Overview

Dataset statistics

Number of variables17
Number of observations106
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory140.2 B

Variable types

Numeric3
Text10
Categorical4

Dataset

Description유해야생동물로 부터 농작물의 피해방지를 위하여 피해예방시설(울타리 설치 등)사업 세부 사항을 알리는 사항입니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15081892/fileData.do

Alerts

설치대상 농경지 민통선 내외표시 is highly overall correlated with 설치대상 농경지 읍면 and 1 other fieldsHigh correlation
설치대상 농경지 읍면 is highly overall correlated with 설치대상 농경지 민통선 내외표시 and 1 other fieldsHigh correlation
지원 시설 규모(m) 신청 is highly overall correlated with 지원 시설 규모(m) 최종 High correlation
지원 시설 규모(m) 최종 is highly overall correlated with 지원 시설 규모(m) 신청 High correlation
지원 시설 시설명 is highly overall correlated with 설치대상 농경지 읍면 and 1 other fieldsHigh correlation
설치대상 농경지 소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:24:05.007602
Analysis finished2023-12-12 05:24:07.740817
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct31
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.018868
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:24:07.813665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q317
95-th percentile25.75
Maximum31
Range30
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.5554851
Coefficient of variation (CV)0.62863534
Kurtosis-0.50378077
Mean12.018868
Median Absolute Deviation (MAD)6
Skewness0.49838657
Sum1274
Variance57.085355
MonotonicityNot monotonic
2023-12-12T14:24:07.966205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 5
 
4.7%
3 5
 
4.7%
4 5
 
4.7%
5 5
 
4.7%
6 5
 
4.7%
7 5
 
4.7%
8 5
 
4.7%
9 5
 
4.7%
10 5
 
4.7%
11 5
 
4.7%
Other values (21) 56
52.8%
ValueCountFrequency (%)
1 5
4.7%
2 5
4.7%
3 5
4.7%
4 5
4.7%
5 5
4.7%
6 5
4.7%
7 5
4.7%
8 5
4.7%
9 5
4.7%
10 5
4.7%
ValueCountFrequency (%)
31 1
0.9%
30 1
0.9%
29 1
0.9%
28 1
0.9%
27 1
0.9%
26 1
0.9%
25 1
0.9%
24 2
1.9%
23 2
1.9%
22 2
1.9%

신청인 주소
Text

Distinct104
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:08.316950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length39
Mean length26.54717
Min length7

Characters and Unicode

Total characters2814
Distinct characters192
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)96.2%

Sample

1st row대전광역시 서구 계백로776번길 154(관저동)
2nd row대전광역시 중구 돌다리로8번길 76(석교동)
3rd row대전광역시 동구 비룡로14번길 25(비룡동)
4th row대전광역시 동구 비룡로14번길 25(비룡동)
5th row세종특별자치시 달빛로 211, 1022-2201(아름동, 범지기마을10단지)
ValueCountFrequency (%)
대전광역시 43
 
8.7%
서구 26
 
5.2%
대덕구 22
 
4.4%
유성구 17
 
3.4%
중구 14
 
2.8%
동구 14
 
2.8%
장동 7
 
1.4%
111동 4
 
0.8%
산디로15번길 4
 
0.8%
55 4
 
0.8%
Other values (297) 341
68.8%
2023-12-12T14:24:08.847527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
408
 
14.5%
1 167
 
5.9%
동 139
 
4.9%
0 118
 
4.2%
2 101
 
3.6%
구 97
 
3.4%
대 88
 
3.1%
로 87
 
3.1%
, 83
 
2.9%
( 74
 
2.6%
Other values (182) 1452
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1401
49.8%
Decimal Number 717
25.5%
Space Separator 408
 
14.5%
Other Punctuation 95
 
3.4%
Open Punctuation 74
 
2.6%
Close Punctuation 73
 
2.6%
Dash Punctuation 44
 
1.6%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 139
 
9.9%
구 97
 
6.9%
대 88
 
6.3%
로 87
 
6.2%
시 50
 
3.6%
길 49
 
3.5%
전 47
 
3.4%
역 43
 
3.1%
광 43
 
3.1%
호 39
 
2.8%
Other values (165) 719
51.3%
Decimal Number
ValueCountFrequency (%)
1 167
23.3%
0 118
16.5%
2 101
14.1%
5 67
9.3%
3 66
 
9.2%
4 54
 
7.5%
6 50
 
7.0%
7 34
 
4.7%
9 32
 
4.5%
8 28
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 83
87.4%
@ 12
 
12.6%
Space Separator
ValueCountFrequency (%)
408
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1411
50.1%
Hangul 1401
49.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 139
 
9.9%
구 97
 
6.9%
대 88
 
6.3%
로 87
 
6.2%
시 50
 
3.6%
길 49
 
3.5%
전 47
 
3.4%
역 43
 
3.1%
광 43
 
3.1%
호 39
 
2.8%
Other values (165) 719
51.3%
Common
ValueCountFrequency (%)
408
28.9%
1 167
11.8%
0 118
 
