Overview

Dataset statistics

Number of variables9
Number of observations1648
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.0 KiB
Average record size in memory72.1 B

Variable types

Categorical3
Text5
DateTime1

Dataset

Description충청북도 제천시의 등산로현황 공공데이터입니다.소재지, 지번, 공부지목, 필지면적, 전용면적, 전용목적, 허가일자, 데이터기준일로 구성되어 있습니다.
Author충청북도 제천시
URLhttps://www.data.go.kr/data/15124044/fileData.do

Alerts

데이타기준일자 has constant value ""Constant
업무구분 is highly imbalanced (79.7%)Imbalance

Reproduction

Analysis started2023-12-12 21:18:38.443164
Analysis finished2023-12-12 21:18:39.149278
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업무구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
농촌-농지전용협의_신규
1561 
농촌-농지전용신고_신규
 
79
농촌-농지전용허가_신규
 
8

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농촌-농지전용허가_신규
2nd row농촌-농지전용허가_신규
3rd row농촌-농지전용허가_신규
4th row농촌-농지전용허가_신규
5th row농촌-농지전용허가_신규

Common Values

ValueCountFrequency (%)
농촌-농지전용협의_신규 1561
94.7%
농촌-농지전용신고_신규 79
 
4.8%
농촌-농지전용허가_신규 8
 
0.5%

Length

2023-12-13T06:18:39.224329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:18:39.363676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농촌-농지전용협의_신규 1561
94.7%
농촌-농지전용신고_신규 79
 
4.8%
농촌-농지전용허가_신규 8
 
0.5%

소재지
Text

Distinct100
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-13T06:18:39.611597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length15.412621
Min length12

Characters and Unicode

Total characters25400
Distinct characters100
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

Unique11 ?
Unique (%)0.7%

Sample

1st row충청북도 제천시 수산면 서곡리
2nd row충청북도 제천시 백운면 애련리
3rd row충청북도 제천시 백운면 평동리
4th row충청북도 제천시 봉양읍 연박리
5th row충청북도 제천시 봉양읍 명도리
ValueCountFrequency (%)
충청북도 1648
27.7%
제천시 1648
27.7%
봉양읍 581
 
9.8%
청전동 257
 
4.3%
백운면 169
 
2.8%
연박리 165
 
2.8%
주포리 108
 
1.8%
천남동 85
 
1.4%
장평리 85
 
1.4%
원박리 83
 
1.4%
Other values (95) 1122
18.9%
2023-12-13T06:18:40.011405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5951
23.4%
청 1948
 
7.7%
천 1740
 
6.9%
도 1714
 
6.7%
시 1681
 
6.6%
제 1662
 
6.5%
북 1652
 
6.5%
충 1648
 
6.5%
리 1007
 
4.0%
동 670
 
2.6%
Other values (90) 5727
22.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19449
76.6%
Space Separator 5951
 
23.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 1948
 
10.0%
천 1740
 
8.9%
도 1714
 
8.8%
시 1681
 
8.6%
제 1662
 
8.5%
북 1652
 
8.5%
충 1648
 
8.5%
리 1007
 
5.2%
동 670
 
3.4%
양 593
 
3.0%
Other values (89) 5134
26.4%
Space Separator
ValueCountFrequency (%)
5951
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19449
76.6%
Common 5951
 
23.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 1948
 
10.0%
천 1740
 
8.9%
도 1714
 
8.8%
시 1681
 
8.6%
제 1662
 
8.5%
북 1652
 
8.5%
충 1648
 
8.5%
리 1007
 
5.2%
동 670
 
3.4%
양 593
 
3.0%
Other values (89) 5134
26.4%
Common
ValueCountFrequency (%)
5951
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19449
76.6%
ASCII 5951
 
23.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5951
100.0%
Hangul
ValueCountFrequency (%)
청 1948
 
10.0%
천 1740
 
8.9%
도 1714
 
8.8%
시 1681
 
8.6%
제 1662
 
8.5%
북 1652
 
8.5%
충 1648
 
8.5%
리 1007
 
5.2%
동 670
 
3.4%
양 593
 
3.0%
Other values (89) 5134
26.4%

지번
Text

Distinct1492
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-13T06:18:40.407250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.0036408
Min length9

Characters and Unicode

Total characters14838
Distinct characters13
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

Unique1352 ?
Unique (%)82.0%

Sample

1st row0329-0003
2nd row0711-0004
3rd row0628-0001
4th row0054-0000
5th row0097-0002
ValueCountFrequency (%)
0031-0011 4
 
0.2%
0206-0000 4
 
0.2%
0694-0000 4
 
0.2%
0378-0000 3
 
0.2%
0046-0000 3
 
0.2%
0145-0000 3
 
0.2%
0243-0001 3
 
0.2%
0918-0005 3
 
0.2%
산 3
 
0.2%
0283-0000 3
 
0.2%
Other values (1483) 1618
98.0%
2023-12-13T06:18:40.922794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6985
47.1%
- 1648
 
