Overview

Dataset statistics

Number of variables33
Number of observations10000
Missing cells372
Missing cells (%)0.1%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory2.8 MiB
Average record size in memory289.0 B

Variable types

Numeric14
Categorical12
DateTime2
Text5

Dataset

Description지방자치단체에서 수행한 전국 공사유림의 산림경영활동 중 조림 사업정보를 현행화하여 제공사업기간: 2015~2020년제공 데이터 항목: 사업번호, 사업년도, 사일기간, 사업명, 발주기관, 업체명, 조림장소(필지주소), 조림수종, 묘령, 본수, 산림기능구분 등
Author산림청
URLhttps://www.data.go.kr/data/15110957/fileData.do

Alerts

발주구분 has constant value ""Constant
Dataset has 2 (< 0.1%) duplicate rowsDuplicates
지목명 is highly imbalanced (81.2%)Imbalance
산림자원조성구분코드 is highly imbalanced (80.0%)Imbalance
산림자원조성구분 is highly imbalanced (80.0%)Imbalance
지목코드 has 188 (1.9%) missing valuesMissing
지적 has 181 (1.8%) missing valuesMissing
부번 is highly skewed (γ1 = 30.62998026)Skewed
지적 is highly skewed (γ1 = 98.4273631)Skewed
부번 has 5283 (52.8%) zerosZeros
조림면적 has 8161 (81.6%) zerosZeros
본수 has 233 (2.3%) zerosZeros
활착본수 has 4667 (46.7%) zerosZeros

Reproduction

Analysis started2024-03-14 08:39:52.471685
Analysis finished2024-03-14 08:39:54.007805
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사유림산림사업번호
Real number (ℝ)

Distinct284
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7076849 × 1017
Minimum3.00008 × 1017
Maximum6.52015 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:39:54.205682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.00008 × 1017
5-th percentile3.99022 × 1017
Q14.28005 × 1017
median4.74009 × 1017
Q35.0102 × 1017
95-th percentile5.48008 × 1017
Maximum6.52015 × 1017
Range3.52007 × 1017
Interquartile range (IQR)7.3015 × 1016

Descriptive statistics

Standard deviation5.0843247 × 1016
Coefficient of variation (CV)0.10800053
Kurtosis0.46953822
Mean4.7076849 × 1017
Median Absolute Deviation (MAD)3.4998 × 1016
Skewness-0.0090704827
Sum3.7651542 × 1018
Variance2.5850358 × 1033
MonotonicityNot monotonic
2024-03-14T17:39:54.660015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
426009000000000000 259
 
2.6%
467022000000000000 244
 
2.4%
491001000000000000 239
 
2.4%
489011000000000000 188
 
1.9%
475007000000000000 175
 
1.8%
418021000000000000 175
 
1.8%
425006000000000000 156
 
1.6%
428005000000000000 151
 
1.5%
499014000000000000 133
 
1.3%
420033000000000000 131
 
1.3%
Other values (274) 8149
81.5%
ValueCountFrequency (%)
300008000000000000 13
0.1%
301017000000000000 1
 
< 0.1%
302008000000000000 1
 
< 0.1%
303008000000000000 1
 
< 0.1%
304014000000000000 1
 
< 0.1%
307025000000000000 4
 
< 0.1%
309008000000000000 14
0.1%
310018000000000000 5
 
0.1%
311021000000000000 1
 
< 0.1%
313016000000000000 5
 
0.1%
ValueCountFrequency (%)
652015000000000000 1
 
< 0.1%
652002000000000000 3
 
< 0.1%
651012000000000000 10
 
0.1%
648000000000000000 1
 
< 0.1%
645000000000000000 5
 
0.1%
644000000000000000 9
 
0.1%
642000000000000000 10
 
0.1%
630000000000000000 25
0.2%
571010000000000000 33
0.3%
570004000000000000 36
0.4%

사업년도
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017
3143 
2016
2872 
2015
2477 
2020
1508 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2017
3rd row2017
4th row2017
5th row2015

Common Values

ValueCountFrequency (%)
2017 3143
31.4%
2016 2872
28.7%
2015 2477
24.8%
2020 1508
15.1%

Length

2024-03-14T17:39:55.085938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:39:55.400999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 3143
31.4%
2016 2872
28.7%
2015 2477
24.8%
2020 1508
15.1%

시작일
Date

Distinct448
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-01-01 00:00:00
Maximum2020-12-01 00:00:00
2024-03-14T17:39:55.754940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:39:56.200274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종료일
Date

Distinct509
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-01-01 00:00:00
Maximum2020-12-31 00:00:00
2024-03-14T17:39:56.609956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:39:57.053812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업명
Text

Distinct2045
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T17:39:58.131343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length29
Mean length17.5171
Min length4

Characters and Unicode

Total characters175171
Distinct characters340
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique633 ?
Unique (%)6.3%

Sample

1st row조림사업(큰나무조림)
2nd row2017년 봄철 경제림 조림사업(대강지구)
3rd row2017년 춘기 조림사업(제1권역)
4th row17년 추기조림사업- 경제수
5th row2015년 경제수 조림사업(진도지구)
ValueCountFrequency (%)
조림사업 2467
 
9.1%
2017년 2210
 
8.2%
2016년 1852
 
6.9%
2015년 1785
 
6.6%
2020년 1274
 
4.7%
봄철 1112
 
4.1%
경제수 1062
 
3.9%
춘기 531
 
2.0%
가을철 421
 
1.6%
조림 402
 
1.5%
Other values (1713) 13911
51.5%
2024-03-14T17:39:59.691093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17081
 
9.8%
림 12240
 
7.0%
2 10850
 
6.2%
조 10601
 
6.1%
0 10114
 
5.8%
1 8433
 
4.8%
년 8395
 
4.8%
사 8210
 
4.7%
업 8116
 
4.6%
지 5029
 
2.9%
Other values (330) 76102
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109018
62.2%
Decimal Number 37691
 
21.5%
Space Separator 17081
 
9.8%
Open Punctuation 4915
 
2.8%
Close Punctuation 4913
 
2.8%
Other Punctuation 742
 
0.4%
Dash Punctuation 637
 
0.4%
Math Symbol 71
 
< 0.1%
Connector Punctuation 63
 
< 0.1%
Uppercase Letter 22
 
< 0.1%
Other values (3) 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
림 12240
 
11.2%
조 10601
 
9.7%
년 8395
 
7.7%
사 8210
 
7.5%
업 8116
 
7.4%
지 5029
 
4.6%
경 3313
 
3.0%
제 3255
 
3.0%
구 3115
 
2.9%
수 2775
 
2.5%
Other values (296) 43969
40.3%
Decimal Number
ValueCountFrequency (%)
2 10850
28.8%
0 10114
26.8%
1 8433
22.4%
7 2871
 
7.6%
6 2599
 
6.9%
5 2348
 
6.2%
3 261
 
0.7%
4 171
 
0.5%
9 22
 
0.1%
8 22
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 616
83.0%
/ 60
 
8.1%
· 34
 
4.6%
. 18
 
2.4%
: 14
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
B 11
50.0%
C 7
31.8%
I 2
 