8.4%
2 101
 
7.2%
, 83
 
5.9%
( 74
 
5.2%
) 73
 
5.2%
5 67
 
4.7%
3 66
 
4.7%
4 54
 
3.8%
Other values (6) 200
14.2%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1413
50.2%
Hangul 1401
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
408
28.9%
1 167
11.8%
0 118
 
8.4%
2 101
 
7.1%
, 83
 
5.9%
( 74
 
5.2%
) 73
 
5.2%
5 67
 
4.7%
3 66
 
4.7%
4 54
 
3.8%
Other values (7) 202
14.3%
Hangul
ValueCountFrequency (%)
동 139
 
9.9%
구 97
 
6.9%
대 88
 
6.3%
로 87
 
6.2%
시 50
 
3.6%
길 49
 
3.5%
전 47
 
3.4%
역 43
 
3.1%
광 43
 
3.1%
호 39
 
2.8%
Other values (165) 719
51.3%

신청인 성명
Text

Distinct103
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:09.214073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0377358
Min length3

Characters and Unicode

Total characters322
Distinct characters105
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

Unique100 ?
Unique (%)94.3%

Sample

1st row박미숙
2nd row박정규
3rd row권선창
4th row민선희
5th row유지훈
ValueCountFrequency (%)
박미숙 2
 
1.9%
마재만 2
 
1.9%
박정규 2
 
1.9%
이시구 1
 
0.9%
유영란외1 1
 
0.9%
박춘서 1
 
0.9%
강영호 1
 
0.9%
유재경 1
 
0.9%
이이준 1
 
0.9%
고인성 1
 
0.9%
Other values (93) 93
87.7%
2023-12-12T14:24:09.805832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 18
 
5.6%
박 16
 
5.0%
김 15
 
4.7%
영 11
 
3.4%
송 10
 
3.1%
순 9
 
2.8%
규 8
 
2.5%
희 7
 
2.2%
용 7
 
2.2%
성 7
 
2.2%
Other values (95) 214
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
99.4%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
5.6%
박 16
 
5.0%
김 15
 
4.7%
영 11
 
3.4%
송 10
 
3.1%
순 9
 
2.8%
규 8
 
2.5%
희 7
 
2.2%
용 7
 
2.2%
성 7
 
2.2%
Other values (93) 212
66.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
99.4%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
5.6%
박 16
 
5.0%
김 15
 
4.7%
영 11
 
3.4%
송 10
 
3.1%
순 9
 
2.8%
규 8
 
2.5%
희 7
 
2.2%
용 7
 
2.2%
성 7
 
2.2%
Other values (93) 212
66.2%
Common
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
99.4%
ASCII 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 18
 
5.6%
박 16
 
5.0%
김 15
 
4.7%
영 11
 
3.4%
송 10
 
3.1%
순 9
 
2.8%
규 8
 
2.5%
희 7
 
2.2%
용 7
 
2.2%
성 7
 
2.2%
Other values (93) 212
66.2%
ASCII
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

설치대상 농경지 읍면
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
대덕구
31 
서구
20 
유성구
19 
대청동
16 
<NA>
12 

Length

Max length4
Median length3
Mean length2.9245283
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산내동
2nd row대청동
3rd row대청동
4th row대청동
5th row대청동

Common Values

ValueCountFrequency (%)
대덕구 31
29.2%
서구 20
18.9%
유성구 19
17.9%
대청동 16
15.1%
<NA> 12
 
11.3%
산내동 8
 
7.5%

Length

2023-12-12T14:24:09.997415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:10.188785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대덕구 31
29.2%
서구 20
18.9%
유성구 19
17.9%
대청동 16
15.1%
na 12
 
11.3%
산내동 8
 
7.5%

설치대상 농경지 소재지
Text

UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:10.588533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length9.754717
Min length5

Characters and Unicode

Total characters1034
Distinct characters77
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

Unique106 ?
Unique (%)100.0%

Sample

1st row구도동 283-1
2nd row주산동 270, 270-2
3rd row비룡동 326
4th row비룡동 327-1,2
5th row효평동 373-1,2
ValueCountFrequency (%)
장동 17
 
6.9%
목달동 7
 
2.8%
흑석동 6
 
2.4%
소호동 4
 
1.6%
2 4
 
1.6%
봉곡동 4
 
1.6%
송정동 4
 
1.6%
연축동 4
 
1.6%
효평동 3
 
1.2%
세동 3
 
1.2%
Other values (165) 190
77.2%
2023-12-12T14:24:11.175864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
13.5%
동 106
 
10.3%
1 102
 
9.9%
- 77
 
7.4%
2 75
 
7.3%
4 48
 
4.6%
3 47
 
4.5%
, 41
 
4.0%
9 41
 
4.0%
7 35
 
3.4%
Other values (67) 322
31.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 466
45.1%
Other Letter 308
29.8%
Space Separator 140
 
