Overview

Dataset statistics

Number of variables6
Number of observations204
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory50.6 B

Variable types

Numeric2
Text3
DateTime1

Dataset

Description부산광역시 기장군에서 운영 중 인 농기계임대사업 농기계 현황(보유 농기계명칭, 구입년도, 규격, 작업폭 등)을 게시합니다.
Author부산광역시 기장군
URLhttps://www.data.go.kr/data/15052585/fileData.do

Alerts

번호 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:05:38.986310
Analysis finished2023-12-13 00:05:39.767394
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.5
Minimum1
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T09:05:39.822587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q151.75
median102.5
Q3153.25
95-th percentile193.85
Maximum204
Range203
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation59.033889
Coefficient of variation (CV)0.57594038
Kurtosis-1.2
Mean102.5
Median Absolute Deviation (MAD)51
Skewness0
Sum20910
Variance3485
MonotonicityStrictly increasing
2023-12-13T09:05:39.931054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
142 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%

관리번호
Text

Distinct168
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T09:05:40.119059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length11.960784
Min length6

Characters and Unicode

Total characters2440
Distinct characters123
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

Unique148 ?
Unique (%)72.5%

Sample

1st row농용트랙터-01
2nd row농용트랙터-02
3rd row농용트랙터-03
4th row농용트랙터-04
5th row농용트랙터-05
ValueCountFrequency (%)
농용트랙터 77
24.7%
보행관리기 15
 
4.8%
로타베이터[로터리]-01 7
 
2.2%
보행형동력경운기 7
 
2.2%
로타베이터[로터리]-02 7
 
2.2%
승용관리기 4
 
1.3%
로타베이터[로터리]-03 4
 
1.3%
원판쟁기-02 3
 
1.0%
땅속작물수확기-01 3
 
1.0%
원판쟁기-01 3
 
1.0%
Other values (156) 182
58.3%
2023-12-13T09:05:40.420552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 204
 
8.4%
0 190
 
7.8%
기 186
 
7.6%
터 132
 
5.4%
108
 
4.4%
농 104
 
4.3%
용 103
 
4.2%
1 87
 
3.6%
트 86
 
3.5%
랙 86
 
3.5%
Other values (113) 1154
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1672
68.5%
Decimal Number 408
 
16.7%
Dash Punctuation 204
 
8.4%
Space Separator 108
 
4.4%
Close Punctuation 24
 
1.0%
Open Punctuation 24
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 186
 
11.1%
터 132
 
7.9%
농 104
 
6.2%
용 103
 
6.2%
트 86
 
5.1%
랙 86
 
5.1%
리 65
 
3.9%
로 55
 
3.3%
동 39
 
2.3%
행 39
 
2.3%
Other values (97) 777
46.5%
Decimal Number
ValueCountFrequency (%)
0 190
46.6%
1 87
21.3%
2 51
 
12.5%
3 28
 
6.9%
4 15
 
3.7%
5 12
 
2.9%
6 7
 
1.7%
9 6
 
1.5%
7 6
 
1.5%
8 6
 
1.5%
Close Punctuation
ValueCountFrequency (%)
] 23
95.8%
) 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
[ 23
95.8%
( 1
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Space Separator
ValueCountFrequency (%)
108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1672
68.5%
Common 768
31.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 186
 
11.1%
터 132
 
7.9%
농 104
 
6.2%
용 103
 
6.2%
트 86
 
5.1%
랙 86
 
5.1%
리 65
 
3.9%
로 55
 
3.3%
동 39
 
2.3%
행 39
 
2.3%
Other values (97) 777
46.5%
Common
ValueCountFrequency (%)
- 204
26.6%
0 190
24.7%
108
14.1%
1 87
11.3%
2 51
 
6.6%
3 28
 
3.6%
] 23
 
3.0%
[ 23
 
3.0%
4 15
 
2.0%
5 12
 
1.6%
Other values (6) 27
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1672
68.5%
ASCII 768
31.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 204
26.6%
0 190
24.7%
108
14.1%
1 87
11.3%
2 51
 
6.6%
3 28
 
3.6%
] 23
 
3.0%
[ 23
 
3.0%
4 15
 
2.0%
5 12
 
1.6%
Other values (6) 27
 
3.5%
Hangul
ValueCountFrequency (%)
기 186
 
11.1%
터 132
 
7.9%
농 104
 
6.2%
용 103
 
6.2%
트 86
 
5.1%
랙 86
 
5.1%
리 65
 
3.9%
로 55
 
3.3%
동 39
 
2.3%
행 39
 
2.3%
Other values (97) 777
46.5%

합계
Real number (ℝ)

