigh correlation
참여자수(농가수) is highly overall correlated with 대상면적(㎡)High correlation
대상면적(㎡) is highly overall correlated with 참여자수(농가수)High correlation
경관작물명 is highly overall correlated with 시군구 and 2 other fieldsHigh correlation
대상면적(㎡) has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:11:21.125403
Analysis finished2023-12-11 03:11:22.683044
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2015
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2015
5th row2015

Common Values

ValueCountFrequency (%)
2015 100
100.0%

Length

2023-12-11T12:11:22.776955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:11:22.918477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015 100
100.0%

시도
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
울산광역시
28 
전라남도
18 
경상북도
14 
전라북도
10 
경상남도
10 
Other values (6)
20 

Length

Max length5
Median length4
Mean length4.29
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row인천광역시
2nd row광주광역시
3rd row광주광역시
4th row대전광역시
5th row대전광역시

Common Values

ValueCountFrequency (%)
울산광역시 28
28.0%
전라남도 18
18.0%
경상북도 14
14.0%
전라북도 10
 
10.0%
경상남도 10
 
10.0%
강원도 8
 
8.0%
대전광역시 6
 
6.0%
광주광역시 2
 
2.0%
충청남도 2
 
2.0%
인천광역시 1
 
1.0%

Length

2023-12-11T12:11:23.079803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울산광역시 28
28.0%
전라남도 18
18.0%
경상북도 14
14.0%
전라북도 10
 
10.0%
경상남도 10
 
10.0%
강원도 8
 
8.0%
대전광역시 6
 
6.0%
광주광역시 2
 
2.0%
충청남도 2
 
2.0%
인천광역시 1
 
1.0%

시군구
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
울주군
28 
진도군
9 
거제시
8 
봉화군
7 
대덕구
6 
Other values (18)
42 

Length

Max length3
Median length3
Mean length2.98
Min length2

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row옹진군
2nd row서구
3rd row서구
4th row대덕구
5th row대덕구

Common Values

ValueCountFrequency (%)
울주군 28
28.0%
진도군 9
 
9.0%
거제시 8
 
8.0%
봉화군 7
 
7.0%
대덕구 6
 
6.0%
태백시 6
 
6.0%
고창군 4
 
4.0%
영양군 4
 
4.0%
예천군 3
 
3.0%
부안군 3
 
3.0%
Other values (13) 22
22.0%

Length

2023-12-11T12:11:23.256952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울주군 28
28.0%
진도군 9
 
9.0%
거제시 8
 
8.0%
봉화군 7
 
7.0%
대덕구 6
 
6.0%
태백시 6
 
6.0%
고창군 4
 
4.0%
영양군 4
 
4.0%
예천군 3
 
3.0%
부안군 3
 
3.0%
Other values (13) 22
22.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
두동면
28 
둔덕면
8 
회덕동
6 
의신면
6 
삼수동
5 
Other values (24)
47 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row백령면
2nd row유덕동
3rd row유덕동
4th row회덕동
5th row회덕동

Common Values

ValueCountFrequency (%)
두동면 28
28.0%
둔덕면 8
 
8.0%
회덕동 6
 
6.0%
의신면 6
 
6.0%
삼수동 5
 
5.0%
재산면 5
 
5.0%
수비면 4
 
4.0%
효자면 3
 
3.0%
상서면 3
 
3.0%
고부면 3
 
3.0%
Other values (19) 29
29.0%

Length

2023-12-11T12:11:23.392555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
두동면 28
28.0%
둔덕면 8
 
8.0%
회덕동 6
 
6.0%
의신면 6
 
6.0%
삼수동 5
 
5.0%
재산면 5
 
5.0%
수비면 4
 
4.0%
효자면 3
 
3.0%
상서면 3
 
3.0%
고부면 3
 
3.0%
Other values (19) 29
29.0%

대상지구명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
봉계(하계)
28 
방하마을
8 
장동
6 
수하2리
 
4
고부리
 
3
Other values (29)
51 

Length

Max length6
Median length5
Mean length4.04
Min length2

Unique

Unique12 ?
Unique (%)12.0%

Sample

1st row진촌1리
2nd row덕흥
3rd row덕흥
4th row장동
5th row장동

Common Values

ValueCountFrequency (%)
봉계(하계) 28
28.0%
방하마을 8
 
8.0%
장동 6
 
6.0%
수하2리 4
 
4.0%
고부리 3
 
3.0%
도명 3
 
3.0%
영산 3
 
3.0%
청림 3
 
3.0%
명봉리 3
 
3.0%
현동남면마을 3
 
3.0%
Other values (24) 36
36.0%

Length

2023-12-11T12:11:23.550118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
봉계(하계 28
28.0%
방하마을 8
 