13.5%
Dash Punctuation 77
 
7.4%
Other Punctuation 41
 
4.0%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 106
34.4%
산 22
 
7.1%
장 21
 
6.8%
달 7
 
2.3%
목 7
 
2.3%
곡 6
 
1.9%
석 6
 
1.9%
송 6
 
1.9%
정 6
 
1.9%
흑 6
 
1.9%
Other values (53) 115
37.3%
Decimal Number
ValueCountFrequency (%)
1 102
21.9%
2 75
16.1%
4 48
10.3%
3 47
10.1%
9 41
8.8%
7 35
 
7.5%
6 32
 
6.9%
5 30
 
6.4%
8 29
 
6.2%
0 27
 
5.8%
Space Separator
ValueCountFrequency (%)
140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 726
70.2%
Hangul 308
29.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 106
34.4%
산 22
 
7.1%
장 21
 
6.8%
달 7
 
2.3%
목 7
 
2.3%
곡 6
 
1.9%
석 6
 
1.9%
송 6
 
1.9%
정 6
 
1.9%
흑 6
 
1.9%
Other values (53) 115
37.3%
Common
ValueCountFrequency (%)
140
19.3%
1 102
14.0%
- 77
10.6%
2 75
10.3%
4 48
 
6.6%
3 47
 
6.5%
, 41
 
5.6%
9 41
 
5.6%
7 35
 
4.8%
6 32
 
4.4%
Other values (4) 88
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 726
70.2%
Hangul 308
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
19.3%
1 102
14.0%
- 77
10.6%
2 75
10.3%
4 48
 
6.6%
3 47
 
6.5%
, 41
 
5.6%
9 41
 
5.6%
7 35
 
4.8%
6 32
 
4.4%
Other values (4) 88
12.1%
Hangul
ValueCountFrequency (%)
동 106
34.4%
산 22
 
7.1%
장 21
 
6.8%
달 7
 
2.3%
목 7
 
2.3%
곡 6
 
1.9%
석 6
 
1.9%
송 6
 
1.9%
정 6
 
1.9%
흑 6
 
1.9%
Other values (53) 115
37.3%

설치대상 농경지 지목
Categorical

Distinct18
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
전
46 
답
18 
전
12 
임야
8 
답
6 
Other values (13)
16 

Length

Max length18
Median length1
Mean length2.2169811
Min length1

Unique

Unique11 ?
Unique (%)10.4%

Sample

1st row전
2nd row답
3rd row답
4th row답(327-1), 전(327-2)
5th row답(373-1), 전(373-2)

Common Values

ValueCountFrequency (%)
전 46
43.4%
답 18
 
17.0%
전 12
 
11.3%
임야 8
 
7.5%
답 6
 
5.7%
임야 3
 
2.8%
과 2
 
1.9%
과수 1
 
0.9%
답(327-1), 전(327-2) 1
 
0.9%
답(373-1), 전(373-2) 1
 
0.9%
Other values (8) 8
 
7.5%

Length

2023-12-12T14:24:11.643202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전 59
52.7%
답 27
24.1%
임야 11
 
9.8%
과 2
 
1.8%
과수원 2
 
1.8%
임 2
 
1.8%
과수 1
 
0.9%
답(327-1 1
 
0.9%
전(327-2 1
 
0.9%
답(373-1 1
 
0.9%
Other values (5) 5
 
4.5%

설치대상 농경지 민통선 내외표시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size980.0 B
외
67 
내
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외 67
63.2%
내 39
36.8%

Length

2023-12-12T14:24:11.836548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:11.981986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외 67
63.2%
내 39
36.8%

설치대상 농경지 면적(㎡)
Text

Distinct105
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:12.352448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.5471698
Min length2

Characters and Unicode

Total characters588
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

Unique104 ?
Unique (%)98.1%

Sample

1st row3,683
2nd row1,456
3rd row4,026
4th row2,142
5th row1,018
ValueCountFrequency (%)
130 2
 
1.9%
160 2
 
1.9%
200 1
 
0.9%
175 1
 
0.9%
2,889 1
 
0.9%
1,071 1
 
0.9%
1,588 1
 
0.9%
1,225 1
 
0.9%
120 1
 
0.9%
145 1
 
0.9%
Other values (94) 94
88.7%
2023-12-12T14:24:12.923157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
20.4%
, 73
12.4%
1 71
12.1%
0 62
10.5%
2 58
9.9%
5 40
 
6.8%
3 37
 
6.3%
4 28
 
4.8%
6 28
 
4.8%
9 27
 
4.6%
Other values (2) 44
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 395
67.2%
Space Separator 120
 
20.4%
Other Punctuation 73
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 71
18.0%
0 62
15.7%
2 58
14.7%
5 40
10.1%
3 37
9.4%
4 28
 
