Overview

Dataset statistics

Number of variables6
Number of observations1509
Missing cells200
Missing cells (%)2.2%
Duplicate rows227
Duplicate rows (%)15.0%
Total size in memory70.9 KiB
Average record size in memory48.1 B

Variable types

Text3
Categorical3

Dataset

Description산림청 및 지자체가 보유한 임업기계장비에 대한 관리정보임(산림사업법인관리시스템에 등록된 임업기계장비 관리정보)
Author산림청
URLhttps://www.data.go.kr/data/15071588/fileData.do

Alerts

Dataset has 227 (15.0%) duplicate rowsDuplicates
소분류 is highly overall correlated with 대분류 and 1 other fieldsHigh correlation
중분류 is highly overall correlated with 대분류 and 1 other fieldsHigh correlation
대분류 is highly overall correlated with 중분류 and 1 other fieldsHigh correlation
장비명 has 47 (3.1%) missing valuesMissing
장비제조사명 has 153 (10.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:42:13.772322
Analysis finished2023-12-12 08:42:14.888782
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

Distinct94
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
2023-12-12T17:42:15.124080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length15.542081
Min length3

Characters and Unicode

Total characters23453
Distinct characters99
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

Unique17 ?
Unique (%)1.1%

Sample

1st row전라남도 진도군
2nd row전라남도 무안군
3rd row전라남도 무안군
4th row산림조합중앙회
5th row전라북도 장수군
ValueCountFrequency (%)
산림청 1024
26.6%
서부지방산림청 492
 
12.8%
동부지방산림청 188
 
4.9%
전라남도 124
 
3.2%
남부지방산림청 123
 
3.2%
북부지방산림청 117
 
3.0%
중부지방산림청 98
 
2.5%
무주국유림관리소 98
 
2.5%
산림조합중앙회 88
 
2.3%
충청남도 76
 
2.0%
Other values (97) 1416
36.8%
2023-12-12T17:42:15.551253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
림 3047
 
13.0%
2335
 
10.0%
산 2213
 
9.4%
청 2139
 
9.1%
지 1060
 
4.5%
부 1047
 
4.5%
방 1018
 
4.3%
소 919
 
3.9%
리 909
 
3.9%
관 909
 
3.9%
Other values (89) 7857
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21118
90.0%
Space Separator 2335
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
림 3047
14.4%
산 2213
 
10.5%
청 2139
 
10.1%
지 1060
 
5.0%
부 1047
 
5.0%
방 1018
 
4.8%
소 919
 
4.4%
리 909
 
4.3%
관 909
 
4.3%
국 887
 
4.2%
Other values (88) 6970
33.0%
Space Separator
ValueCountFrequency (%)
2335
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21118
90.0%
Common 2335
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
림 3047
14.4%
산 2213
 
10.5%
청 2139
 
10.1%
지 1060
 
5.0%
부 1047
 
5.0%
방 1018
 
4.8%
소 919
 
4.4%
리 909
 
4.3%
관 909
 
4.3%
국 887
 
4.2%
Other values (88) 6970
33.0%
Common
ValueCountFrequency (%)
2335
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21118
90.0%
ASCII 2335
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
림 3047
14.4%
산 2213
 
10.5%
청 2139
 
10.1%
지 1060
 
5.0%
부 1047
 
5.0%
방 1018
 
4.8%
소 919
 
4.4%
리 909
 
4.3%
관 909
 
4.3%
국 887
 
4.2%
Other values (88) 6970
33.0%
ASCII
ValueCountFrequency (%)
2335
100.0%

대분류
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
임목생산장비
888 
조림·육림장비
203 
산림보호장비
121 
임도장비
102 
목재가공장비
89 
Other values (2)
106 

Length

Max length7
Median length6
Mean length5.8588469
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임목생산장비 888
58.8%
조림·육림장비 203
 
13.5%
산림보호장비 121
 
8.0%
임도장비 102
 
6.8%
목재가공장비 89
 
5.9%
양묘장비 53
 
3.5%
행정장비 53
 
3.5%

Length

2023-12-12T17:42:15.708858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:42:15.881911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임목생산장비 888
58.8%
조림·육림장비 203
 