8.0%
장동 6
 
6.0%
수하2리 4
 
4.0%
고부리 3
 
3.0%
도명 3
 
3.0%
영산 3
 
3.0%
청림 3
 
3.0%
명봉리 3
 
3.0%
현동남면마을 3
 
3.0%
Other values (24) 36
36.0%

법정리명
Text

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-11T12:11:23.854427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.44
Min length2

Characters and Unicode

Total characters344
Distinct characters93
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

Unique54 ?
Unique (%)54.0%

Sample

1st row진촌리
2nd row덕흥
3rd row덕흥
4th row장동
5th row장동
ValueCountFrequency (%)
봉계(하계 15
 
14.9%
장동 6
 
5.9%
노하리 3
 
3.0%
봉계리 2
 
2.0%
명봉리 2
 
2.0%
동면리 2
 
2.0%
현동리 2
 
2.0%
침계리 2
 
2.0%
구미리 2
 
2.0%
덕흥 2
 
2.0%
Other values (59) 63
62.4%
2023-12-11T12:11:24.404026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 67
19.5%
계 35
 
10.2%
하 24
 
7.0%
봉 19
 
5.5%
( 15
 
4.4%
) 15
 
4.4%
동 15
 
4.4%
마 6
 
1.7%
산 6
 
1.7%
장 6
 
1.7%
Other values (83) 136
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
91.0%
Open Punctuation 15
 
4.4%
Close Punctuation 15
 
4.4%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 67
21.4%
계 35
 
11.2%
하 24
 
7.7%
봉 19
 
6.1%
동 15
 
4.8%
마 6
 
1.9%
산 6
 
1.9%
장 6
 
1.9%
을 5
 
1.6%
진 5
 
1.6%
Other values (80) 125
39.9%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
91.0%
Common 31
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 67
21.4%
계 35
 
11.2%
하 24
 
7.7%
봉 19
 
6.1%
동 15
 
4.8%
마 6
 
1.9%
산 6
 
1.9%
장 6
 
1.9%
을 5
 
1.6%
진 5
 
1.6%
Other values (80) 125
39.9%
Common
ValueCountFrequency (%)
( 15
48.4%
) 15
48.4%
1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
91.0%
ASCII 31
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 67
21.4%
계 35
 
11.2%
하 24
 
7.7%
봉 19
 
6.1%
동 15
 
4.8%
마 6
 
1.9%
산 6
 
1.9%
장 6
 
1.9%
을 5
 
1.6%
진 5
 
1.6%
Other values (80) 125
39.9%
ASCII
ValueCountFrequency (%)
( 15
48.4%
) 15
48.4%
1
 
3.2%

절기(동/하계)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
하계
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하계 100
100.0%

Length

2023-12-11T12:11:24.580670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:11:24.700232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하계 100
100.0%

경관작물명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
메밀
43 
코스모스
42 
해바라기
5 
국화류
5 
기타(준경관작물)(수단그라스)
 
3

Length

Max length16
Median length4
Mean length3.41
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
메밀 43
43.0%
코스모스 42
42.0%
해바라기 5
 
5.0%
국화류 5
 
5.0%
기타(준경관작물)(수단그라스) 3
 
3.0%
연꽃 2
 
2.0%

Length

2023-12-11T12:11:24.846255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:11:25.007143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
메밀 43
43.0%
코스모스 42
42.0%
해바라기 5
 
5.0%
국화류 5
 
5.0%
기타(준경관작물)(수단그라스 3
 
3.0%
연꽃 2
 
2.0%

참여자수(농가수)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.66
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T12:11:25.158449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile12.5
Maximum42
Range41
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.3424496
Coefficient of variation (CV)1.7329097
Kurtosis17.191133
Mean3.66
Median Absolute Deviation (MAD)0
Skewness3.8930643
Sum366
Variance40.226667
MonotonicityNot monotonic
2023-12-11T12:11:25.298891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 56
56.0%
2 13
 
13.0%
3 7
 
7.0%
4 5
 
5.0%
5 5
 
5.0%
6 4
 
4.0%
12 2
 
2.0%
11 2
 
2.0%
22 2
 
2.0%
30 1
 
1.0%
Other values (3) 3
 
3.0%
ValueCountFrequency (%)
1 56
56.0%
2 13
 
13.0%
3 7
 
7.0%
4 5
 
5.0%
5 5
 
5.0%
6 4
 
4.0%
8 1
 
1.0%
11 2
 
2.0%
12 2
 
2.0%
22 2
 
2.0%
ValueCountFrequency (%)
42 1
 
1.0%
30 1
 
1.0%
24 1
 
1.0%
22 2
 
2.0%
12 2
 
2.0%
11 2
 
2.0%
8 1
 
1.0%
6 4
4.0%
5 5
5.0%
4 5
5.0%

대상면적(㎡)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42742.77
Minimum170
Maximum528952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T12:11:25.466437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170
5-th percentile1129.15
Q12387.25
median8841
Q339480.5
95-th percentile204175.65
Maximum528952
Range528782
Interquartile range (IQR)37093.25