9.1%
A 2
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 4893
99.6%
[ 17
 
0.3%
「 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4891
99.6%
] 17
 
0.3%
」 5
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
a 4
50.0%
h 4
50.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
17081
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 637
100.0%
Math Symbol
ValueCountFrequency (%)
~ 71
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 63
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109018
62.2%
Common 66119
37.7%
Latin 34
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
림 12240
 
11.2%
조 10601
 
9.7%
년 8395
 
7.7%
사 8210
 
7.5%
업 8116
 
7.4%
지 5029
 
4.6%
경 3313
 
3.0%
제 3255
 
3.0%
구 3115
 
2.9%
수 2775
 
2.5%
Other values (296) 43969
40.3%
Common
ValueCountFrequency (%)
17081
25.8%
2 10850
16.4%
0 10114
15.3%
1 8433
12.8%
( 4893
 
7.4%
) 4891
 
7.4%
7 2871
 
4.3%
6 2599
 
3.9%
5 2348
 
3.6%
- 637
 
1.0%
Other values (16) 1402
 
2.1%
Latin
ValueCountFrequency (%)
B 11
32.4%
C 7
20.6%
a 4
 
11.8%
h 4
 
11.8%
Ⅱ 3
 
8.8%
I 2
 
5.9%
A 2
 
5.9%
Ⅰ 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109018
62.2%
ASCII 66105
37.7%
None 44
 
< 0.1%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17081
25.8%
2 10850
16.4%
0 10114
15.3%
1 8433
12.8%
( 4893
 
7.4%
) 4891
 
7.4%
7 2871
 
4.3%
6 2599
 
3.9%
5 2348
 
3.6%
- 637
 
1.0%
Other values (19) 1388
 
2.1%
Hangul
ValueCountFrequency (%)
림 12240
 
11.2%
조 10601
 
9.7%
년 8395
 
7.7%
사 8210
 
7.5%
업 8116
 
7.4%
지 5029
 
4.6%
경 3313
 
3.0%
제 3255
 
3.0%
구 3115
 
2.9%
수 2775
 
2.5%
Other values (296) 43969
40.3%
None
ValueCountFrequency (%)
· 34
77.3%
」 5
 
11.4%
「 5
 
11.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%

발주구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
시군구
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시군구 10000
100.0%

Length

2024-03-14T17:39:59.912228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:00.085287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군구 10000
100.0%

기관명
Text

Distinct201
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T17:40:01.333576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.7498
Min length3

Characters and Unicode

Total characters77498
Distinct characters136
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

Unique16 ?
Unique (%)0.2%

Sample

1st row경상남도 진주시
2nd row전라북도 남원시
3rd row경기도 가평군
4th row충청남도 논산시
5th row전라남도 진도군
ValueCountFrequency (%)
전라남도 2171
 
10.9%
강원도 1811
 
9.1%
전라북도 1103
 
5.5%
경상남도 1057
 
5.3%
경기도 903
 
4.5%
경상북도 896
 
4.5%
충청북도 807
 
4.1%
충청남도 783
 
3.9%
횡성군 328
 
1.6%
군산시 244
 
1.2%
Other values (190) 9783
49.2%
2024-03-14T17:40:02.855824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9886
 
12.8%
도 9761
 
12.6%
군 6437
 
8.3%
남 4327
 
5.6%
시 3921
 
5.1%
전 3346
 
4.3%
라 3274
 
4.2%
경 2932
 
3.8%
북 2820
 
3.6%
강 2106
 
2.7%
Other values (126) 28688
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67612
87.2%
Space Separator 9886
 
12.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9761
 
14.4%
군 6437
 
9.5%
남 4327
 
6.4%
시 3921
 
5.8%
전 3346
 
4.9%
라 3274
 
4.8%
경 2932
 
4.3%
북 2820
 
4.2%
강 2106
 
3.1%
원 2025
 
3.0%
Other values (125) 26663
39.4%
Space Separator
ValueCountFrequency (%)
9886
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67612
87.2%
Common 9886
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9761
 
14.4%
군 6437
 
9.5%
남 4327
 
6.4%
시 3921
 
5.8%
전 3346
 
4.9%
라 3274
 
4.8%
경 2932
 
4.3%
북 2820
 
4.2%
강 2106
 
3.1%
원 2025
 
3.0%
Other values (125) 26663
39.4%
Common
ValueCountFrequency (%)
9886
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67612
87.2%
ASCII 9886
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9886
100.0%
Hangul
ValueCountFrequency (%)
도 9761
 
14.4%
군 6437
 
9.5%
남 4327
 
6.4%
시 3921
 
5.8%
전 3346
 
4.9%
라 3274
 
4.8%
경 2932
 
4.3%
북 2820
 
4.2%
강 2106
 
3.1%
원 2025
 
3.0%
Other values (125) 26663
39.4%

실행주체구분
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
도급·계약(산림조합)
3266 
위탁·대행(산림사업법인)
1858 
기타
1672 
도급·계약(산림사업법인)
674 
산주직접실행(기타)
635 
Other values (12)
1895 

Length

Max length16
Median length13
Mean length9.8898
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row위탁·대행(산림사업법인)
2nd row기타
3rd row위탁·대행(산림사업법인)
4th row산주직접실행(기타)
5th row도급·계약(산림사업법인)

Common Values

ValueCountFrequency (%)
도급·계약(산림조합) 3266
32.7%
위탁·대행(산림사업법인) 1858
18.6%
기타 1672
16.7%
도급·계약(산림사업법인) 674
 
6.7%
산주직접실행(기타) 635
 
6.3%
일반경쟁(산림사업법인) 617
 
6.2%
위탁·대행(산림조합) 453
 
4.5%
수의계약(산림조합) 409
 
4.1%
도급·계약(기타) 112
 
1.1%
지자체직접실행 101
 
1.0%
Other values (7) 203
 
2.0%

Length

2024-03-14T17:40:03.300757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도급·계약(산림조합 3266
32.7%
위탁·대행(산림사업법인 1858
18.6%
기타 1672
16.7%
도급·계약(산림사업법인 674
 
6.7%
산주직접실행(기타 635
 
6.3%
일반경쟁(산림사업법인 617
 
6.2%
위탁·대행(산림조합 453
 
4.5%
수의계약(산림조합 409
 
4.1%
도급·계약(기타 112
 
1.1%
지자체직접실행 101
 
1.0%
Other values (7) 203
 
2.0%

업체명
Text

Distinct849
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T17:40:04.088954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.9389
Min length1

Characters and Unicode

Total characters59389
Distinct characters297
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)1.5%

Sample

1st row(주) 정원
2nd row(유)남강산림개발
3rd row(주)승산
4th row서승항 외 8인
5th row(유)대한산림개발
ValueCountFrequency (%)
기타 1890
 
17.1%
산림조합 487
 
4.4%
주식회사 306
 
2.8%
군산산림조합 233
 
2.1%
장흥군산림조합 158
 
1.4%
신안군산림조합 154
 
1.4%
함평군산림조합 112
 
1.0%
영월군산림조합 104
 
0.9%
산주직접실행 89
 
0.8%
강진군산림조합 88
 
0.8%
Other values (854) 7445
67.3%
2024-03-14T17:40:05.298533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 6606
 
11.1%
림 5676
 
9.6%
조 4630
 
7.8%
합 4471
 
7.5%
주 2892
 
4.9%
군 2654
 
4.5%
( 2317
 
3.9%
) 2317
 
3.9%
기 1929
 
3.2%
타 1890
 
3.2%
Other values (287) 24007
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53490
90.1%
Open Punctuation 2317
 