13.5%
산림보호장비 121
 
8.0%
임도장비 102
 
6.8%
목재가공장비 89
 
5.9%
양묘장비 53
 
3.5%
행정장비 53
 
3.5%

중분류
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
기계톱
238 
예불기
167 
윈치류
160 
굴삭기
134 
기타
120 
Other values (39)
690 

Length

Max length10
Median length3
Mean length3.7673956
Min length2

Unique

Unique6 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
기계톱 238
15.8%
예불기 167
11.1%
윈치류 160
10.6%
굴삭기 134
8.9%
기타 120
8.0%
굴삭기집재기 105
 
7.0%
트랙터집재기 101
 
6.7%
트렉터 94
 
6.2%
목재파쇄기 49
 
3.2%
동력펌프 46
 
3.0%
Other values (34) 295
19.5%

Length

2023-12-12T17:42:16.046850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계톱 238
15.7%
예불기 167
11.0%
윈치류 160
10.5%
굴삭기 134
8.8%
기타 120
 
7.9%
굴삭기집재기 105
 
6.9%
트랙터집재기 101
 
6.6%
트렉터 94
 
6.2%
목재파쇄기 49
 
3.2%
동력펌프 46
 
3.0%
Other values (35) 305
20.1%

소분류
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
<NA>
913 
0.3㎥이하
 
82
100마력 미만
 
70
소형윈치(아키아 등)
 
70
기타
 
70
Other values (20)
304 

Length

Max length15
Median length4
Mean length5.1888668
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 913
60.5%
0.3㎥이하 82
 
5.4%
100마력 미만 70
 
4.6%
소형윈치(아키아 등) 70
 
4.6%
기타 70
 
4.6%
소형케이블윈치(2드럼) 51
 
3.4%
우드그랩 50
 
3.3%
스마트 38
 
2.5%
0.4㎥~0.7㎥ 33
 
2.2%
스윙야더 19
 
1.3%
Other values (15) 113
 
7.5%

Length

2023-12-12T17:42:16.208644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 913
53.7%
100마력 85
 
5.0%
0.3㎥이하 82
 
4.8%
미만 70
 
4.1%
소형윈치(아키아 70
 
4.1%
등 70
 
4.1%
기타 70
 
4.1%
소형케이블윈치(2드럼 51
 
3.0%
우드그랩 50
 
2.9%
스마트 38
 
2.2%
Other values (21) 201
 
11.8%

장비명
Text

MISSING 

Distinct271
Distinct (%)18.5%
Missing47
Missing (%)3.1%
Memory size11.9 KiB
2023-12-12T17:42:16.535086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length9.9008208
Min length2

Characters and Unicode

Total characters14475
Distinct characters260
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)10.5%

Sample

1st row유압도끼
2nd row원목제재기
3rd row목재가공장비 > 기타
4th row장작생산기계
5th row장작제조기
ValueCountFrequency (%)
833
25.3%
임목생산장비 411
 
12.5%
기계톱 229
 
6.9%
조림·육림장비 152
 
4.6%
예불기 140
 
4.2%
굴삭기 101
 
3.1%
윈치류 95
 
2.9%
트랙터집재기 56
 
1.7%
기타 53
 
1.6%
트렉터 51
 
1.5%
Other values (261) 1174
35.6%
2023-12-12T17:42:17.041912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1833
 
12.7%
기 900
 
6.2%
> 833
 
5.8%
장 659
 
4.6%
비 657
 
4.5%
목 467
 
3.2%
산 447
 
3.1%
임 427
 
2.9%
생 412
 
2.8%
림 336
 
2.3%
Other values (250) 7504
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10531
72.8%
Space Separator 1833
 
12.7%
Math Symbol 849
 
5.9%
Decimal Number 516
 
3.6%
Open Punctuation 194
 
1.3%
Close Punctuation 192
 
1.3%
Other Punctuation 180
 
1.2%
Uppercase Letter 131
 
0.9%
Dash Punctuation 24
 
0.2%
Lowercase Letter 20
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 900
 
