Overview

Dataset statistics

Number of variables7
Number of observations3107
Missing cells3106
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory173.1 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Text4
Categorical2

Dataset

Description경상남도 수목원에 대한 데이터로, 수목원명, 공립/사립 구분, 주소, 개원일, 면적, 연락처, 식물자원 보유현황(종 개수) 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079052

Alerts

참고사항 has constant value ""Constant
보유경위 is highly imbalanced (56.6%)Imbalance
원산지 is highly imbalanced (72.3%)Imbalance
참고사항 has 3106 (> 99.9%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-04-19 06:49:45.106923
Analysis finished2024-04-19 06:49:46.295967
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct3107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1554
Minimum1
Maximum3107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.4 KiB
2024-04-19T15:49:46.374106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile156.3
Q1777.5
median1554
Q32330.5
95-th percentile2951.7
Maximum3107
Range3106
Interquartile range (IQR)1553

Descriptive statistics

Standard deviation897.05797
Coefficient of variation (CV)0.57725738
Kurtosis-1.2
Mean1554
Median Absolute Deviation (MAD)777
Skewness0
Sum4828278
Variance804713
MonotonicityStrictly increasing
2024-04-19T15:49:46.504837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2089 1
 
< 0.1%
2067 1
 
< 0.1%
2068 1
 
< 0.1%
2069 1
 
< 0.1%
2070 1
 
< 0.1%
2071 1
 
< 0.1%
2072 1
 
< 0.1%
2073 1
 
< 0.1%
2074 1
 
< 0.1%
Other values (3097) 3097
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3107 1
< 0.1%
3106 1
< 0.1%
3105 1
< 0.1%
3104 1
< 0.1%
3103 1
< 0.1%
3102 1
< 0.1%
3101 1
< 0.1%
3100 1
< 0.1%
3099 1
< 0.1%
3098 1
< 0.1%

식물유전자명
Text

Distinct3096
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
2024-04-19T15:49:46.729309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length6.9417444
Min length1

Characters and Unicode

Total characters21568
Distinct characters798
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3085 ?
Unique (%)99.3%

Sample

1st rowDipsacus laciniatus L.
2nd rowEcheveria cv. 'Early light'
3rd rowLycopodium pblehmaria
4th rowLycopodium pinifolia
5th rowLycopodium pinipens
ValueCountFrequency (%)
무궁화 88
 
2.0%
비비추 67
 
1.5%
밤나무 61
 
1.4%
단풍나무 51
 
1.1%
아이비 48
 
1.1%
산수국 47
 
1.0%
일본철쭉 46
 
1.0%
모란 36
 
0.8%
아렌스노루오줌 23
 
0.5%
장미 23
 
0.5%
Other values (3286) 4022
89.1%
2024-04-19T15:49:47.099318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 2034
 
9.4%
1425
 
6.6%
무 960
 
4.5%
나 952
 
4.4%
리 484
 
2.2%
아 398
 
1.8%
스 373
 
1.7%
이 346
 
1.6%
비 342
 
1.6%
화 253
 
1.2%
Other values (788) 14001
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17430
80.8%
Other Punctuation 2076
 
9.6%
Space Separator 1425
 
6.6%
Lowercase Letter 471
 
2.2%
Decimal Number 84
 
0.4%
Uppercase Letter 31
 
0.1%
Open Punctuation 15
 
0.1%
Close Punctuation 15
 
0.1%
Dash Punctuation 7
 
< 0.1%
Final Punctuation 7
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 960
 
5.5%
나 952
 
5.5%
리 484
 
2.8%
아 398
 
2.3%
스 373
 
2.1%
이 346
 
2.0%
비 342
 
2.0%
화 253
 
1.5%
수 216
 
1.2%
라 202
 
1.2%
Other values (729) 12904
74.0%
Lowercase Letter
ValueCountFrequency (%)
p 91
19.3%
s 54
11.5%
a 49
10.4%
i 37
 
7.9%
n 30
 
6.4%
e 26
 
5.5%
l 21
 
4.5%
r 20
 
4.2%
o 19
 
4.0%
u 16
 
3.4%
Other values (12) 108
22.9%
Uppercase Letter
ValueCountFrequency (%)
A 5
16.1%
L 5
16.1%
E 4
12.9%
N 3
9.7%
C 3
9.7%
B 2
 
6.5%
H 2
 
6.5%
K 2
 
6.5%
G 2
 
6.5%
M 1
 
3.2%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 22
26.2%
0 19
22.6%
2 10
11.9%
3 8
 