Descriptive statistics

Standard deviation78346.98
Coefficient of variation (CV)1.8329879
Kurtosis15.275591
Mean42742.77
Median Absolute Deviation (MAD)7539
Skewness3.4142137
Sum4274277
Variance6.1382492 × 109
MonotonicityNot monotonic
2023-12-11T12:11:25.625154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21025 1
 
1.0%
200888 1
 
1.0%
203900 1
 
1.0%
193821 1
 
1.0%
32419 1
 
1.0%
20507 1
 
1.0%
100887 1
 
1.0%
188570 1
 
1.0%
50034 1
 
1.0%
209413 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
170 1
1.0%
568 1
1.0%
638 1
1.0%
977 1
1.0%
1018 1
1.0%
1135 1
1.0%
1286 1
1.0%
1318 1
1.0%
1604 1
1.0%
1636 1
1.0%
ValueCountFrequency (%)
528952 1
1.0%
267625 1
1.0%
235781 1
1.0%
210382 1
1.0%
209413 1
1.0%
203900 1
1.0%
200888 1
1.0%
200036 1
1.0%
193821 1
1.0%
188570 1
1.0%

Interactions

2023-12-11T12:11:22.107080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:11:21.864890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:11:22.214658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:11:21.987579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:11:25.724752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도시군구읍면동대상지구명법정리명경관작물명참여자수(농가수)대상면적(㎡)
시도1.0001.0001.0001.0001.0000.6760.0000.578
시군구1.0001.0001.0001.0000.9970.9180.4560.789
읍면동1.0001.0001.0001.0000.9970.9500.4620.835
대상지구명1.0001.0001.0001.0000.9970.9530.4230.872
법정리명1.0000.9970.9970.9971.0000.8810.7330.872
경관작물명0.6760.9180.9500.9530.8811.0000.1380.000
참여자수(농가수)0.0000.4560.4620.4230.7330.1381.0000.578
대상면적(㎡)0.5780.7890.8350.8720.8720.0000.5781.000
2023-12-11T12:11:25.859521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구읍면동대상지구명경관작물명시도
시군구1.0000.9600.9260.6540.930
읍면동0.9601.0000.9640.6890.893
대상지구명0.9260.9641.0000.6670.861
경관작물명0.6540.6890.6671.0000.417
시도0.9300.8930.8610.4171.000
2023-12-11T12:11:25.970004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참여자수(농가수)대상면적(㎡)시도시군구읍면동대상지구명경관작물명
참여자수(농가수)1.0000.5650.0000.1990.1870.1570.045
대상면적(㎡)0.5651.0000.3250.4480.4700.4990.000
시도0.0000.3251.0000.9300.8930.8610.417
시군구0.1990.4480.9301.0000.9600.9260.654
읍면동0.1870.4700.8930.9601.0000.9640.689
대상지구명0.1570.4990.8610.9260.9641.0000.667
경관작물명0.0450.0000.4170.6540.6890.6671.000

Missing values

2023-12-11T12:11:22.388897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:11:22.608717image/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(㎡)
02015인천광역시옹진군백령면진촌1리진촌리하계메밀421025
12015광주광역시서구유덕동덕흥덕흥하계메밀318273
22015광주광역시서구유덕동덕흥덕흥하계메밀122999
32015대전광역시대덕구회덕동장동장동하계코스모스15422
42015대전광역시대덕구회덕동장동장동하계코스모스12319
52015대전광역시대덕구회덕동장동장동하계코스모스25990
62015대전광역시대덕구회덕동장동장동하계코스모스11318
72015대전광역시대덕구회덕동장동장동하계코스모스1239773
82015대전광역시대덕구회덕동장동장동하계코스모스11018
92015울산광역시울주군두동면봉계(하계)봉계(하계)하계코스모스21135
사업년도시도시군구읍면동대상지구명법정리명절기(동/하계)경관작물명참여자수(농가수)대상면적(㎡)
902015경상남도진주시명석면조비조비하계연꽃14594
912015경상남도진주시명석면조비용산리하계연꽃22105645
922015경상남도거제시둔덕면방하마을하둔리하계코스모스12958
932015경상남도거제시둔덕면방하마을방하리하계코스모스537500
942015경상남도거제시둔덕면방하마을산방리하계코스모스24962
952015경상남도거제시둔덕면방하마을거림리하계코스모스526880
962015경상남도거제시둔덕면방하마을상둔리하계코스모스27197
972015경상남도거제시둔덕면방하마을망치리하계코스모스12216
982015경상남도거제시둔덕면방하마을방하마을하계코스모스12260
992015경상남도거제시둔덕면방하마을방하마을하계코스모스11286