8.5%
장 659
 
6.3%
비 657
 
6.2%
목 467
 
4.4%
산 447
 
4.2%
임 427
 
4.1%
생 412
 
3.9%
림 336
 
3.2%
톱 254
 
2.4%
계 245
 
2.3%
Other values (201) 5727
54.4%
Uppercase Letter
ValueCountFrequency (%)
M 20
15.3%
H 16
12.2%
S 16
12.2%
A 12
9.2%
C 10
7.6%
T 9
6.9%
B 7
 
5.3%
P 7
 
5.3%
D 7
 
5.3%
L 6
 
4.6%
Other values (9) 21
16.0%
Decimal Number
ValueCountFrequency (%)
0 172
33.3%
2 105
20.3%
1 78
15.1%
5 50
 
9.7%
3 28
 
5.4%
4 26
 
5.0%
6 20
 
3.9%
9 18
 
3.5%
8 10
 
1.9%
7 9
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
m 5
25.0%
w 5
25.0%
a 3
15.0%
h 2
 
10.0%
c 2
 
10.0%
t 1
 
5.0%
r 1
 
5.0%
e 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
· 152
84.4%
/ 14
 
7.8%
. 8
 
4.4%
, 6
 
3.3%
Math Symbol
ValueCountFrequency (%)
> 833
98.1%
~ 14
 
1.6%
+ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
1833
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10531
72.8%
Common 3793
 
26.2%
Latin 151
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 900
 
8.5%
장 659
 
6.3%
비 657
 
6.2%
목 467
 
4.4%
산 447
 
4.2%
임 427
 
4.1%
생 412
 
3.9%
림 336
 
3.2%
톱 254
 
2.4%
계 245
 
2.3%
Other values (201) 5727
54.4%
Latin
ValueCountFrequency (%)
M 20
13.2%
H 16
 
10.6%
S 16
 
10.6%
A 12
 
7.9%
C 10
 
6.6%
T 9
 
6.0%
B 7
 
4.6%
P 7
 
4.6%
D 7
 
4.6%
L 6
 
4.0%
Other values (17) 41
27.2%
Common
ValueCountFrequency (%)
1833
48.3%
> 833
22.0%
( 194
 
5.1%
) 192
 
5.1%
0 172
 
4.5%
· 152
 
4.0%
2 105
 
2.8%
1 78
 
2.1%
5 50
 
1.3%
3 28
 
0.7%
Other values (12) 156
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10531
72.8%
ASCII 3787
 
26.2%
None 152
 
1.1%
CJK Compat 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1833
48.4%
> 833
22.0%
( 194
 
5.1%
) 192
 
5.1%
0 172
 
4.5%
2 105
 
2.8%
1 78
 
2.1%
5 50
 
1.3%
3 28
 
0.7%
4 26
 
0.7%
Other values (37) 276
 
7.3%
Hangul
ValueCountFrequency (%)
기 900
 
8.5%
장 659
 
6.3%
비 657
 
6.2%
목 467
 
4.4%
산 447
 
4.2%
임 427
 
4.1%
생 412
 
3.9%
림 336
 
3.2%
톱 254
 
2.4%
계 245
 
2.3%
Other values (201) 5727
54.4%
None
ValueCountFrequency (%)
· 152
100.0%
CJK Compat
ValueCountFrequency (%)
㎥ 5
100.0%

장비제조사명
Text

MISSING 

Distinct283
Distinct (%)20.9%
Missing153
Missing (%)10.1%
Memory size11.9 KiB
2023-12-12T17:42:17.369817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length6.2205015
Min length2

Characters and Unicode

Total characters8435
Distinct characters267
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)10.5%

Sample

1st row(주)풍림
2nd row(주)유림기계
3rd row(주)유림기계
4th row슬로베니아
5th rowTAJFUN
ValueCountFrequency (%)
mitsubishi 65
 