9.5%
7 6
 
7.1%
5 5
 
6.0%
4 5
 
6.0%
6 4
 
4.8%
8 3
 
3.6%
9 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
' 2034
98.0%
. 40
 
1.9%
; 1
 
< 0.1%
" 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 13
86.7%
[ 2
 
13.3%
Close Punctuation
ValueCountFrequency (%)
) 13
86.7%
] 2
 
13.3%
Final Punctuation
ValueCountFrequency (%)
’ 6
85.7%
” 1
 
14.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 5
83.3%
“ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17430
80.8%
Common 3636
 
16.9%
Latin 502
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 960
 
5.5%
나 952
 
5.5%
리 484
 
2.8%
아 398
 
2.3%
스 373
 
2.1%
이 346
 
2.0%
비 342
 
2.0%
화 253
 
1.5%
수 216
 
1.2%
라 202
 
1.2%
Other values (729) 12904
74.0%
Latin
ValueCountFrequency (%)
p 91
18.1%
s 54
 
10.8%
a 49
 
9.8%
i 37
 
7.4%
n 30
 
6.0%
e 26
 
5.2%
l 21
 
4.2%
r 20
 
4.0%
o 19
 
3.8%
u 16
 
3.2%
Other values (24) 139
27.7%
Common
ValueCountFrequency (%)
' 2034
55.9%
1425
39.2%
. 40
 
1.1%
1 22
 
0.6%
0 19
 
0.5%
( 13
 
0.4%
) 13
 
0.4%
2 10
 
0.3%
3 8
 
0.2%
- 7
 
0.2%
Other values (15) 45
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17430
80.8%
ASCII 4125
 
19.1%
Punctuation 13
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 2034
49.3%
1425
34.5%
p 91
 
2.2%
s 54
 
1.3%
a 49
 
1.2%
. 40
 
1.0%
i 37
 
0.9%
n 30
 
0.7%
e 26
 
0.6%
1 22
 
0.5%
Other values (45) 317
 
7.7%
Hangul
ValueCountFrequency (%)
무 960
 
5.5%
나 952
 
5.5%
리 484
 
2.8%
아 398
 
2.3%
스 373
 
2.1%
이 346
 
2.0%
비 342
 
2.0%
화 253
 
1.5%
수 216
 
1.2%
라 202
 
1.2%
Other values (729) 12904
74.0%
Punctuation
ValueCountFrequency (%)
’ 6
46.2%
‘ 5
38.5%
“ 1
 
7.7%
” 1
 
7.7%

보유연월일
Text

Distinct91
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
2024-04-19T15:49:47.291691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters31070
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

Unique25 ?
Unique (%)0.8%

Sample

1st row1989-01-02
2nd row1989-01-01
3rd row2014-09-23
4th row2014-09-23
5th row2014-09-23
ValueCountFrequency (%)
1989-01-01 597
19.2%
2014-11-13 253
 
8.1%
2000-01-30 199
 
6.4%
2009-06-24 197
 
6.3%
1993-08-20 130
 
4.2%
2014-09-23 124
 
4.0%
2008-06-01 122
 
3.9%
2008-06-25 113
 
3.6%
2011-06-21 99
 
3.2%
2007-02-14 93
 
3.0%
Other values (81) 1180
38.0%
2024-04-19T15:49:47.602236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7833
25.2%
- 6214
20.0%
1 5824
18.7%
2 3801
12.2%
9 2108
 
6.8%
3 1261
 
4.1%
4 1202
 
3.9%
8 1062
 
3.4%
6 699
 
2.2%
5 612
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24856
80.0%
Dash Punctuation 6214
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7833
31.5%
1 5824
23.4%
2 3801
15.3%
9 2108
 
8.5%
3 1261
 
5.1%
4 1202
 
4.8%
8 1062
 
4.3%
6 699
 
2.8%
5 612
 
2.5%
7 454
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 6214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31070
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7833
25.2%
- 6214
20.0%
1 5824
18.7%
2 3801
12.2%
9 2108
 
6.8%
3 1261
 
4.1%
4 1202
 
3.9%
8 1062
 
3.4%
6 699
 
2.2%
5 612
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7833
25.2%
- 6214
20.0%
1 5824
18.7%
2 3801
12.2%
9 2108
 