3.9%
Close Punctuation 2317
 
3.9%
Space Separator 1066
 
1.8%
Decimal Number 144
 
0.2%
Other Symbol 28
 
< 0.1%
Uppercase Letter 15
 
< 0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 6606
 
12.3%
림 5676
 
10.6%
조 4630
 
8.7%
합 4471
 
8.4%
주 2892
 
5.4%
군 2654
 
5.0%
기 1929
 
3.6%
타 1890
 
3.5%
시 1190
 
2.2%
업 758
 
1.4%
Other values (273) 20794
38.9%
Decimal Number
ValueCountFrequency (%)
0 40
27.8%
3 35
24.3%
5 30
20.8%
8 23
16.0%
2 14
 
9.7%
4 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
G 5
33.3%
N 5
33.3%
E 5
33.3%
Open Punctuation
ValueCountFrequency (%)
( 2317
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2317
100.0%
Space Separator
ValueCountFrequency (%)
1066
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53518
90.1%
Common 5856
 
9.9%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 6606
 
12.3%
림 5676
 
10.6%
조 4630
 
8.7%
합 4471
 
8.4%
주 2892
 
5.4%
군 2654
 
5.0%
기 1929
 
3.6%
타 1890
 
3.5%
시 1190
 
2.2%
업 758
 
1.4%
Other values (274) 20822
38.9%
Common
ValueCountFrequency (%)
( 2317
39.6%
) 2317
39.6%
1066
18.2%
0 40
 
0.7%
3 35
 
0.6%
5 30
 
0.5%
8 23
 
0.4%
2 14
 
0.2%
, 12
 
0.2%
4 2
 
< 0.1%
Latin
ValueCountFrequency (%)
G 5
33.3%
N 5
33.3%
E 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53490
90.1%
ASCII 5871
 
9.9%
None 28
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 6606
 
12.3%
림 5676
 
10.6%
조 4630
 
8.7%
합 4471
 
8.4%
주 2892
 
5.4%
군 2654
 
5.0%
기 1929
 
3.6%
타 1890
 
3.5%
시 1190
 
2.2%
업 758
 
1.4%
Other values (273) 20794
38.9%
ASCII
ValueCountFrequency (%)
( 2317
39.5%
) 2317
39.5%
1066
18.2%
0 40
 
0.7%
3 35
 
0.6%
5 30
 
0.5%
8 23
 
0.4%
2 14
 
0.2%
, 12
 
0.2%
G 5
 
0.1%
Other values (3) 12
 
0.2%
None
ValueCountFrequency (%)
㈜ 28
100.0%

지역코드
Real number (ℝ)

Distinct3970
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4327328 × 109
Minimum1.1110115 × 109
Maximum5.013032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:05.720905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110115 × 109
5-th percentile4.1273105 × 109
Q14.273038 × 109
median4.513039 × 109
Q34.686036 × 109
95-th percentile4.874031 × 109
Maximum5.013032 × 109
Range3.9020205 × 109
Interquartile range (IQR)4.12998 × 108

Descriptive statistics

Standard deviation4.6644506 × 108
Coefficient of variation (CV)0.10522743
Kurtosis21.539606
Mean4.4327328 × 109
Median Absolute Deviation (MAD)2.02004 × 108
Skewness-3.8791937
Sum4.4327328 × 1013
Variance2.17571 × 1017
MonotonicityNot monotonic
2024-03-14T17:40:06.190139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4221011300 95
 
0.9%
3171025329 53
 
0.5%
4513032027 44
 
0.4%
4682034028 35
 
0.4%
4684025626 34
 
0.3%
4273038023 34
 
0.3%
4691041023 33
 
0.3%
4611015700 31
 
0.3%
4611010200 31
 
0.3%
4822035023 30
 
0.3%
Other values (3960) 9580
95.8%
ValueCountFrequency (%)
1111011500 2
< 0.1%
1111014000 1
 
< 0.1%
1111018200 1
 
< 0.1%
1111018300 3
< 0.1%
1111018400 2
< 0.1%
1111018500 1
 
< 0.1%
1111018700 3
< 0.1%
1114016200 1
 
< 0.1%
1117013100 1
 
< 0.1%
1120011200 1
 
< 0.1%
ValueCountFrequency (%)
5013032024 1
< 0.1%
5013011900 2
< 0.1%
5013011100 1
< 0.1%
5011032021 1
< 0.1%
5011031022 1
< 0.1%
5011025628 1
< 0.1%
5011025624 1
< 0.1%
5011025339 2
< 0.1%
5011025336 1
< 0.1%
5011025321 2
< 0.1%

시도코드
Real number (ℝ)

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.7544
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:06.589268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile41
Q142
median45
Q346
95-th percentile48
Maximum50
Range39
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6201315
Coefficient of variation (CV)0.10559239
Kurtosis21.948916
Mean43.7544
Median Absolute Deviation (MAD)2
Skewness-3.9161157
Sum437544
Variance21.345615
MonotonicityNot monotonic
2024-03-14T17:40:06.997589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
46 2171
21.7%
42 1811
18.1%
45 1103
11.0%
48 1057
10.6%
41 903
9.0%
47 896
9.0%
43 807
 
8.1%
44 783
 
7.8%
31 137
 
1.4%
11 86
 
0.9%
Other values (7) 246
 
2.5%
ValueCountFrequency (%)
11 86
 
0.9%
26 40
 
0.4%
27 17
 
0.2%
28 30
 
0.3%
29 9
 
0.1%
30 72
 
0.7%
31 137
 
1.4%
36 64
 
0.6%
41 903
9.0%
42 1811
18.1%
ValueCountFrequency (%)
50 14
 
0.1%
48 1057
10.6%
47 896
9.0%
46 2171
21.7%
45 1103
11.0%
44 783
 
7.8%
43 807
 
8.1%
42 1811
18.1%
41 903
9.0%
36 64
 
0.6%

시군구코드
Real number (ℝ)

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean572.6129
Minimum110
Maximum930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:07.406403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile123
Q1220
median730
Q3800
95-th percentile890
Maximum930
Range820
Interquartile range (IQR)580

Descriptive statistics

Standard deviation290.91399
Coefficient of variation (CV)0.50804653
Kurtosis-1.4569164
Mean572.6129
Median Absolute Deviation (MAD)100
Skewness-0.57150872
Sum5726129
Variance84630.952
MonotonicityNot monotonic
2024-03-14T17:40:07.857083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
730 654
 
6.5%
720 510
 
5.1%
130 494
 
4.9%
770 482
 
4.8%
800 444
 
4.4%
150 432
 
4.3%
760 424
 
4.2%
820 390
 
3.9%
710 386
 
3.9%
750 375
 
3.8%
Other values (78) 5409
54.1%
ValueCountFrequency (%)
110 370
3.7%
111 32
 
0.3%
112 4
 
< 0.1%
113 74
 
0.7%
121 15
 
0.1%
123 6
 
0.1%
125 25
 
0.2%
127 6
 
0.1%
130 494
4.9%
131 42
 
0.4%
ValueCountFrequency (%)
930 38
 
0.4%
920 102
1.0%
910 170
1.7%
900 95
0.9%
890 186
1.9%
880 131
1.3%
870 143
1.4%
860 193
1.9%
850 54
 