Distinct90
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5573700.9
Minimum98000
Maximum1.035 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T09:05:40.538406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum98000
5-th percentile122500
Q1902750
median2100000
Q33911102.5
95-th percentile25130976
Maximum1.035 × 108
Range1.03402 × 108
Interquartile range (IQR)3008352.5

Descriptive statistics

Standard deviation11879479
Coefficient of variation (CV)2.1313449
Kurtosis37.486646
Mean5573700.9
Median Absolute Deviation (MAD)1472500
Skewness5.4647128
Sum1.137035 × 109
Variance1.4112202 × 1014
MonotonicityNot monotonic
2023-12-13T09:05:40.690987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2060000 13
 
6.4%
98000 10
 
4.9%
660000 10
 
4.9%
320000 10
 
4.9%
3300000 8
 
3.9%
182000 5
 
2.5%
308000 5
 
2.5%
1860000 5
 
2.5%
4060000 5
 
2.5%
410000 4
 
2.0%
Other values (80) 129
63.2%
ValueCountFrequency (%)
98000 10
4.9%
112000 1
 
0.5%
182000 5
2.5%
308000 5
2.5%
320000 10
4.9%
410000 4
 
2.0%
480000 3
 
1.5%
580000 1
 
0.5%
645000 1
 
0.5%
660000 10
4.9%
ValueCountFrequency (%)
103500000 1
 
0.5%
93739470 1
 
0.5%
43077000 1
 
0.5%
41181180 1
 
0.5%
37552545 1
 
0.5%
34000000 1
 
0.5%
27940000 1
 
0.5%
26356000 3
1.5%
25130976 2
1.0%
21202000 1
 
0.5%

구입년월일
Date

Distinct27
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1999-01-01 00:00:00
Maximum2014-08-27 00:00:00
2023-12-13T09:05:40.796571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:05:40.897436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

형식명
Text

Distinct97
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T09:05:41.159740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length6.872549
Min length4

Characters and Unicode

Total characters1402
Distinct characters76
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)24.5%

Sample

1st rowAF455
2nd rowAF325
3rd rowAF325
4th row대동6430
5th rowNF455-0
ValueCountFrequency (%)
amc-900 10
 
4.7%
hg20a 10
 
4.7%
dr-30 10
 
4.7%
hg10a 10
 
4.7%
am180 5
 
2.3%
uds-6533 5
 
2.3%
td45-f2 5
 
2.3%
2.2ps 5
 
2.3%
az-350ch 5
 
2.3%
bh6030 4
 
1.9%
Other values (92) 145
67.8%
2023-12-13T09:05:41.553621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 194
 
13.8%
- 107
 
7.6%
1 88
 
6.3%
5 72
 
5.1%
S 64
 
4.6%
3 62
 
4.4%
2 60
 
4.3%
D 59
 
4.2%
A 58
 
4.1%
H 51
 
3.6%
Other values (66) 587
41.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 604
43.1%
Uppercase Letter 585
41.7%
Dash Punctuation 107
 
7.6%
Lowercase Letter 37
 
2.6%
Other Letter 37
 
2.6%
Other Punctuation 16
 
1.1%
Space Separator 10
 
0.7%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 64
 
10.9%
D 59
 
10.1%
A 58
 
9.9%
H 51
 
8.7%
Y 40
 
6.8%
R 35
 
6.0%
C 30
 
5.1%
T 29
 
5.0%
J 27
 
4.6%
G 26
 
4.4%
Other values (16) 166
28.4%
Other Letter
ValueCountFrequency (%)
조 4
 
10.8%
파 4
 
10.8%
형 3
 
8.1%
기 2
 
5.4%
비 2
 
5.4%
시 2
 
5.4%
측 2
 
5.4%
산 2
 
5.4%
딩 2
 
5.4%
성 2
 
5.4%
Other values (9) 12
32.4%
Lowercase Letter
ValueCountFrequency (%)
m 6
16.2%
p 5
13.5%
s 5
13.5%
a 4
10.8%
k 3
8.1%
v 3
8.1%
w 2
 
5.4%
n 2
 
5.4%
r 2
 
5.4%
t 2
 
5.4%
Other values (3) 3
8.1%
Decimal Number
ValueCountFrequency (%)
0 194
32.1%
1 88
14.6%
5 72
 
11.9%
3 62
 
10.3%
2 60
 
9.9%
6 40
 
6.6%
4 32
 
5.3%
7 20
 
3.3%
8 20
 
3.3%
9 16
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 6
37.5%
, 6
37.5%
/ 2
 