6.8%
3 1261
 
4.1%
4 1202
 
3.9%
8 1062
 
3.4%
6 699
 
2.2%
5 612
 
2.0%

보유경위
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
구입
2266 
이식
508 
채집
 
182
분양
 
81
자생
 
29
Other values (3)
 
41

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이식
2nd row이식
3rd row교환
4th row교환
5th row교환

Common Values

ValueCountFrequency (%)
구입 2266
72.9%
이식 508
 
16.4%
채집 182
 
5.9%
분양 81
 
2.6%
자생 29
 
0.9%
무상 18
 
0.6%
교환 15
 
0.5%
기증 8
 
0.3%

Length

2024-04-19T15:49:47.729702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:47.833529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구입 2266
72.9%
이식 508
 
16.4%
채집 182
 
5.9%
분양 81
 
2.6%
자생 29
 
0.9%
무상 18
 
0.6%
교환 15
 
0.5%
기증 8
 
0.3%

원산지
Categorical

IMBALANCE 

Distinct32
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
한국
2129 
품종
749 
일본
 
85
영국
 
45
미국
 
18
Other values (27)
 
81

Length

Max length10
Median length2
Mean length2.0492436
Min length2

Unique

Unique15 ?
Unique (%)0.5%

Sample

1st row한국
2nd row한국
3rd row품종
4th row품종
5th row품종

Common Values

ValueCountFrequency (%)
한국 2129
68.5%
품종 749
 
24.1%
일본 85
 
2.7%
영국 45
 
1.4%
미국 18
 
0.6%
유럽 17
 
0.5%
동남아시아 11
 
0.4%
중국 8
 
0.3%
미국 8
 
0.3%
인도 4
 
0.1%
Other values (22) 33
 
1.1%

Length

2024-04-19T15:49:47.998006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국 2132
68.4%
품종 749
 
24.0%
일본 88
 
2.8%
영국 45
 
1.4%
미국 26
 
0.8%
유럽 17
 
0.5%
동남아시아 11
 
0.4%
중국 11
 
0.4%
인도 4
 
0.1%
북아메리카 4
 
0.1%
Other values (21) 29
 
0.9%

산지
Text

Distinct73
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
2024-04-19T15:49:48.219455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length5.9497908
Min length2

Characters and Unicode

Total characters18486
Distinct characters126
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.6%

Sample

1st row경남 진주시
2nd row경남 진주시
3rd row고운자연농원
4th row고운자연농원
5th row고운자연농원
ValueCountFrequency (%)
경남 601
15.1%
진주시 587
14.8%
기청산식물원 429
 
10.8%
미산식물원 400
 
10.1%
대한종묘(구례 181
 
4.6%
대림원예종묘 181
 
4.6%
제주도 117
 
2.9%
제주시 110
 
2.8%
천리포수목원 102
 
2.6%
하나건설 97
 
2.4%
Other values (69) 1170
29.4%
2024-04-19T15:49:48.598634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1722
 
9.3%
물 1089
 
5.9%
식 1089
 
5.9%
산 1005
 
5.4%
872
 
4.7%
주 814
 
4.4%
시 784
 
4.2%
경 771
 
4.2%
남 686
 
3.7%
진 588
 
3.2%
Other values (116) 9066
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17111
92.6%
Space Separator 872
 
4.7%
Open Punctuation 241
 
1.3%
Close Punctuation 241
 
1.3%
Uppercase Letter 21
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1722
 
10.1%
물 1089
 
6.4%
식 1089
 
6.4%
산 1005
 
5.9%
주 814
 
4.8%
시 784
 
4.6%
경 771
 
4.5%
남 686
 
4.0%
진 588
 
3.4%
미 553
 
3.2%
Other values (110) 8010
46.8%
Uppercase Letter
ValueCountFrequency (%)
C 7
33.3%
N 7
33.3%
F 7
33.3%
Space Separator
ValueCountFrequency (%)
872
100.0%
Open Punctuation
ValueCountFrequency (%)
( 241
100.0%
Close Punctuation
ValueCountFrequency (%)
) 241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17111
92.6%
Common 1354
 
7.3%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1722
 
10.1%
물 1089
 
6.4%
식 1089
 
6.4%
산 1005
 
5.9%
주 814
 
4.8%
시 784
 
4.6%
경 771
 
4.5%
남 686
 
4.0%
진 588
 
3.4%
미 553
 
3.2%
Other values (110) 8010
46.8%
Common
ValueCountFrequency (%)
872
64.4%
( 241
 
17.8%
) 241
 
17.8%
Latin
ValueCountFrequency (%)
C 7
33.3%
N 7
33.3%
F 7
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17111
92.6%
ASCII 1375
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1722
 