7.1%
6 28
 
7.1%
9 27
 
6.8%
8 23
 
5.8%
7 21
 
5.3%
Space Separator
ValueCountFrequency (%)
120
100.0%
Other Punctuation
ValueCountFrequency (%)
, 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
120
20.4%
, 73
12.4%
1 71
12.1%
0 62
10.5%
2 58
9.9%
5 40
 
6.8%
3 37
 
6.3%
4 28
 
4.8%
6 28
 
4.8%
9 27
 
4.6%
Other values (2) 44
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
20.4%
, 73
12.4%
1 71
12.1%
0 62
10.5%
2 58
9.9%
5 40
 
6.8%
3 37
 
6.3%
4 28
 
4.8%
6 28
 
4.8%
9 27
 
4.6%
Other values (2) 44
 
7.5%

설치대상 농경지 작물명
Text

Distinct76
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:13.179873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length6.2924528
Min length1

Characters and Unicode

Total characters667
Distinct characters62
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

Unique56 ?
Unique (%)52.8%

Sample

1st row특용작물
2nd row고구마, 고추
3rd row벼
4th row포도, 콩
5th row고구마, 콩, 고추 등 밭작물
ValueCountFrequency (%)
고구마 23
 
10.7%
밭작물 20
 
9.3%
등 19
 
8.8%
콩 18
 
8.4%
배추 15
 
7.0%
고추 15
 
7.0%
채소류 14
 
6.5%
과수 12
 
5.6%
감자 6
 
2.8%
들깨 6
 
2.8%
Other values (43) 67
31.2%
2023-12-12T14:24:13.637305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
16.5%
, 81
 
12.1%
고 44
 
6.6%
추 40
 
6.0%
마 29
 
4.3%
수 27
 
4.0%
구 26
 
3.9%
작 21
 
3.1%
콩 21
 
3.1%
배 21
 
3.1%
Other values (52) 247
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 474
71.1%
Space Separator 110
 
16.5%
Other Punctuation 83
 
12.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 44
 
9.3%
추 40
 
8.4%
마 29
 
6.1%
수 27
 
5.7%
구 26
 
5.5%
작 21
 
4.4%
콩 21
 
4.4%
배 21
 
4.4%
물 21
 
4.4%
채 20
 
4.2%
Other values (49) 204
43.0%
Other Punctuation
ValueCountFrequency (%)
, 81
97.6%
. 2
 
2.4%
Space Separator
ValueCountFrequency (%)
110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 474
71.1%
Common 193
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 44
 
9.3%
추 40
 
8.4%
마 29
 
6.1%
수 27
 
5.7%
구 26
 
5.5%
작 21
 
4.4%
콩 21
 
4.4%
배 21
 
4.4%
물 21
 
4.4%
채 20
 
4.2%
Other values (49) 204
43.0%
Common
ValueCountFrequency (%)
110
57.0%
, 81
42.0%
. 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 474
71.1%
ASCII 193
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
57.0%
, 81
42.0%
. 2
 
1.0%
Hangul
ValueCountFrequency (%)
고 44
 
9.3%
추 40
 
8.4%
마 29
 
6.1%
수 27
 
5.7%
구 26
 
5.5%
작 21
 
4.4%
콩 21
 
4.4%
배 21
 
4.4%
물 21
 
4.4%
채 20
 
4.2%
Other values (49) 204
43.0%

지원 시설 시설명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
철선울타리
72 
철선울타리(능형철망)
19 
철선울타리
9 
전기목책기
 
3
전기목책
 
2

Length

Max length11
Median length5
Mean length6.2735849
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
철선울타리 72
67.9%
철선울타리(능형철망) 19
 
17.9%
철선울타리 9
 
8.5%
전기목책기 3
 
2.8%
전기목책 2
 
1.9%
메쉬휀스 1
 
0.9%

Length

2023-12-12T14:24:13.776161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:13.892655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철선울타리 81
76.4%
철선울타리(능형철망 19
 
17.9%
전기목책기 3
 
2.8%
전기목책 2
 
1.9%
메쉬휀스 1
 
0.9%

지원 시설 규모(m) 신청
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)62.9%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean161.12381
Minimum18
Maximum530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:24:14.031297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile65.2
Q1105
median150
Q3200
95-th percentile308
Maximum530
Range512
Interquartile range (IQR)95

Descriptive statistics

Standard deviation82.758766
Coefficient of variation (CV)0.51363462
Kurtosis3.7002335
Mean161.12381
Median Absolute Deviation (MAD)50
Skewness1.4884411
Sum16918
Variance6849.0134
MonotonicityNot monotonic
2023-12-12T14:24:14.162981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200 6
 