0.5%
840 144
1.4%

읍면동코드
Real number (ℝ)

Distinct92
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.2246
Minimum0
Maximum470
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:08.103744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile113
Q1310
median335
Q3360
95-th percentile410
Maximum470
Range470
Interquartile range (IQR)50

Descriptive statistics

Standard deviation80.083697
Coefficient of variation (CV)0.25405281
Kurtosis1.3326511
Mean315.2246
Median Absolute Deviation (MAD)25
Skewness-1.3365021
Sum3152246
Variance6413.3985
MonotonicityNot monotonic
2024-03-14T17:40:08.346792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250 988
9.9%
350 950
 
9.5%
320 940
 
9.4%
310 834
 
8.3%
340 797
 
8.0%
330 740
 
7.4%
360 739
 
7.4%
370 649
 
6.5%
380 529
 
5.3%
390 398
 
4.0%
Other values (82) 2436
24.4%
ValueCountFrequency (%)
0 6
 
0.1%
101 60
0.6%
102 83
0.8%
103 34
0.3%
104 23
 
0.2%
105 25
 
0.2%
106 46
0.5%
107 39
0.4%
108 38
0.4%
109 33
 
0.3%
ValueCountFrequency (%)
470 4
 
< 0.1%
460 7
 
0.1%
450 39
 
0.4%
440 46
 
0.5%
430 75
 
0.8%
420 188
1.9%
415 9
 
0.1%
410 187
1.9%
400 352
3.5%
395 10
 
0.1%

시군구읍면동코드(PNU)
Real number (ℝ)

Distinct388
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4327336 × 1018
Minimum1.11101 × 1018
Maximum5.01303 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:08.727448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11101 × 1018
5-th percentile4.12731 × 1018
Q14.27304 × 1018
median4.51304 × 1018
Q34.68604 × 1018
95-th percentile4.87403 × 1018
Maximum5.01303 × 1018
Range3.90202 × 1018
Interquartile range (IQR)4.13 × 1017

Descriptive statistics

Standard deviation4.6644517 × 1017
Coefficient of variation (CV)0.10522743
Kurtosis21.539618
Mean4.4327336 × 1018
Median Absolute Deviation (MAD)2.02 × 1017
Skewness-3.8791949
Sum-1.8979912 × 1017
Variance2.175711 × 1035
MonotonicityNot monotonic
2024-03-14T17:40:09.200828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4513030000000000000 195
 
1.9%
4680030000000000000 186
 
1.9%
4273030000000000000 176
 
1.8%
4273040000000000000 152
 
1.5%
4574030000000000000 143
 
1.4%
4689030000000000000 124
 
1.2%
4272040000000000000 123
 
1.2%
4276030000000000000 121
 
1.2%
4182030000000000000 119
 
1.2%
4691040000000000000 118
 
1.2%
Other values (378) 8543
85.4%
ValueCountFrequency (%)
1111010000000000000 3
 
< 0.1%
1111020000000000000 10
0.1%
1114020000000000000 1
 
< 0.1%
1117010000000000000 1
 
< 0.1%
1120010000000000000 1
 
< 0.1%
1121510000000000000 1
 
< 0.1%
1129010000000000000 4
 
< 0.1%
1132010000000000000 14
0.1%
1135010000000000000 5
 
0.1%
1138010000000000000 1
 
< 0.1%
ValueCountFrequency (%)
5013030000000000000 1
 
< 0.1%
5013010000000000000 3
 
< 0.1%
5011030000000000000 9
 
0.1%
5011010000000000000 1
 
< 0.1%
4889050000000000000 10
 
0.1%
4889040000000000000 35
0.4%
4889030000000000000 8
 
0.1%
4888040000000000000 35
0.4%
4888030000000000000 36
0.4%
4887040000000000000 42
0.4%

산구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8366 
1
1634 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 8366
83.7%
1 1634
 
16.3%

Length

2024-03-14T17:40:09.535590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:09.833390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8366
83.7%
1 1634
 
16.3%

산구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
8366 
산
1634 

Length

Max length2
Median length2
Mean length1.8366
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 8366
83.7%
산 1634
 
16.3%

Length

2024-03-14T17:40:10.165143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:10.334193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 8366
83.7%
산 1634
 
16.3%

본번
Real number (ℝ)

Distinct966
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.6237
Minimum1
Maximum5083
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:10.530283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q135
median80
Q3173
95-th percentile733.05
Maximum5083
Range5082
Interquartile range (IQR)138

Descriptive statistics

Standard deviation292.08755
Coefficient of variation (CV)1.6631443
Kurtosis33.286155
Mean175.6237
Median Absolute Deviation (MAD)55
Skewness4.4693249
Sum1756237
Variance85315.135
MonotonicityNot monotonic
2024-03-14T17:40:10.810329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 143
 
1.4%
2 113
 
1.1%
4 93
 
0.9%
32 83
 
0.8%
39 81
 
0.8%
28 81
 
0.8%
17 80
 
0.8%
43 79
 
0.8%
30 77
 
0.8%
10 77
 
0.8%
Other values (956) 9093
90.9%
ValueCountFrequency (%)
1 143
1.4%
2 113
1.1%
3 57
 
0.6%
4 93
0.9%
5 74
0.7%
6 75
0.8%
7 67
0.7%
8 71
0.7%
9 66
0.7%
10 77
0.8%
ValueCountFrequency (%)
5083 2
< 0.1%
3533 1
< 0.1%
3200 1
< 0.1%
3176 1
< 0.1%
2852 1
< 0.1%
2777 1
< 0.1%
2776 1
< 0.1%
2637 1
< 0.1%
2614 1
< 0.1%
2554 1
< 0.1%

부번
Real number (ℝ)

SKEWED  ZEROS 

Distinct120
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4749
Minimum0
Maximum1055
Zeros5283
Zeros (%)52.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:11.232833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile15
Maximum1055
Range1055
Interquartile range (IQR)2

Descriptive statistics

Standard deviation16.387765
Coefficient of variation (CV)4.7160392
Kurtosis1735.5716
Mean3.4749
Median Absolute Deviation (MAD)0
Skewness30.62998
Sum34749
Variance268.55883
MonotonicityNot monotonic
2024-03-14T17:40:11.670401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5283
52.8%
1 2049
 
20.5%
2 646
 
6.5%
3 382
 
3.8%
4 269
 
2.7%
5 167
 
1.7%
6 163
 
1.6%
7 132
 
1.3%
8 91
 
0.9%
9 73
 
0.7%
Other values (110) 745
 
7.4%
ValueCountFrequency (%)
0 5283
52.8%
1 2049
 
20.5%
2 646
 
6.5%
3 382
 
3.8%
4 269
 
2.7%
5 167
 
1.7%
6 163
 
1.6%
7 132
 
1.3%
8 91
 
0.9%
9 73
 
0.7%
ValueCountFrequency (%)
1055 1
 
< 0.1%
274 2
< 0.1%
231 1
 
< 0.1%
189 1
 
< 0.1%
175 1
 
< 0.1%
174 1
 
< 0.1%
172 1
 
< 0.1%
164 1
 
< 0.1%
159 4
< 0.1%
154 3
< 0.1%

지목코드
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)0.3%
Missing188
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean5.17234
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:12.055619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q35
95-th percentile5
Maximum28
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6603997
Coefficient of variation (CV)0.51435127
Kurtosis29.491607
Mean5.17234
Median Absolute Deviation (MAD)0
Skewness4.7790589
Sum50751
Variance7.0777263
MonotonicityNot monotonic
2024-03-14T17:40:12.438436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
5 8775
87.8%
1 489
 