10.1%
물 1089
 
6.4%
식 1089
 
6.4%
산 1005
 
5.9%
주 814
 
4.8%
시 784
 
4.6%
경 771
 
4.5%
남 686
 
4.0%
진 588
 
3.4%
미 553
 
3.2%
Other values (110) 8010
46.8%
ASCII
ValueCountFrequency (%)
872
63.4%
( 241
 
17.5%
) 241
 
17.5%
C 7
 
0.5%
N 7
 
0.5%
F 7
 
0.5%

참고사항
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3106
Missing (%)> 99.9%
Memory size24.4 KiB
2024-04-19T15:49:48.761199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
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

Unique1 ?
Unique (%)100.0%

Sample

1st row천연기념물 1299
ValueCountFrequency (%)
천연기념물 1
50.0%
1299 1
50.0%
2024-04-19T15:49:49.005371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2
20.0%
천 1
10.0%
연 1
10.0%
기 1
10.0%
념 1
10.0%
물 1
10.0%
1
10.0%
1 1
10.0%
2 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
50.0%
Decimal Number 4
40.0%
Space Separator 1
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 1
20.0%
연 1
20.0%
기 1
20.0%
념 1
20.0%
물 1
20.0%
Decimal Number
ValueCountFrequency (%)
9 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
50.0%
Hangul 5
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 1
20.0%
연 1
20.0%
기 1
20.0%
념 1
20.0%
물 1
20.0%
Common
ValueCountFrequency (%)
9 2
40.0%
1
20.0%
1 1
20.0%
2 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
50.0%
Hangul 5
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 2
40.0%
1
20.0%
1 1
20.0%
2 1
20.0%
Hangul
ValueCountFrequency (%)
천 1
20.0%
연 1
20.0%
기 1
20.0%
념 1
20.0%
물 1
20.0%

Interactions

2024-04-19T15:49:45.994798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:49:49.112898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호보유연월일보유경위원산지산지
일련번호1.0000.7720.3260.3670.719
보유연월일0.7721.0000.9870.8910.997
보유경위0.3260.9871.0000.3200.976
원산지0.3670.8910.3201.0000.755
산지0.7190.9970.9760.7551.000
2024-04-19T15:49:49.241540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보유경위원산지
보유경위1.0000.118
원산지0.1181.000
2024-04-19T15:49:49.326859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호보유경위원산지
일련번호1.0000.1620.138
보유경위0.1621.0000.118
원산지0.1380.1181.000

Missing values

2024-04-19T15:49:46.106281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:49:46.223954image/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

일련번호식물유전자명보유연월일보유경위원산지산지참고사항
01Dipsacus laciniatus L.1989-01-02이식한국경남 진주시<NA>
12Echeveria cv. 'Early light'1989-01-01이식한국경남 진주시<NA>
23Lycopodium pblehmaria2014-09-23교환품종고운자연농원<NA>
34Lycopodium pinifolia2014-09-23교환품종고운자연농원<NA>
45Lycopodium pinipens2014-09-23교환품종고운자연농원<NA>
56Lycopodium ssp philippines2014-09-23교환품종고운자연농원<NA>
67Mammillaria elongata var. echinaria1989-01-01이식한국경남 진주시<NA>
78가는기린초2010-11-04구입한국기청산식물원<NA>
89가는다리장구채2009-06-24구입한국기청산식물원<NA>
910가는잎조팝나무1989-01-01이식한국경남 진주시<NA>
일련번호식물유전자명보유연월일보유경위원산지산지참고사항
30973098히말라야자작2014-11-13구입영국미산식물원<NA>
30983099히베르니카아이비 '델토이데아'2008-06-25구입품종하나건설<NA>
30993100히베르니카아이비 '베티 앨런'2008-06-25구입품종하나건설<NA>
31003101히베르니카아이비 '해밀턴'2008-06-25구입품종하나건설<NA>
31013102히브리다말발도리 '스트로베리 필즈'2007-12-15구입품종미산식물원<NA>
31023103히소피폴리아쿠페아2008-06-25구입품종하나건설<NA>
31033104히아신스2014-07-11구입한국늘푸른식물원<NA>
31043105히어리2000-01-30구입한국대한종묘(구례)<NA>
31053106히에말리스동백 '샹소네트’1989-01-01구입품종천리포수목원<NA>
31063107히코리1989-01-01이식일본경남 진주시<NA>