5.7%
130 4
 
3.8%
150 4
 
3.8%
120 4
 
3.8%
135 3
 
2.8%
160 3
 
2.8%
145 3
 
2.8%
75 3
 
2.8%
175 3
 
2.8%
110 2
 
1.9%
Other values (56) 70
66.0%
ValueCountFrequency (%)
18 1
 
0.9%
33 1
 
0.9%
41 1
 
0.9%
56 1
 
0.9%
62 1
 
0.9%
64 1
 
0.9%
70 2
1.9%
75 3
2.8%
80 2
1.9%
81 1
 
0.9%
ValueCountFrequency (%)
530 1
0.9%
400 2
1.9%
347 1
0.9%
340 1
0.9%
310 1
0.9%
300 1
0.9%
295 1
0.9%
275 2
1.9%
270 1
0.9%
260 1
0.9%

지원 시설 규모(m) 최종
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.5
Minimum18
Maximum530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:24:14.329236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile65.5
Q1101.25
median148
Q3198.75
95-th percentile298.75
Maximum530
Range512
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation81.728966
Coefficient of variation (CV)0.51240731
Kurtosis4.0014855
Mean159.5
Median Absolute Deviation (MAD)50
Skewness1.522548
Sum16907
Variance6679.6238
MonotonicityNot monotonic
2023-12-12T14:24:14.460829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200 6
 
5.7%
150 4
 
3.8%
130 4
 
3.8%
145 3
 
2.8%
135 3
 
2.8%
160 3
 
2.8%
175 3
 
2.8%
120 3
 
2.8%
75 3
 
2.8%
70 3
 
2.8%
Other values (58) 71
67.0%
ValueCountFrequency (%)
18 1
 
0.9%
33 1
 
0.9%
41 1
 
0.9%
57 1
 
0.9%
62 1
 
0.9%
64 1
 
0.9%
70 3
2.8%
75 3
2.8%
80 2
1.9%
81 1
 
0.9%
ValueCountFrequency (%)
530 1
0.9%
400 2
1.9%
347 1
0.9%
340 1
0.9%
300 1
0.9%
295 1
0.9%
275 1
0.9%
270 1
0.9%
266 1
0.9%
260 1
0.9%

사업비 집행내역 보조금 소계(60%)
Text

Distinct89
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:14.687112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.7924528
Min length7

Characters and Unicode

Total characters1038
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

Unique82 ?
Unique (%)77.4%

Sample

1st row3,000,000
2nd row3,000,000
3rd row3,000,000
4th row1,379,400
5th row1,584,000
ValueCountFrequency (%)
3,000,000 8
 
7.5%
4,000,000 7
 
6.6%
1,386,000 3
 
2.8%
1,518,000 3
 
2.8%
1,716,000 2
 
1.9%
1,254,000 2
 
1.9%
3,234,000 2
 
1.9%
1,188,000 2
 
1.9%
1,650,000 2
 
1.9%
2,892,000 1
 
0.9%
Other values (74) 74
69.8%
2023-12-12T14:24:15.119591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 356
34.3%
, 207
19.9%
94
 
9.1%
2 71
 
6.8%
1 55
 
5.3%
8 46
 
4.4%
4 44
 
4.2%
3 43
 
4.1%
6 37
 
3.6%
5 36
 
3.5%
Other values (2) 49
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 737
71.0%
Other Punctuation 207
 
19.9%
Space Separator 94
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 356
48.3%
2 71
 
9.6%
1 55
 
7.5%
8 46
 
6.2%
4 44
 
6.0%
3 43
 
5.8%
6 37
 
5.0%
5 36
 
4.9%
7 26
 
3.5%
9 23
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 207
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1038
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 356
34.3%
, 207
19.9%
94
 
9.1%
2 71
 
6.8%
1 55
 
5.3%
8 46
 
4.4%
4 44
 
4.2%
3 43
 
4.1%
6 37
 
3.6%
5 36
 
3.5%
Other values (2) 49
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 356
34.3%
, 207
19.9%
94
 
9.1%
2 71
 
6.8%
1 55
 
5.3%
8 46
 
4.4%
4 44
 
4.2%
3 43
 
4.1%
6 37
 
3.6%
5 36
 
3.5%
Other values (2) 49
 
4.7%

사업비 집행내역 국비(30%)
Text

Distinct89
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:15.392932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.1886792
Min length7

Characters and Unicode

Total characters974
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

Unique82 ?
Unique (%)77.4%

Sample

1st row1,500,000
2nd row1,500,000
3rd row1,500,000
4th row689,700
5th row792,000
ValueCountFrequency (%)
1,500,000 8
 
7.5%
2,000,000 7
 
6.6%
693,000 3
 
2.8%
759,000 3
 
2.8%
858,000 2
 
1.9%
627,000 2
 
1.9%
1,617,000 2
 
1.9%
594,000 2
 
1.9%
825,000 2
 
1.9%
1,446,000 1
 
0.9%
Other values (74) 74
69.8%
2023-12-12T14:24:15.786067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 338
34.7%
, 175
18.0%
94
 