4.9%
2 191
 
1.9%
14 99
 
1.0%
22 71
 
0.7%
17 47
 
0.5%
8 32
 
0.3%
16 23
 
0.2%
18 18
 
0.2%
28 14
 
0.1%
Other values (15) 53
 
0.5%
(Missing) 188
 
1.9%
ValueCountFrequency (%)
1 489
 
4.9%
2 191
 
1.9%
3 2
 
< 0.1%
4 4
 
< 0.1%
5 8775
87.8%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 32
 
0.3%
9 2
 
< 0.1%
10 7
 
0.1%
ValueCountFrequency (%)
28 14
 
0.1%
27 10
 
0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%
24 2
 
< 0.1%
23 4
 
< 0.1%
22 71
0.7%
21 6
 
0.1%
19 8
 
0.1%
18 18
 
0.2%

지목명
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
임야
8775 
전
 
489
답
 
191
<NA>
 
188
도로
 
99
Other values (21)
 
258

Length

Max length4
Median length2
Mean length1.9739
Min length1

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
임야 8775
87.8%
전 489
 
4.9%
답 191
 
1.9%
<NA> 188
 
1.9%
도로 99
 
1.0%
공원 71
 
0.7%
하천 47
 
0.5%
대 32
 
0.3%
제방 23
 
0.2%
구거 18
 
0.2%
Other values (16) 67
 
0.7%

Length

2024-03-14T17:40:12.842692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
임야 8775
87.8%
전 489
 
4.9%
답 191
 
1.9%
na 188
 
1.9%
도로 99
 
1.0%
공원 71
 
0.7%
하천 47
 
0.5%
대 32
 
0.3%
제방 23
 
0.2%
구거 18
 
0.2%
Other values (16) 67
 
0.7%

지적
Real number (ℝ)

MISSING  SKEWED 

Distinct5044
Distinct (%)51.4%
Missing181
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean180492.81
Minimum0
Maximum8.7325 × 108
Zeros14
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:13.249466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile600
Q15455
median19700
Q353444.5
95-th percentile258664
Maximum8.7325 × 108
Range8.7325 × 108
Interquartile range (IQR)47989.5

Descriptive statistics

Standard deviation8831678.7
Coefficient of variation (CV)48.930916
Kurtosis9730.4168
Mean180492.81
Median Absolute Deviation (MAD)17100
Skewness98.427363
Sum1.7722589 × 109
Variance7.7998549 × 1013
MonotonicityNot monotonic
2024-03-14T17:40:13.683980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 84
 
0.8%
20000 40
 
0.4%
2000 37
 
0.4%
800 37
 
0.4%
5000 34
 
0.3%
3000 30
 
0.3%
4000 29
 
0.3%
15000 28
 
0.3%
1000 27
 
0.3%
6000 27
 
0.3%
Other values (5034) 9446
94.5%
(Missing) 181
 
1.8%
ValueCountFrequency (%)
0 14
0.1%
4 3
 
< 0.1%
10 2
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
16 2
 
< 0.1%
17 2
 
< 0.1%
20 1
 
< 0.1%
31 1
 
< 0.1%
39 1
 
< 0.1%
ValueCountFrequency (%)
873250000 1
 
< 0.1%
26431593 1
 
< 0.1%
20487695 2
< 0.1%
14039935 3
< 0.1%
12648261 2
< 0.1%
9395441 3
< 0.1%
8007818 1
 
< 0.1%
7793312 1
 
< 0.1%
5885032 1
 
< 0.1%
5635059 1
 
< 0.1%

산림자원조성구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11
9688 
13
 
312

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 9688
96.9%
13 312
 
3.1%

Length

2024-03-14T17:40:14.094200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:14.392642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 9688
96.9%
13 312
 
3.1%

산림자원조성구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
조림/갱신
9688 
보완조림
 
312

Length

Max length5
Median length5
Mean length4.9688
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조림/갱신
2nd row조림/갱신
3rd row조림/갱신
4th row조림/갱신
5th row조림/갱신

Common Values

ValueCountFrequency (%)
조림/갱신 9688
96.9%
보완조림 312
 
3.1%

Length

2024-03-14T17:40:14.730821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:15.033913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조림/갱신 9688
96.9%
보완조림 312
 
3.1%

사업구분
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목재생산조림
4582 
산림재해방지조림
1460 
큰나무공익조림
1176 
특용자원조림
727 
바이오순환림조성
602 
Other values (6)
1453 

Length

Max length8
Median length6
Mean length6.5297
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row큰나무공익조림
2nd row목재생산조림
3rd row목재생산조림
4th row목재생산조림
5th row바이오순환림조성

Common Values

ValueCountFrequency (%)
목재생산조림 4582
45.8%
산림재해방지조림 1460
 
14.6%
큰나무공익조림 1176
 
11.8%
특용자원조림 727
 
7.3%
바이오순환림조성 602
 
6.0%
유휴토지조림 441
 
4.4%
기타조림 380
 
3.8%
기타지역특화조림 293
 
2.9%
섬지역산림가꾸기 201
 
2.0%
<NA> 123
 
1.2%

Length

2024-03-14T17:40:15.398514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목재생산조림 4582
45.8%
산림재해방지조림 1460
 
14.6%
큰나무공익조림 1176
 
11.8%
특용자원조림 727
 
7.3%
바이오순환림조성 602
 
6.0%
유휴토지조림 441
 
4.4%
기타조림 380
 
3.8%
기타지역특화조림 293
 
2.9%
섬지역산림가꾸기 201
 
2.0%
na 123
 
1.2%

조림수종코드
Real number (ℝ)

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1177.4561
Minimum1101
Maximum1299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:15.813218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101
5-th percentile1101
Q11104
median1205
Q31250
95-th percentile1299
Maximum1299
Range198
Interquartile range (IQR)146

Descriptive statistics

Standard deviation74.295271
Coefficient of variation (CV)0.063098124
Kurtosis-1.7106584
Mean1177.4561
Median Absolute Deviation (MAD)94
Skewness0.15613962
Sum11774561
Variance5519.7873
MonotonicityNot monotonic
2024-03-14T17:40:16.280557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1104 2350
23.5%
1101 1303
13.0%
1106 823
 
8.2%
1299 687
 
6.9%
1252 687
 
6.9%
1235 676
 
6.8%
1207 470
 
4.7%
1261 377
 
3.8%
1264 327
 
3.3%
1237 255
 
2.5%
Other values (55) 2045
20.4%
ValueCountFrequency (%)
1101 1303
13.0%
1103 15
 
0.1%
1104 2350
23.5%
1105 6
 
0.1%
1106 823
 
8.2%
1108 209
 
2.1%
1110 66
 
0.7%
1114 30
 
0.3%
1117 1
 
< 0.1%
1118 13
 
0.1%
ValueCountFrequency (%)
1299 687
6.9%
1280 3
 
< 0.1%
1279 1
 
< 0.1%
1277 2
 
< 0.1%
1275 1
 
< 0.1%
1273 1
 
< 0.1%
1271 2
 
< 0.1%
1269 4
 
< 0.1%
1267 12
 
0.1%
1266 6
 
0.1%

조림수종
Text

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T17:40:17.084745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.4891
Min length2