12.5%
* 2
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 743
53.0%
Latin 622
44.4%
Hangul 37
 
2.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 64
 
10.3%
D 59
 
9.5%
A 58
 
9.3%
H 51
 
8.2%
Y 40
 
6.4%
R 35
 
5.6%
C 30
 
4.8%
T 29
 
4.7%
J 27
 
4.3%
G 26
 
4.2%
Other values (29) 203
32.6%
Hangul
ValueCountFrequency (%)
조 4
 
10.8%
파 4
 
10.8%
형 3
 
8.1%
기 2
 
5.4%
비 2
 
5.4%
시 2
 
5.4%
측 2
 
5.4%
산 2
 
5.4%
딩 2
 
5.4%
성 2
 
5.4%
Other values (9) 12
32.4%
Common
ValueCountFrequency (%)
0 194
26.1%
- 107
14.4%
1 88
11.8%
5 72
 
9.7%
3 62
 
8.3%
2 60
 
8.1%
6 40
 
5.4%
4 32
 
4.3%
7 20
 
2.7%
8 20
 
2.7%
Other values (8) 48
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1365
97.4%
Hangul 37
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 194
 
14.2%
- 107
 
7.8%
1 88
 
6.4%
5 72
 
5.3%
S 64
 
4.7%
3 62
 
4.5%
2 60
 
4.4%
D 59
 
4.3%
A 58
 
4.2%
H 51
 
3.7%
Other values (47) 550
40.3%
Hangul
ValueCountFrequency (%)
조 4
 
10.8%
파 4
 
10.8%
형 3
 
8.1%
기 2
 
5.4%
비 2
 
5.4%
시 2
 
5.4%
측 2
 
5.4%
산 2
 
5.4%
딩 2
 
5.4%
성 2
 
5.4%
Other values (9) 12
32.4%

규격
Text

Distinct91
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T09:05:41.837750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.622549
Min length2

Characters and Unicode

Total characters1963
Distinct characters134
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

Unique44 ?
Unique (%)21.6%

Sample

1st row45(33)/38(28)
2nd row마력/PTO 33(24)/32(24)
3rd row마력/PTO 33(24)/32(24)
4th row85kw터보,24단변속
5th row45마력
ValueCountFrequency (%)
소요동력 36
 
10.7%
인력용 20
 
6.0%
자주보행형 15
 
4.5%
5.3ps 15
 
4.5%
1줄 10
 
3.0%
2줄 10
 
3.0%
6.5ps 10
 
3.0%
고추50kg(생고추 9
 
2.7%
2포대 9
 
2.7%
40cm 5
 
1.5%
Other values (115) 196
58.5%
2023-12-13T09:05:42.208465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
6.7%
0 114
 
5.8%
5 109
 
5.6%
력 91
 
4.6%
3 91
 
4.6%
2 80
 
4.1%
4 61
 
3.1%
, 58
 
3.0%
1 58
 
3.0%
. 57
 
2.9%
Other values (124) 1113
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
35.8%
Decimal Number 619
31.5%
Lowercase Letter 254
 
12.9%
Other Punctuation 146
 
7.4%
Space Separator 131
 
6.7%
Math Symbol 31
 
1.6%
Uppercase Letter 29
 
1.5%
Open Punctuation 19
 
1.0%
Close Punctuation 18
 
0.9%
Other Symbol 11
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
력 91
 
13.0%
동 48
 
6.8%
요 38
 
5.4%
소 38
 
5.4%
마 33
 
4.7%
형 32
 
4.6%
용 31
 
4.4%
인 21
 
3.0%
자 20
 
2.8%
줄 20
 
2.8%
Other values (79) 330
47.0%
Uppercase Letter
ValueCountFrequency (%)
S 4
13.8%
O 4
13.8%
F 3
10.3%
V 3
10.3%
L 2
6.9%
W 2
6.9%
G 2
6.9%
R 2
6.9%
T 2
6.9%
P 2
6.9%
Other values (3) 3
10.3%
Decimal Number
ValueCountFrequency (%)
0 114
18.4%
5 109
17.6%
3 91
14.7%
2 80
12.9%
4 61
9.9%
1 58
9.4%
6 41
 
6.6%
8 34
 
5.5%
7 18
 
2.9%
9 13
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
p 49
19.3%
s 49
19.3%
m 46
18.1%
k 32
12.6%
c 29
11.4%
g 24
9.4%
w 9
 