9.7%
1 81
 
8.3%
2 43
 
4.4%
5 41
 
4.2%
9 38
 
3.9%
7 37
 
3.8%
6 33
 
3.4%
8 33
 
3.4%
Other values (2) 61
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 705
72.4%
Other Punctuation 175
 
18.0%
Space Separator 94
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 338
47.9%
1 81
 
11.5%
2 43
 
6.1%
5 41
 
5.8%
9 38
 
5.4%
7 37
 
5.2%
6 33
 
4.7%
8 33
 
4.7%
4 32
 
4.5%
3 29
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 175
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 338
34.7%
, 175
18.0%
94
 
9.7%
1 81
 
8.3%
2 43
 
4.4%
5 41
 
4.2%
9 38
 
3.9%
7 37
 
3.8%
6 33
 
3.4%
8 33
 
3.4%
Other values (2) 61
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 338
34.7%
, 175
18.0%
94
 
9.7%
1 81
 
8.3%
2 43
 
4.4%
5 41
 
4.2%
9 38
 
3.9%
7 37
 
3.8%
6 33
 
3.4%
8 33
 
3.4%
Other values (2) 61
 
6.3%

사업비 집행내역 시비(15%)
Text

Distinct89
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:16.058710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.0660377
Min length7

Characters and Unicode

Total characters855
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

Unique82 ?
Unique (%)77.4%

Sample

1st row750,000
2nd row750,000
3rd row750,000
4th row344,850
5th row396,000
ValueCountFrequency (%)
750,000 8
 
7.5%
1,000,000 7
 
6.6%
346,500 3
 
2.8%
379,500 3
 
2.8%
429,000 2
 
1.9%
313,500 2
 
1.9%
808,500 2
 
1.9%
297,000 2
 
1.9%
412,500 2
 
1.9%
723,000 1
 
0.9%
Other values (74) 74
69.8%
2023-12-12T14:24:16.476752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 49
 
5.7%
6 41
 
4.8%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 645
75.4%
Other Punctuation 116
 
13.6%
Space Separator 94
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 284
44.0%
5 75
 
11.6%
7 49
 
7.6%
6 41
 
6.4%
3 40
 
6.2%
4 40
 
6.2%
1 31
 
4.8%
9 31
 
4.8%
8 30
 
4.7%
2 24
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 116
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 49
 
5.7%
6 41
 
4.8%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 49
 
5.7%
6 41
 
4.8%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

사업비 집행내역구비(15%)
Text

Distinct89
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:16.746407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.0660377
Min length7

Characters and Unicode

Total characters855
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

Unique82 ?
Unique (%)77.4%

Sample

1st row750,000
2nd row750,000
3rd row750,000
4th row344,850
5th row396,000
ValueCountFrequency (%)
750,000 8
 
7.5%
1,000,000 7
 
6.6%
346,500 3
 
2.8%
379,500 3
 
2.8%
429,000 2
 
1.9%
313,500 2
 
1.9%
808,500 2
 
1.9%
297,000 2
 
1.9%
412,500 2
 
1.9%
723,000 1
 
0.9%
Other values (74) 74
69.8%
2023-12-12T14:24:17.313947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 48
 
5.6%
6 42
 
4.9%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 645
75.4%
Other Punctuation 116
 
13.6%
Space Separator 94
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 284
44.0%
5 75
 
11.6%
7 48
 
7.4%
6 42
 
6.5%
3 40
 
6.2%
4 40
 
6.2%
1 31
 
4.8%
9 31
 
4.8%
8 30
 
4.7%
2 24
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 116
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 48
 
5.6%
6 42
 
4.9%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 284
33.2%
, 116
13.6%
94
 
11.0%
5 75
 
8.8%
7 48
 
5.6%
6 42
 
4.9%
3 40
 
4.7%
4 40
 
4.7%
1 31
 
3.6%
9 31
 
3.6%
Other values (2) 54
 
6.3%

사업비 집행내역자부담 (40%)
Text

Distinct93
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T14:24:17.650645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.5471698
Min length7

Characters and Unicode

Total characters1012
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

Unique84 ?
Unique (%)79.2%

Sample

1st row2,200,000
2nd row2,200,000
3rd row2,000,000
4th row961,000
5th row1,056,000
ValueCountFrequency (%)
2,000,000 5
 
4.7%
2,666,670 4
 
3.8%
924,000 3
 
2.8%
1,012,000 3
 
2.8%
1,144,000 2
 
1.9%
1,100,000 2
 
1.9%
792,000 2
 
1.9%
2,156,000 2
 
1.9%
2,200,000 2
 
1.9%
2,666,660 2
 
1.9%
Other values (78) 79
74.5%
2023-12-12T14:24:18.135437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 329
32.5%
, 194
19.2%
94
 
9.3%
1 83
 
8.2%
2 80
 
7.9%
6 56
 
5.5%
8 38
 
3.8%
4 36
 
3.6%
3 30
 
3.0%
7 27
 
2.7%
Other values (2) 45
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 724
71.5%
Other Punctuation 194
 