Characters and Unicode

Total characters34891
Distinct characters102
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

Unique9 ?
Unique (%)0.1%

Sample

1st row편백
2nd row편백
3rd row자작나무
4th row상수리나무
5th row황칠나무
ValueCountFrequency (%)
편백 2350
23.5%
소나무 1303
13.0%
낙엽송 823
 
8.2%
활엽수기타 687
 
6.9%
자작나무 687
 
6.9%
백합나무 676
 
6.8%
상수리나무 470
 
4.7%
황칠나무 377
 
3.8%
헛개나무 327
 
3.3%
벚나무(산벚 255
 
2.5%
Other values (55) 2045
20.4%
2024-03-14T17:40:18.299832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 5797
16.6%
무 5797
16.6%
백 3257
 
9.3%
편 2350
 
6.7%
엽 1533
 
4.4%
소 1318
 
3.8%
수 1303
 
3.7%
송 893
 
2.6%
낙 827
 
2.4%
기 745
 
2.1%
Other values (92) 11071
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34149
97.9%
Open Punctuation 371
 
1.1%
Close Punctuation 371
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 5797
17.0%
무 5797
17.0%
백 3257
 
9.5%
편 2350
 
6.9%
엽 1533
 
4.5%
소 1318
 
3.9%
수 1303
 
3.8%
송 893
 
2.6%
낙 827
 
2.4%
기 745
 
2.2%
Other values (90) 10329
30.2%
Open Punctuation
ValueCountFrequency (%)
( 371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 371
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34149
97.9%
Common 742
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 5797
17.0%
무 5797
17.0%
백 3257
 
9.5%
편 2350
 
6.9%
엽 1533
 
4.5%
소 1318
 
3.9%
수 1303
 
3.8%
송 893
 
2.6%
낙 827
 
2.4%
기 745
 
2.2%
Other values (90) 10329
30.2%
Common
ValueCountFrequency (%)
( 371
50.0%
) 371
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34149
97.9%
ASCII 742
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 5797
17.0%
무 5797
17.0%
백 3257
 
9.5%
편 2350
 
6.9%
엽 1533
 
4.5%
소 1318
 
3.9%
수 1303
 
3.8%
송 893
 
2.6%
낙 827
 
2.4%
기 745
 
2.2%
Other values (90) 10329
30.2%
ASCII
ValueCountFrequency (%)
( 371
50.0%
) 371
50.0%

묘령
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2-0
2780 
1-0
1945 
기타
1921 
01월 01일
1423 
02월 02일
1155 
Other values (4)
776 

Length

Max length7
Median length3
Mean length4.1495
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02월 02일
2nd row2-0
3rd row01월 01일
4th row1-0
5th row2-0

Common Values

ValueCountFrequency (%)
2-0 2780
27.8%
1-0 1945
19.4%
기타 1921
19.2%
01월 01일 1423
14.2%
02월 02일 1155
11.6%
01월 02일 461
 
4.6%
02월 03일 164
 
1.6%
02월 01일 109
 
1.1%
03월 01일 42
 
0.4%

Length

2024-03-14T17:40:18.532286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:18.743658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2-0 2780
20.8%
1-0 1945
14.6%
기타 1921
14.4%
01월 1884
14.1%
02일 1616
12.1%
01일 1574
11.8%
02월 1428
10.7%
03일 164
 
1.2%
03월 42
 
0.3%

조림면적
Real number (ℝ)

ZEROS 

Distinct333
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2739.7438
Minimum0
Maximum200000
Zeros8161
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:19.074137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile18210
Maximum200000
Range200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10144.755
Coefficient of variation (CV)3.7028116
Kurtosis77.189077
Mean2739.7438
Median Absolute Deviation (MAD)0
Skewness7.2183001
Sum27397438
Variance1.0291606 × 108
MonotonicityNot monotonic
2024-03-14T17:40:19.529951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8161
81.6%
10000 143
 
1.4%
20000 86
 
0.9%
5000 83
 
0.8%
3000 61
 
0.6%
15000 50
 
0.5%
4000 50
 
0.5%
2000 44
 
0.4%
30000 43
 
0.4%
1000 42
 
0.4%
Other values (323) 1237
 
12.4%
ValueCountFrequency (%)
0 8161
81.6%
24 1
 
< 0.1%
27 1
 
< 0.1%
36 1
 
< 0.1%
100 14
 
0.1%
150 1
 
< 0.1%
200 12
 
0.1%
270 1
 
< 0.1%
300 16
 
0.2%
323 1
 
< 0.1%
ValueCountFrequency (%)
200000 1
< 0.1%
170000 2
< 0.1%
150000 2
< 0.1%
147400 1
< 0.1%
140000 2
< 0.1%
127000 1
< 0.1%
123000 1
< 0.1%
122000 1
< 0.1%
120000 1
< 0.1%
115000 2
< 0.1%

본수
Real number (ℝ)

ZEROS 

Distinct1593
Distinct (%)15.9%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3316.7464
Minimum0
Maximum108900
Zeros233
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:20.149719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1269
median1500
Q34200
95-th percentile12000
Maximum108900
Range108900
Interquartile range (IQR)3931

Descriptive statistics

Standard deviation5316.8879
Coefficient of variation (CV)1.6030432
Kurtosis56.946293
Mean3316.7464
Median Absolute Deviation (MAD)1440
Skewness5.3138791
Sum33157514
Variance28269296
MonotonicityNot monotonic
2024-03-14T17:40:20.597957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000 507
 
5.1%
1500 303
 
3.0%
6000 292
 
2.9%
0 233
 
2.3%
300 157
 
1.6%
1200 155
 
1.6%
900 141
 
1.4%
600 136
 
1.4%
9000 128
 
1.3%
4500 128
 
1.3%
Other values (1583) 7817
78.2%
ValueCountFrequency (%)
0 233
2.3%
1 26
 
0.3%
2 31
 
0.3%
3 28
 
0.3%
4 38
 
0.4%
5 30
 
0.3%
6 18
 
0.2%
7 24
 
0.2%
8 22
 
0.2%
9 16
 
0.2%
ValueCountFrequency (%)
108900 1
 
< 0.1%
102900 1
 
< 0.1%
90000 1
 
< 0.1%
76600 1
 
< 0.1%
63700 1
 
< 0.1%
60000 3
< 0.1%
58560 1
 
< 0.1%
56782 1
 
< 0.1%
56400 1
 
< 0.1%
54520 1
 
< 0.1%

활착본수
Real number (ℝ)

ZEROS 

Distinct1754
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1755.4379
Minimum0
Maximum108900
Zeros4667
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T17:40:21.024870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q31800
95-th percentile8844.4
Maximum108900
Range108900
Interquartile range (IQR)1800

Descriptive statistics

Standard deviation4274.9567
Coefficient of variation (CV)2.4352651
Kurtosis114.21119
Mean1755.4379
Median Absolute Deviation (MAD)30
Skewness7.5471488
Sum17554379
Variance18275255
MonotonicityNot monotonic
2024-03-14T17:40:21.467078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4667
46.7%
3000 186
 