11.1%
1 1162
 
7.8%
2 1001
 
6.7%
3 772
 
5.2%
4 667
 
4.5%
6 611
 
4.1%
5 565
 
3.8%
7 550
 
3.7%
8 448
 
3.0%
Other values (3) 429
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13184
88.9%
Dash Punctuation 1648
 
11.1%
Other Letter 3
 
< 0.1%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6985
53.0%
1 1162
 
8.8%
2 1001
 
7.6%
3 772
 
5.9%
4 667
 
5.1%
6 611
 
4.6%
5 565
 
4.3%
7 550
 
4.2%
8 448
 
3.4%
9 423
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 1648
100.0%
Other Letter
ValueCountFrequency (%)
산 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14835
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6985
47.1%
- 1648
 
11.1%
1 1162
 
7.8%
2 1001
 
6.7%
3 772
 
5.2%
4 667
 
4.5%
6 611
 
4.1%
5 565
 
3.8%
7 550
 
3.7%
8 448
 
3.0%
Other values (2) 426
 
2.9%
Hangul
ValueCountFrequency (%)
산 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14835
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6985
47.1%
- 1648
 
11.1%
1 1162
 
7.8%
2 1001
 
6.7%
3 772
 
5.2%
4 667
 
4.5%
6 611
 
4.1%
5 565
 
3.8%
7 550
 
3.7%
8 448
 
3.0%
Other values (2) 426
 
2.9%
Hangul
ValueCountFrequency (%)
산 3
100.0%

공부지목
Categorical

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
전
880 
답
638 
구거
 
69
과수원
 
36
도로
 
20

Length

Max length3
Median length1
Mean length1.1007282
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전 880
53.4%
답 638
38.7%
구거 69
 
4.2%
과수원 36
 
2.2%
도로 20
 
1.2%
제방 5
 
0.3%

Length

2023-12-13T06:18:41.144379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:18:41.278268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전 880
53.4%
답 638
38.7%
구거 69
 
4.2%
과수원 36
 
2.2%
도로 20
 
1.2%
제방 5
 
0.3%

필지면적
Text

Distinct1090
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-13T06:18:41.719412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5351942
Min length1

Characters and Unicode

Total characters5826
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique766 ?
Unique (%)46.5%

Sample

1st row80
2nd row1,494
3rd row440
4th row2,456
5th row202
ValueCountFrequency (%)
1 19
 
1.2%
992 9
 
0.5%
16 8
 
0.5%
330 8
 
0.5%
2 7
 
0.4%
10 6
 
0.4%
26 6
 
0.4%
20 6
 
0.4%
46 6
 
0.4%
827 6
 
0.4%
Other values (1080) 1567
95.1%
2023-12-13T06:18:42.345782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 882
15.1%
2 680
11.7%
, 607
10.4%
3 535
9.2%
4 522
9.0%
5 460
7.9%
6 459
7.9%
9 441
7.6%
8 430
7.4%
0 407
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5219
89.6%
Other Punctuation 607
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 882
16.9%
2 680
13.0%
3 535
10.3%
4 522
10.0%
5 460
8.8%
6 459
8.8%
9 441
8.4%
8 430
8.2%
0 407
7.8%
7 403
7.7%
Other Punctuation
ValueCountFrequency (%)
, 607
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5826
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 882
15.1%
2 680
11.7%
, 607
10.4%
3 535
9.2%
4 522
9.0%
5 460
7.9%
6 459
7.9%
9 441
7.6%
8 430
7.4%
0 407
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 882
15.1%
2 680
11.7%
, 607
10.4%
3 535
9.2%
4 522
9.0%
5 460
7.9%
6 459
7.9%
9 441
7.6%
8 430
7.4%
0 407
7.0%

전용면적
Text

Distinct913
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-13T06:18:42.749688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1055825
Min length1

Characters and Unicode

Total characters5118
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique567 ?
Unique (%)34.4%

Sample

1st row80
2nd row1,494
3rd row91
4th row77
5th row56
ValueCountFrequency (%)
1 22
 