19.2%
Space Separator 94
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 329
45.4%
1 83
 
11.5%
2 80
 
11.0%
6 56
 
7.7%
8 38
 
5.2%
4 36
 
5.0%
3 30
 
4.1%
7 27
 
3.7%
9 23
 
3.2%
5 22
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 194
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 329
32.5%
, 194
19.2%
94
 
9.3%
1 83
 
8.2%
2 80
 
7.9%
6 56
 
5.5%
8 38
 
3.8%
4 36
 
3.6%
3 30
 
3.0%
7 27
 
2.7%
Other values (2) 45
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 329
32.5%
, 194
19.2%
94
 
9.3%
1 83
 
8.2%
2 80
 
7.9%
6 56
 
5.5%
8 38
 
3.8%
4 36
 
3.6%
3 30
 
3.0%
7 27
 
2.7%
Other values (2) 45
 
4.4%

Interactions

2023-12-12T14:24:06.909454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.284883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.597852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.029093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.376068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.711528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.145431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.474764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.802226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:24:18.244450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번설치대상 농경지 읍면설치대상 농경지 지목설치대상 농경지 민통선 내외표시설치대상 농경지 작물명지원 시설 시설명지원 시설 규모(m) 신청지원 시설 규모(m) 최종사업비 집행내역 보조금 소계(60%)사업비 집행내역 국비(30%)사업비 집행내역 시비(15%)사업비 집행내역구비(15%)사업비 집행내역자부담 (40%)
순번1.0000.0000.4060.1090.7660.1940.3850.3800.8010.8010.8010.8010.698
설치대상 농경지 읍면0.0001.0000.8041.0000.9440.6460.3810.3920.8600.8600.8600.8600.847
설치대상 농경지 지목0.4060.8041.0000.6280.8100.3510.5830.6420.9260.9260.9260.9260.889
설치대상 농경지 민통선 내외표시0.1091.0000.6281.0000.9300.8600.2040.1690.9630.9630.9630.9630.952
설치대상 농경지 작물명0.7660.9440.8100.9301.0000.9930.5990.5050.0000.0000.0000.0000.807
지원 시설 시설명0.1940.6460.3510.8600.9931.0000.5710.6010.9970.9970.9970.9970.997
지원 시설 규모(m) 신청0.3850.3810.5830.2040.5990.5711.0000.9990.0000.0000.0000.0000.000
지원 시설 규모(m) 최종0.3800.3920.6420.1690.5050.6010.9991.0000.0000.0000.0000.0000.000
사업비 집행내역 보조금 소계(60%)0.8010.8600.9260.9630.0000.9970.0000.0001.0001.0001.0001.0001.000
사업비 집행내역 국비(30%)0.8010.8600.9260.9630.0000.9970.0000.0001.0001.0001.0001.0001.000
사업비 집행내역 시비(15%)0.8010.8600.9260.9630.0000.9970.0000.0001.0001.0001.0001.0001.000
사업비 집행내역구비(15%)0.8010.8600.9260.9630.0000.9970.0000.0001.0001.0001.0001.0001.000
사업비 집행내역자부담 (40%)0.6980.8470.8890.9520.8070.9970.0000.0001.0001.0001.0001.0001.000
2023-12-12T14:24:18.415674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치대상 농경지 지목설치대상 농경지 민통선 내외표시지원 시설 시설명설치대상 농경지 읍면
설치대상 농경지 지목1.0000.4600.1320.450
설치대상 농경지 민통선 내외표시0.4601.0000.6550.984
지원 시설 시설명0.1320.6551.0000.572
설치대상 농경지 읍면0.4500.9840.5721.000
2023-12-12T14:24:18.543402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지원 시설 규모(m) 신청지원 시설 규모(m) 최종설치대상 농경지 읍면설치대상 농경지 지목설치대상 농경지 민통선 내외표시지원 시설 시설명
순번1.000-0.269-0.2620.0000.1320.1020.000
지원 시설 규모(m) 신청-0.2691.0000.9990.2390.2170.1950.320
지원 시설 규모(m) 최종-0.2620.9991.0000.2470.2520.1600.344
설치대상 농경지 읍면0.0000.2390.2471.0000.4500.9840.572
설치대상 농경지 지목0.1320.2170.2520.4501.0000.4600.132
설치대상 농경지 민통선 내외표시0.1020.1950.1600.9840.4601.0000.655
지원 시설 시설명0.0000.3200.3440.5720.1320.6551.000

Missing values

2023-12-12T14:24:07.315819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:24:07.591097image/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