1.9%
1500 122
 
1.2%
6000 92
 
0.9%
4500 59
 
0.6%
600 54
 
0.5%
2400 54
 
0.5%
900 52
 
0.5%
9000 52
 
0.5%
300 49
 
0.5%
Other values (1744) 4613
46.1%
ValueCountFrequency (%)
0 4667
46.7%
1 7
 
0.1%
2 9
 
0.1%
3 16
 
0.2%
4 19
 
0.2%
5 10
 
0.1%
6 9
 
0.1%
7 22
 
0.2%
8 12
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
108900 1
< 0.1%
102900 1
< 0.1%
84600 1
< 0.1%
63700 1
< 0.1%
60000 2
< 0.1%
56400 1
< 0.1%
51000 1
< 0.1%
47400 1
< 0.1%
44550 1
< 0.1%
43200 1
< 0.1%

산림기능구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목재생산
3662 
수원함양
1635 
기타
1527 
생활환경보전
1288 
산림휴양
912 
Other values (2)
976 

Length

Max length6
Median length4
Mean length4.1474
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목재생산
2nd row산림휴양
3rd row산림휴양
4th row목재생산
5th row목재생산

Common Values

ValueCountFrequency (%)
목재생산 3662
36.6%
수원함양 1635
16.4%
기타 1527
15.3%
생활환경보전 1288
 
12.9%
산림휴양 912
 
9.1%
산림재해방지 765
 
7.6%
자연환경보전 211
 
2.1%

Length

2024-03-14T17:40:21.915412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:40:22.280476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목재생산 3662
36.6%
수원함양 1635
16.4%
기타 1527
15.3%
생활환경보전 1288
 
12.9%
산림휴양 912
 
9.1%
산림재해방지 765
 
7.6%
자연환경보전 211
 
2.1%

경제림단지구분
Text

Distinct248
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T17:40:23.474061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6749
Min length2

Characters and Unicode

Total characters36749
Distinct characters182
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

Unique17 ?
Unique (%)0.2%

Sample

1st row대상아님
2nd row대강송동
3rd row가평
4th row탄천월암
5th row녹진회동
ValueCountFrequency (%)
대상아님 6912
69.1%
팔봉산 73
 
0.7%
가평 61
 
0.6%
화평장리 55
 
0.5%
청일 54
 
0.5%
산서번암 50
 
0.5%
김천 49
 
0.5%
비봉청량 49
 
0.5%
백우산 45
 
0.4%
백두산 45
 
0.4%
Other values (238) 2607
 
26.1%
2024-03-14T17:40:25.069845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 7028
19.1%
아 7005
19.1%
상 6987
19.0%
님 6912
18.8%
산 1019
 
2.8%
천 322
 
0.9%
봉 257
 
0.7%
장 246
 
0.7%
백 222
 
0.6%
평 196
 
0.5%
Other values (172) 6555
17.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36699
99.9%
Connector Punctuation 44
 
0.1%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 7028
19.2%
아 7005
19.1%
상 6987
19.0%
님 6912
18.8%
산 1019
 
2.8%
천 322
 
0.9%
봉 257
 
0.7%
장 246
 
0.7%
백 222
 
0.6%
평 196
 
0.5%
Other values (170) 6505
17.7%
Connector Punctuation
ValueCountFrequency (%)
_ 44
100.0%
Decimal Number
ValueCountFrequency (%)
5 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36699
99.9%
Common 50
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 7028
19.2%
아 7005
19.1%
상 6987
19.0%
님 6912
18.8%
산 1019
 
2.8%
천 322
 
0.9%
봉 257
 
0.7%
장 246
 
0.7%
백 222
 
0.6%
평 196
 
0.5%
Other values (170) 6505
17.7%
Common
ValueCountFrequency (%)
_ 44
88.0%
5 6
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36699
99.9%
ASCII 50
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 7028
19.2%
아 7005
19.1%
상 6987
19.0%
님 6912
18.8%
산 1019
 
2.8%
천 322
 
0.9%
봉 257
 
0.7%
장 246
 
0.7%
백 222
 
0.6%
평 196
 
0.5%
Other values (170) 6505
17.7%
ASCII
ValueCountFrequency (%)
_ 44
88.0%
5 6
 
12.0%

대상지별구분
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
천연림벌채지(기타 수확벌채지)
2654 
인공림벌채지(기타 수확벌채지)
2293 
천연림벌채지(불량림 수종갱신지)
1175 
무립목지(미립목지)
885 
천연림벌채지(산불피해지)
458 
Other values (22)
2535 

Length

Max length18
Median length17
Mean length14.8558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인공림벌채지(불량림 수종갱신지)
2nd row인공림벌채지(기타 수확벌채지)
3rd row인공림벌채지(낙엽송 수확벌채지)
4th row천연림벌채지(기타 수확벌채지)
5th row천연림벌채지(불량림 수종갱신지)

Common Values

ValueCountFrequency (%)
천연림벌채지(기타 수확벌채지) 2654
26.5%
인공림벌채지(기타 수확벌채지) 2293
22.9%
천연림벌채지(불량림 수종갱신지) 1175
11.8%
무립목지(미립목지) 885
 
8.8%
천연림벌채지(산불피해지) 458
 
4.6%
천연림벌채지(병해충피해지) 389
 
3.9%
인공림벌채지(낙엽송 수확벌채지) 381
 
3.8%
인공림벌채지(리기다소나무 갱신지) 300
 
3.0%
인공림벌채지(불량림 수종갱신지) 264
 
2.6%
기타 230
 
2.3%
Other values (17) 971
 
9.7%

Length

2024-03-14T17:40:25.327974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수확벌채지 5423
31.4%
천연림벌채지(기타 2658
15.4%
인공림벌채지(기타 2299
13.3%
수종갱신지 1439
 