4.7%
stihl 58
 
4.2%
현대중공업(주 53
 
3.8%
볼보그룹코리아(주 46
 
3.3%
두산인프라코어(주 46
 
3.3%
유비통상 45
 
3.2%
zenoah 43
 
3.1%
제노아 42
 
3.0%
신풍엔지니어링 35
 
2.5%
허스크바나 34
 
2.5%
Other values (269) 920
66.3%
2023-12-12T17:42:17.877281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 383
 
4.5%
) 383
 
4.5%
주 367
 
4.4%
i 241
 
2.9%
대 229
 
2.7%
업 193
 
2.3%
공 185
 
2.2%
a 169
 
2.0%
h 168
 
2.0%
동 159
 
1.9%
Other values (257) 5958
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5360
63.5%
Lowercase Letter 1436
 
17.0%
Uppercase Letter 807
 
9.6%
Open Punctuation 383
 
4.5%
Close Punctuation 383
 
4.5%
Space Separator 31
 
0.4%
Decimal Number 20
 
0.2%
Other Punctuation 13
 
0.2%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 367
 
6.8%
대 229
 
4.3%
업 193
 
3.6%
공 185
 
3.5%
동 159
 
3.0%
기 155
 
2.9%
계 129
 
2.4%
아 125
 
2.3%
현 117
 
2.2%
유 115
 
2.1%
Other values (191) 3586
66.9%
Lowercase Letter
ValueCountFrequency (%)
i 241
16.8%
a 169
11.8%
h 168
11.7%
s 152
10.6%
t 97
6.8%
n 97
6.8%
u 88
 
6.1%
o 75
 
5.2%
e 64
 
4.5%
b 61
 
4.2%
Other values (16) 224
15.6%
Uppercase Letter
ValueCountFrequency (%)
S 130
16.1%
I 117
14.5%
M 102
12.6%
H 96
11.9%
T 66
8.2%
L 42
 
5.2%
Z 39
 
4.8%
U 26
 
3.2%
B 25
 
3.1%
E 23
 
2.9%
Other values (16) 141
17.5%
Decimal Number
ValueCountFrequency (%)
5 6
30.0%
2 5
25.0%
4 3
15.0%
6 2
 
10.0%
3 2
 
10.0%
0 2
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 6
46.2%
. 4
30.8%
/ 3
23.1%
Open Punctuation
ValueCountFrequency (%)
( 383
100.0%
Close Punctuation
ValueCountFrequency (%)
) 383
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5361
63.6%
Latin 2243
26.6%
Common 831
 
9.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 367
 
6.8%
대 229
 
4.3%
업 193
 
3.6%
공 185
 
3.5%
동 159
 
3.0%
기 155
 
2.9%
계 129
 
2.4%
아 125
 
2.3%
현 117
 
2.2%
유 115
 
2.1%
Other values (192) 3587
66.9%
Latin
ValueCountFrequency (%)
i 241
 
10.7%
a 169
 
7.5%
h 168
 
7.5%
s 152
 
6.8%
S 130
 
5.8%
I 117
 
5.2%
M 102
 
4.5%
t 97
 
4.3%
n 97
 
4.3%
H 96
 
4.3%
Other values (42) 874
39.0%
Common
ValueCountFrequency (%)
( 383
46.1%
) 383
46.1%
31
 
3.7%
, 6
 
0.7%
5 6
 
0.7%
2 5
 
0.6%
. 4
 
0.5%
/ 3
 
0.4%
4 3
 
0.4%
6 2
 
0.2%
Other values (3) 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5360
63.5%
ASCII 3074
36.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 383
 
12.5%
) 383
 
12.5%
i 241
 
7.8%
a 169
 
5.5%
h 168
 
5.5%
s 152
 
4.9%
S 130
 
4.2%
I 117
 
3.8%
M 102
 
3.3%
t 97
 
3.2%
Other values (55) 1132
36.8%
Hangul
ValueCountFrequency (%)
주 367
 
6.8%
대 229
 
4.3%
업 193
 
3.6%
공 185
 
3.5%
동 159
 
3.0%
기 155
 
2.9%
계 129
 
2.4%
아 125
 
2.3%
현 117
 
2.2%
유 115
 
2.1%
Other values (191) 3586
66.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Correlations