3.5%
h 9
 
3.5%
ℓ 6
 
2.4%
t 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 58
39.7%
. 57
39.0%
/ 24
16.4%
* 7
 
4.8%
Other Symbol
ValueCountFrequency (%)
㎝ 6
54.5%
㎥ 3
27.3%
㎏ 2
 
18.2%
Space Separator
ValueCountFrequency (%)
131
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 984
50.1%
Hangul 702
35.8%
Latin 277
 
14.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
력 91
 
13.0%
동 48
 
6.8%
요 38
 
5.4%
소 38
 
5.4%
마 33
 
4.7%
형 32
 
4.6%
용 31
 
4.4%
인 21
 
3.0%
자 20
 
2.8%
줄 20
 
2.8%
Other values (79) 330
47.0%
Common
ValueCountFrequency (%)
131
13.3%
0 114
11.6%
5 109
11.1%
3 91
9.2%
2 80
8.1%
4 61
 
6.2%
, 58
 
5.9%
1 58
 
5.9%
. 57
 
5.8%
6 41
 
4.2%
Other values (13) 184
18.7%
Latin
ValueCountFrequency (%)
p 49
17.7%
s 49
17.7%
m 46
16.6%
k 32
11.6%
c 29
10.5%
g 24
8.7%
w 9
 
3.2%
h 9
 
3.2%
S 4
 
1.4%
O 4
 
1.4%
Other values (12) 22
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1244
63.4%
Hangul 702
35.8%
CJK Compat 11
 
0.6%
Letterlike Symbols 6
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
 
10.5%
0 114
 
9.2%
5 109
 
8.8%
3 91
 
7.3%
2 80
 
6.4%
4 61
 
4.9%
, 58
 
4.7%
1 58
 
4.7%
. 57
 
4.6%
p 49
 
3.9%
Other values (31) 436
35.0%
Hangul
ValueCountFrequency (%)
력 91
 
13.0%
동 48
 
6.8%
요 38
 
5.4%
소 38
 
5.4%
마 33
 
4.7%
형 32
 
4.6%
용 31
 
4.4%
인 21
 
3.0%
자 20
 
2.8%
줄 20
 
2.8%
Other values (79) 330
47.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 6
100.0%
CJK Compat
ValueCountFrequency (%)
㎝ 6
54.5%
㎥ 3
27.3%
㎏ 2
 
18.2%

Interactions

2023-12-13T09:05:39.498228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:05:39.350608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:05:39.567983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:05:39.425712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:05:42.289470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호합계구입년월일형식명규격
번호1.0000.3240.7890.9960.993
합계0.3241.0000.8031.0000.999
구입년월일0.7890.8031.0001.0000.998
형식명0.9961.0001.0001.0001.000
규격0.9930.9990.9981.0001.000
2023-12-13T09:05:42.371742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호합계
번호1.000-0.494
합계-0.4941.000

Missing values

2023-12-13T09:05:39.654011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:05:39.733562image/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

번호관리번호합계구입년월일형식명규격
01농용트랙터-01175220002009-04-28AF45545(33)/38(28)
12농용트랙터-02133650002009-06-29AF325마력/PTO 33(24)/32(24)
23농용트랙터-03133650002009-06-29AF325마력/PTO 33(24)/32(24)
34농용트랙터-04937394702010-01-13대동643085kw터보,24단변속
45농용트랙터-05191289602011-01-14NF455-045마력
56농용트랙터-06430770002012-01-01KS750575마력
67농용트랙터-07212020002012-01-01NF45545마력
78농용트랙터-08251309762014-08-27DYNAQ4747마력
89농용트랙터-09251309762014-08-27DYNAQ 4747마력
910농용트랙터 결속기-01161400002009-06-18markant45드럼폭1190mm, 40마력, 사각형
번호관리번호합계구입년월일형식명규격
194195엔진양수기-034800002009-06-29WB30X5.5/3,600
195196휴대형비료살포기-014100002009-06-18BH60303.7마력, 30ℓ
196197휴대형비료살포기-024100002009-06-18BH60303.7마력, 30ℓ
197198휴대형비료살포기-034100002009-06-18BH60303.7마력, 30ℓ
198199휴대형비료살포기-044100002009-06-18BH60303.7마력, 30ℓ
199200벽돌기계-0135900002009-06-18단상220V400kg
200201자동접목기-01375525452011-01-14GS-600 CS300w
201202비닐접착기-0120000002010-01-14600*5(mm)반자동 각도조절형
202203비닐접착기-0220000002010-01-14600*5(mm)반자동 각도조절형
203204동력이식기-0149500002011-01-14가변형,TP-101식