1.3%
16 12
 
0.7%
660 12
 
0.7%
8 11
 
0.7%
2 10
 
0.6%
91 9
 
0.5%
7 9
 
0.5%
3 9
 
0.5%
330 9
 
0.5%
24 8
 
0.5%
Other values (903) 1537
93.3%
2023-12-13T06:18:43.319335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 752
14.7%
2 620
12.1%
3 500
9.8%
6 460
9.0%
4 439
8.6%
5 438
8.6%
9 423
8.3%
0 391
7.6%
8 385
7.5%
7 372
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4780
93.4%
Other Punctuation 338
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 752
15.7%
2 620
13.0%
3 500
10.5%
6 460
9.6%
4 439
9.2%
5 438
9.2%
9 423
8.8%
0 391
8.2%
8 385
8.1%
7 372
7.8%
Other Punctuation
ValueCountFrequency (%)
, 338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 752
14.7%
2 620
12.1%
3 500
9.8%
6 460
9.0%
4 439
8.6%
5 438
8.6%
9 423
8.3%
0 391
7.6%
8 385
7.5%
7 372
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 752
14.7%
2 620
12.1%
3 500
9.8%
6 460
9.0%
4 439
8.6%
5 438
8.6%
9 423
8.3%
0 391
7.6%
8 385
7.5%
7 372
7.3%

전용목적
Text

Distinct293
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-13T06:18:43.610349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length37
Mean length28.199636
Min length4

Characters and Unicode

Total characters46473
Distinct characters218
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)10.7%

Sample

1st row민간기타 (산림화에 따른 농지전용)
2nd row어업용 (다슬기 양식장 부지조성)
3rd row주거시설 (단독주택 부지증설)
4th row주거시설 (단독주택 진출입로 부지조성)
5th row공공기타 (영농폐비닐 공동집하장 부지조성)
ValueCountFrequency (%)
도로철도항만공항 557
 
7.7%
철도 477
 
6.6%
건설사업 477
 
6.6%
실시계획변경(9차 477
 
6.6%
중앙선(원주~제천 477
 
6.6%
공공기타 459
 
6.3%
주거시설 285
 
3.9%
신축 276
 
3.8%
단독주택 265
 
3.6%
의림지뜰 257
 
3.5%
Other values (257) 3271
44.9%
2023-12-13T06:18:44.074678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5637
 
12.1%
( 2896
 
6.2%
) 2894
 
6.2%
도 1725
 
3.7%
공 1559
 
3.4%
지 1176
 
2.5%
설 1167
 
2.5%
시 1151
 
2.5%
주 1116
 
2.4%
항 1114
 
2.4%
Other values (208) 26038
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33318
71.7%
Space Separator 5637
 
12.1%
Open Punctuation 2896
 
6.2%
Close Punctuation 2894
 
6.2%
Decimal Number 1009
 
2.2%
Math Symbol 484
 
1.0%
Other Punctuation 136
 
0.3%
Dash Punctuation 99
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1725
 
5.2%
공 1559
 
4.7%
지 1176
 
3.5%
설 1167
 
3.5%
시 1151
 
3.5%
주 1116
 
3.3%
항 1114
 
3.3%
철 1036
 
3.1%
로 924
 
2.8%
천 866
 
2.6%
Other values (188) 21484
64.5%
Decimal Number
ValueCountFrequency (%)
9 479
47.5%
2 156
 
15.5%
4 98
 
9.7%
1 93
 
9.2%
3 58
 
5.7%
6 44
 
4.4%
7 41
 
4.1%
5 17
 
1.7%
0 12
 
1.2%
8 11
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 62
45.6%
· 52
38.2%
. 16
 
11.8%
: 5
 
3.7%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
5637
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2896
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2894
100.0%
Math Symbol
ValueCountFrequency (%)
~ 484
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33318
71.7%
Common 13155
 
28.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1725
 
5.2%
공 1559
 
4.7%
지 1176
 
3.5%
설 1167
 
3.5%
시 1151
 
3.5%
주 1116
 
3.3%
항 1114
 
3.3%
철 1036
 
3.1%
로 924
 
2.8%
천 866
 
2.6%
Other values (188) 21484
64.5%
Common
ValueCountFrequency (%)
5637
42.9%
( 2896
22.0%
) 2894
22.0%
~ 484
 
3.7%
9 479
 
3.6%
2 156
 
1.2%
- 99
 
0.8%
4 98
 
0.7%
1 93
 
0.7%
, 62
 
0.5%
Other values (10) 257
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33318
71.7%
ASCII 13103
 
28.2%
None 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5637
43.0%
( 2896
22.1%
) 2894
22.1%
~ 484
 
3.7%
9 479
 
3.7%
2 156
 
1.2%
- 99
 
0.8%
4 98
 
0.7%
1 93
 
0.7%
, 62
 
0.5%
Other values (9) 205
 
1.6%
Hangul
ValueCountFrequency (%)
도 1725
 
5.2%
공 1559
 
4.7%
지 1176
 
3.5%
설 1167
 
3.5%
시 1151
 
3.5%
주 1116
 
3.3%
항 1114
 
3.3%
철 1036
 
3.1%
로 924
 
2.8%
천 866
 
2.6%
Other values (188) 21484
64.5%
None
ValueCountFrequency (%)
· 52
100.0%

허가일자
Date

Distinct220
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
Minimum2022-01-03 00:00:00
Maximum2022-12-29 00:00:00
2023-12-13T06:18:44.239132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:18:44.408518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이타기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-09-25
1648 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-25
2nd row2023-09-25
3rd row2023-09-25
4th row2023-09-25
5th row2023-09-25