2023-12-12T17:42:18.021182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명대분류중분류소분류
기관명1.0000.7570.8000.773
대분류0.7571.0000.9840.970
중분류0.8000.9841.0000.992
소분류0.7730.9700.9921.000
2023-12-12T17:42:18.145614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류소분류중분류
대분류1.0000.8050.881
소분류0.8051.0000.950
중분류0.8810.9501.000
2023-12-12T17:42:18.250357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류소분류
대분류1.0000.8810.805
중분류0.8811.0000.950
소분류0.8050.9501.000

Missing values

2023-12-12T17:42:14.552133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:42:14.673401image/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.
2023-12-12T17:42:14.799927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기관명대분류중분류소분류장비명장비제조사명
0전라남도 진도군목재가공장비기타<NA>유압도끼(주)풍림
1전라남도 무안군목재가공장비기타<NA>원목제재기(주)유림기계
2전라남도 무안군목재가공장비기타<NA>목재가공장비 > 기타(주)유림기계
3산림조합중앙회목재가공장비기타<NA>장작생산기계슬로베니아
4전라북도 장수군목재가공장비기타<NA>장작제조기TAJFUN
5전라남도 장흥군목재가공장비기타<NA>유압도끼(주)풍림이엔지
6전라남도 곡성군목재가공장비기타<NA>크레인두산인프라코어(주)
7전라남도 장성군목재가공장비기타<NA>유압도끼(주)풍림이엔지
8전라남도 장성군목재가공장비기타<NA>롤박스(주)화인통상
9강원도 화천군목재가공장비목재파쇄기대형(20~30cm)목재파쇄기풍림산업
기관명대분류중분류소분류장비명장비제조사명
1499산림청 서부지방산림청 함양국유림관리소행정장비승합차<NA>행정장비 > 승합차현대
1500산림청 서부지방산림청 무주국유림관리소행정장비승합차<NA>대형승용기아자동차
1501충청남도 아산시행정장비승합차<NA>행정장비 > 승합차기아자동차(주)
1502산림청 서부지방산림청 함양국유림관리소행정장비승합차<NA>행정장비 > 승합차현대
1503산림청 서부지방산림청 함양국유림관리소행정장비승합차<NA>행정장비 > 승합차기아
1504산림청 서부지방산림청 무주국유림관리소행정장비승합차<NA>대형승용현대자동차
1505산림청 서부지방산림청 무주국유림관리소행정장비승합차<NA>대형승용현대자동차
1506산림청 서부지방산림청행정장비승합차<NA>행정장비 > 승합차현대자동차
1507산림청 서부지방산림청행정장비승합차<NA>행정장비 > 승합차현대자동차
1508산림청 동부지방산림청 양양국유림관리소행정장비승합차<NA><NA><NA>

Duplicate rows

Most frequently occurring

기관명대분류중분류소분류장비명장비제조사명# duplicates
190산림청 중부지방산림청 충주국유림관리소조림·육림장비예불기<NA><NA><NA>20
115산림청 서부지방산림청 무주국유림관리소조림·육림장비예불기<NA>예불기Mitsubishi17
145산림청 서부지방산림청 영암국유림관리소조림·육림장비예불기<NA>조림·육림장비 > 예불기제노아16
56산림청 동부지방산림청 양양국유림관리소산림보호장비천공기<NA>천공기<NA>15
204전라남도 장성군조림·육림장비예불기<NA>조림·육림장비 > 예불기Mitsubishi15
112산림청 서부지방산림청 무주국유림관리소임목생산장비기계톱<NA>기계톱STIHL13
195전라남도 강진군임목생산장비기계톱<NA>기계톱Zenoah13
116산림청 서부지방산림청 무주국유림관리소조림·육림장비예불기<NA>조림·육림장비 > 예불기<NA>11
101산림청 서부지방산림청조림·육림장비예불기<NA>조림·육림장비 > 예불기Mitsubishi9
201전라남도 장성군임목생산장비기계톱<NA>임목생산장비 > 기계톱shindaiwa9