순번신청인 주소신청인 성명설치대상 농경지 읍면설치대상 농경지 소재지설치대상 농경지 지목설치대상 농경지 민통선 내외표시설치대상 농경지 면적(㎡)설치대상 농경지 작물명지원 시설 시설명지원 시설 규모(m) 신청지원 시설 규모(m) 최종사업비 집행내역 보조금 소계(60%)사업비 집행내역 국비(30%)사업비 집행내역 시비(15%)사업비 집행내역구비(15%)사업비 집행내역자부담 (40%)
01대전광역시 서구 계백로776번길 154(관저동)박미숙산내동구도동 283-1전외3,683특용작물철선울타리3403403,000,0001,500,000750,000750,0002,200,000
12대전광역시 중구 돌다리로8번길 76(석교동)박정규대청동주산동 270, 270-2답외1,456고구마, 고추철선울타리2012013,000,0001,500,000750,000750,0002,200,000
23대전광역시 동구 비룡로14번길 25(비룡동)권선창대청동비룡동 326답외4,026벼철선울타리2002003,000,0001,500,000750,000750,0002,000,000
34대전광역시 동구 비룡로14번길 25(비룡동)민선희대청동비룡동 327-1,2답(327-1), 전(327-2)외2,142포도, 콩철선울타리56571,379,400689,700344,850344,850961,000
45세종특별자치시 달빛로 211, 1022-2201(아름동, 범지기마을10단지)유지훈대청동효평동 373-1,2답(373-1), 전(373-2)외1,018고구마, 콩, 고추 등 밭작물철선울타리86861,584,000792,000396,000396,0001,056,000
56대전광역시 대덕구 계족산로 135, 406-104(송촌동, 선비마을아파트)유영준대청동효평동 374-3전외1,000고구마, 콩, 고추 등 밭작물철선울타리95951,650,000825,000412,500412,5001,100,000
67대전광역시 중구 충무로107번길 100, 105-903(대흥동, 센트럴자이)박성관산내동낭월동 10-10전외2,500고구마, 매실 등 밭작물철선울타리2002003,000,0001,500,000750,000750,0002,150,000
78대전광역시 동구 동구청로203번길 35, 102-403(판암동, 미리내아파트)송일영산내동낭월동 12-11전외900고구마 등 밭작물철선울타리<NA>701,716,000858,000429,000429,0001,144,000
89대전광역시 동구 냉천로 323-1(직동)김응명대청동직동 산56-3임야외45,000고구마 등 밭작물철선울타리2002003,000,0001,500,000750,000750,0002,000,000
910대전광역시 동구 대청호수로633번길 54(추동)송신호대청동추동 572답외2,300벼철선울타리1901902,688,0001,344,000672,000672,0001,792,000
순번신청인 주소신청인 성명설치대상 농경지 읍면설치대상 농경지 소재지설치대상 농경지 지목설치대상 농경지 민통선 내외표시설치대상 농경지 면적(㎡)설치대상 농경지 작물명지원 시설 시설명지원 시설 규모(m) 신청지원 시설 규모(m) 최종사업비 집행내역 보조금 소계(60%)사업비 집행내역 국비(30%)사업비 집행내역 시비(15%)사업비 집행내역구비(15%)사업비 집행내역자부담 (40%)
9622대덕구 산디로15번길 149 (장동박정규대덕구장동 100-1, 100-2과수원외9,501과수, 채소류철선울타리81811,254,000627,000313,500313,500836,000
9723대덕구 산디로15번길 147 (장동)박종수대덕구장동 산27-10, 산27-11임야외36,546감, 채소류철선울타리92921,386,000693,000346,500346,500924,000
9824유성구 엑스포로 448, 103동 701호 (전민동, 엑스포@)김성자대덕구장동 산27-9임야외1,211채소류철선울타리90901,254,000627,000313,500313,500836,000
9925대덕구 장동로 271-1 (장동)박용오대덕구장동 94전외1,987채소류철선울타리6262858,000429,000214,500214,500572,000
10026대덕구 신탄진로218번길 62 102동 1606 (와동, 현대@)박종훈대덕구장동 96전외952채소류철선울타리3333462,000231,000115,500115,500308,000
10127대덕구 산디로15번길 110 (장동)송문수대덕구장동 산41임야외8,231과수, 채소류철선울타리2452453,828,0001,914,000957,000957,0002,552,000
10228유성구 학하로 33, 102동 1401호 (계산동, 학의뜰아@)김하안대덕구연축동 산1-8임야외1,003배, 과수철선울타리80801,518,000759,000379,500379,5001,012,000
10329대덕구 계족로663번길 23, 3동 1006호 (법동, 유원@)유영란외1대덕구연축동 4전외575채소류, 콩철선울타리64641,174,800587,400293,700293,700783,200
10430대덕구 송촌북로31, 3층 (중리동)황덕선외2대덕구신일동 1-27임야외1,560고구마, 콩, 채소류철선울타리92921,650,000825,000412,500412,5001,100,000
10531유성구 가정로 310-7 (도룡동)박문규대덕구송촌동 산1-18임야외3,669고추,과수 등철선울타리1621532,415,8001,207,900603,950603,9501,610,200