Common Values

ValueCountFrequency (%)
2023-09-25 1648
100.0%

Length

2023-12-13T06:18:44.574977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:18:44.676917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-25 1648
100.0%

Correlations

2023-12-13T06:18:44.742062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무구분소재지공부지목
업무구분1.0000.7270.229
소재지0.7271.0000.591
공부지목0.2290.5911.000
2023-12-13T06:18:44.833617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무구분공부지목
업무구분1.0000.097
공부지목0.0971.000
2023-12-13T06:18:44.940538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업무구분공부지목
업무구분1.0000.097
공부지목0.0971.000

Missing values

2023-12-13T06:18:38.909410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:18:39.080177image/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

업무구분소재지지번공부지목필지면적전용면적전용목적허가일자데이타기준일자
0농촌-농지전용허가_신규충청북도 제천시 수산면 서곡리0329-0003전8080민간기타 (산림화에 따른 농지전용)2022-12-292023-09-25
1농촌-농지전용허가_신규충청북도 제천시 백운면 애련리0711-0004전1,4941,494어업용 (다슬기 양식장 부지조성)2022-10-052023-09-25
2농촌-농지전용허가_신규충청북도 제천시 백운면 평동리0628-0001전44091주거시설 (단독주택 부지증설)2022-08-292023-09-25
3농촌-농지전용허가_신규충청북도 제천시 봉양읍 연박리0054-0000전2,45677주거시설 (단독주택 진출입로 부지조성)2022-04-122023-09-25
4농촌-농지전용허가_신규충청북도 제천시 봉양읍 명도리0097-0002전20256공공기타 (영농폐비닐 공동집하장 부지조성)2022-03-242023-09-25
5농촌-농지전용허가_신규충청북도 제천시 수산면 수곡리0695-0000전1,7921,792농업용 (산림화로 인한 임야로 농지 전용)2022-09-062023-09-25
6농촌-농지전용허가_신규충청북도 제천시 수산면 율지리0110-0000전294215민간기타 (마을회관설치)2022-06-222023-09-25
7농촌-농지전용허가_신규충청북도 제천시 수산면 대전리0757-0000전2,2212,221민간기타 (산림화로 인한 농지전용)2022-01-262023-09-25
8농촌-농지전용신고_신규충청북도 제천시 봉양읍 삼거리1230-0006전4040농업용 (농업용 저온창고 신축의 진, 출입로)2022-12-282023-09-25
9농촌-농지전용신고_신규충청북도 제천시 봉양읍 장평리1045-0000답1,6031,603기타시설 (산림화에 따른 농지전용신고)2022-11-272023-09-25
업무구분소재지지번공부지목필지면적전용면적전용목적허가일자데이타기준일자
1638농촌-농지전용협의_신규충청북도 제천시 청전동0339-0000답2,9032,903공공기타 (의림지뜰 자연치유 특구 지정)2022-01-102023-09-25
1639농촌-농지전용협의_신규충청북도 제천시 덕산면 도전리1555-0000답8,5872,871민간기타 (야영장 시설 신축 부지 조성)2022-01-052023-09-25
1640농촌-농지전용협의_신규충청북도 제천시 덕산면 도전리1561-0000전844109민간기타 (야영장 시설 신축 부지 조성)2022-01-052023-09-25
1641농촌-농지전용협의_신규충청북도 제천시 백운면 운학리0804-0009전548548민간기타 (제1종근생(사무소) 부지조성)2022-01-052023-09-25
1642농촌-농지전용협의_신규충청북도 제천시 하소동0239-0003답2,6192,619민간기타 (야영장 부지조성)2022-01-052023-09-25
1643농촌-농지전용협의_신규충청북도 제천시 고암동1060-0007전992954민간기타 (일반창고부지조성)2022-01-052023-09-25
1644농촌-농지전용협의_신규충청북도 제천시 백운면 원월리0511-0000전2,154413민간기타 (제2종근린생활시설(사무소) 신축 및 진출입로 부지조성)2022-01-042023-09-25
1645농촌-농지전용협의_신규충청북도 제천시 청풍면 장선리0219-0001전82052민간기타 (제2종근린생활시설(종교집회장) 증축 부지조성)2022-01-042023-09-25
1646농촌-농지전용협의_신규충청북도 제천시 덕산면 수산리0558-0000전1,762902주거시설 (단독주택 신축 및 진·출입로)2022-01-042023-09-25
1647농촌-농지전용협의_신규충청북도 제천시 덕산면 수산리0557-0000전3,84491주거시설 (단독주택 신축 및 진·출입로)2022-01-042023-09-25