8.3%
천연림벌채지(불량림 1175
 
6.8%
무립목지(미립목지 885
 
5.1%
천연림벌채지(산불피해지 458
 
2.7%
갱신지 408
 
2.4%
천연림벌채지(병해충피해지 389
 
2.3%
인공림벌채지(낙엽송 381
 
2.2%
Other values (18) 1755
 
10.2%

Sample

사유림산림사업번호사업년도시작일종료일사업명발주구분기관명실행주체구분업체명지역코드시도코드시군구코드읍면동코드시군구읍면동코드(PNU)산구분코드산구분본번부번지목코드지목명지적산림자원조성구분코드산림자원조성구분사업구분조림수종코드조림수종묘령조림면적본수활착본수산림기능구분경제림단지구분대상지별구분
652353101600000000000020152015-03-182015-05-13조림사업(큰나무조림)시군구경상남도 진주시위탁·대행(산림사업법인)(주) 정원48170420224817042048170400000000000002일반11305임야1300011조림/갱신큰나무공익조림1104편백02월 02일015001500목재생산대상아님인공림벌채지(불량림 수종갱신지)
2240247001600000000000020172017-03-202017-04-162017년 봄철 경제림 조림사업(대강지구)시군구전라북도 남원시기타(유)남강산림개발45190360254519036045190400000000000002일반11605임야1953711조림/갱신목재생산조림1104편백2-0057005700산림휴양대강송동인공림벌채지(기타 수확벌채지)
1843841600800000000000020172017-03-242017-04-272017년 춘기 조림사업(제1권역)시군구경기도 가평군위탁·대행(산림사업법인)(주)승산41820250324182025041820300000000000002일반3805임야892611조림/갱신목재생산조림1252자작나무01월 01일017500산림휴양가평인공림벌채지(낙엽송 수확벌채지)
2110345401800000000000020172017-10-262017-11-3017년 추기조림사업- 경제수시군구충청남도 논산시산주직접실행(기타)서승항 외 8인44230360304423036044230400000000000002일반5105임야400011조림/갱신목재생산조림1207상수리나무1-006000목재생산탄천월암천연림벌채지(기타 수확벌채지)
526650000800000000000020152015-03-192015-06-162015년 경제수 조림사업(진도지구)시군구전라남도 진도군도급·계약(산림사업법인)(유)대한산림개발46900250214690025046900300000000000002일반11305임야7790011조림/갱신바이오순환림조성1261황칠나무2-02000600600목재생산녹진회동천연림벌채지(불량림 수종갱신지)
1259847600800000000000020162016-03-072016-04-292016년 봄철 경제림 조성사업(강진덕치지구)시군구전라북도 임실군도급·계약(산림조합)임실군산림조합45750400284575040045750400000000000002일반8855임야8700011조림/갱신목재생산조림1235백합나무1-0020002000목재생산대상아님천연림벌채지(기타 수확벌채지)
1552650801900000000000020162016-03-012016-05-15유휴토지조림시군구경상북도 구미시산주직접실행(기타)기타47190330274719033047190300000000000001산13605임야146811조림/갱신유휴토지조림1299활엽수기타기타05050목재생산대상아님무립목지(개간지)
246647102000000000000020152015-09-302015-12-01재해방지 조림사업(추기)시군구전라북도 김제시도급·계약(산림조합)김제산림조합45210420264521042045210400000000000002일반10335임야1570011조림/갱신목재생산조림1104편백02월 02일016801680산림휴양대상아님인공림벌채지(기타 수확벌채지)
36339200800000000000020152015-04-022015-04-212015년 조림(경제수)조림시군구경기도 동두천시도급·계약(산림조합)양주지역산림조합41250108004125010841250100000000000002일반18505임야5377911조림/갱신목재생산조림1108잣나무02월 02일030003000생활환경보전대상아님천연림벌채지(기타 수확벌채지)
1664053702100000000000020162016-02-292016-04-252016년 소나무재선충병 방제 및 봄철 조림사업시군구경상남도 거제시도급·계약(산림조합)거제시 산림조합48310111004831011148310100000000000002일반3805임야4095911조림/갱신산림재해방지조림1104편백02월 02일046500목재생산대상아님천연림벌채지(병해충피해지)
사유림산림사업번호사업년도시작일종료일사업명발주구분기관명실행주체구분업체명지역코드시도코드시군구코드읍면동코드시군구읍면동코드(PNU)산구분코드산구분본번부번지목코드지목명지적산림자원조성구분코드산림자원조성구분사업구분조림수종코드조림수종묘령조림면적본수활착본수산림기능구분경제림단지구분대상지별구분
524950000800000000000020152015-03-192015-06-162015년 경제수 조림사업(의신지구)시군구전라남도 진도군도급·계약(산림사업법인)(주)성언산림46900330334690033046900300000000000002일반9105임야1830011조림/갱신바이오순환림조성1210가시나무2-01000030003000목재생산첨철산천연림벌채지(불량림 수종갱신지)
3075642402000000000000020202020-03-152020-04-202020년 경제림조성사업(산주실행분)시군구강원도 삼척시산주직접실행(기타)산주직접실행42230320344223032042230300000000000002일반10525임야2069811조림/갱신목재생산조림1106낙엽송2-0043500수원함양하장천연림벌채지(기타 수확벌채지)
661953401500000000000020152015-03-132015-05-012015년 지역특화조림사업시군구경상남도 사천시위탁·대행(산림사업법인)(주)산맥48240320264824032048240300000000000002일반8505임야4385411조림/갱신목재생산조림1104편백01월 01일066006600수원함양대상아님천연림벌채지(불량림 수종갱신지)
212145401800000000000020152015-04-012015-05-302015년 경제수 조림사업시군구충청남도 논산시산주직접실행(기타)기타44230360364423036044230400000000000002일반605임야24800011조림/갱신목재생산조림1235백합나무1-0030001920산림휴양탄천월암기타
227046803100000000000020152015-04-032015-04-302015년 경제수 조림시군구전라북도 익산시도급·계약(기타)익산산림조합45140390234514039045140400000000000002일반16815임야3586111조림/갱신목재생산조림1235백합나무1-0020000자연환경보전대상아님인공림벌채지(리기다소나무 갱신지)
16937301500000000000020152015-02-112015-05-112015년 조림사업시군구울산광역시 울주군도급·계약(산림조합)울산광역시산림조합31710253293171025331710300000000000001산120945임야130011조림/갱신산림재해방지조림1235백합나무01월 01일0325276생활환경보전대상아님천연림벌채지(산불피해지)
2380448401700000000000020172017-03-272017-05-272017년 조림사업시군구전라남도 광양시도급·계약(산림조합)광양시산림조합46230320264623032046230300000000000002일반26635임야3090011조림/갱신산림재해방지조림1104편백2-0900090005400목재생산광양천연림벌채지(병해충피해지)
115642600900000000000020152015-03-032015-11-202015년도 경제림조성사업(봄,가을)시군구강원도 횡성군도급·계약(기타)기타42730360234273036042730400000000000002일반7405임야3500011조림/갱신특용자원조림1252자작나무1-0070007000산림재해방지대상아님천연림벌채지(기타 수확벌채지)
2449749000800000000000020172017-03-202017-04-28경제수 일반조림-동면지구시군구전라남도 화순군도급·계약(산림사업법인)(주)남도산림개발46790390234679039046790400000000000002일반2825임야1904111조림/갱신목재생산조림1104편백01월 01일1800054000목재생산백아산인공림벌채지(리기다소나무 갱신지)
2355748002500000000000020172017-01-022018-12-312017년 조림사업시군구전라남도 목포시기타기타46110102004611010246110100000000000001산14244128잡종지335313보완조림섬지역산림가꾸기1237벚나무(산벚)2-0050생활환경보전대상아님인공림벌채지(불량림 수종갱신지)

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사유림산림사업번호사업년도시작일종료일사업명발주구분기관명실행주체구분업체명지역코드시도코드시군구코드읍면동코드시군구읍면동코드(PNU)산구분코드산구분본번부번지목코드지목명지적산림자원조성구분코드산림자원조성구분사업구분조림수종코드조림수종묘령조림면적본수활착본수산림기능구분경제림단지구분대상지별구분# duplicates
049400900000000000020152015-03-242015-04-242015년 큰나무조림사업시군구전라남도 영암군도급·계약(산림조합)영암군산림조합46830250344683025046830300000000000002일반7605임야6644611조림/갱신큰나무공익조림1104편백기타000목재생산금정천연림벌채지(기타 수확벌채지)2
152400700000000000020152015-04-212015-05-072015년도 큰나무 공익조림시군구경상북도 봉화군기타기타47920380234792038047920400000000000002일반10205임야12607411조림/갱신큰나무공익조림1299활엽수기타기타07350목재생산비봉청량천연림벌채지(기타 수확벌채지)2