Overview

Dataset statistics

Number of variables7
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)1.9%
Total size in memory3.2 KiB
Average record size in memory61.4 B

Variable types

Text3
DateTime1
Numeric3

Dataset

Description경상남도 남해군 보조사업관리시스템에 등록된 보조사업추진현황정보입니다. 취득재산명, 규격명, 취득일자, 취득수량, 설치장소, 단가 등 정보를 포함하고 있습니다.
Author경상남도 남해군
URLhttps://www.data.go.kr/data/15041220/fileData.do

Alerts

Dataset has 1 (1.9%) duplicate rowsDuplicates
단가 is highly overall correlated with 취득가액High correlation
취득가액 is highly overall correlated with 단가High correlation

Reproduction

Analysis started2023-12-12 10:03:37.595727
Analysis finished2023-12-12 10:03:39.576083
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

취득재산명
Text

Distinct28
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T19:03:39.736771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16.5
Mean length6.7037037
Min length2

Characters and Unicode

Total characters362
Distinct characters89
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)44.4%

Sample

1st row토지
2nd row사랑의 집 1식
3rd row사랑의 집수리
4th row안마의자
5th row안마의자
ValueCountFrequency (%)
안마의자 19
20.4%
자동 13
14.0%
소독분무기 13
14.0%
수리 8
 
8.6%
사랑의 2
 
2.2%
및 2
 
2.2%
좌식형 2
 
2.2%
집하장 2
 
2.2%
농산물 2
 
2.2%
의자 1
 
1.1%
Other values (29) 29
31.2%
2023-12-12T19:03:40.200358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
10.8%
자 34
 
9.4%
기 23
 
6.4%
의 22
 
6.1%
마 20
 
5.5%
안 19
 
5.2%
소 15
 
4.1%
분 14
 
3.9%
무 14
 
3.9%
동 14
 
3.9%
Other values (79) 148
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
88.4%
Space Separator 39
 
10.8%
Decimal Number 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 34
 
10.6%
기 23
 
7.2%
의 22
 
6.9%
마 20
 
6.2%
안 19
 
5.9%
소 15
 
4.7%
분 14
 
4.4%
무 14
 
4.4%
동 14
 
4.4%
독 13
 
4.1%
Other values (76) 132
41.2%
Space Separator
ValueCountFrequency (%)
39
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
88.4%
Common 42
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 34
 
10.6%
기 23
 
7.2%
의 22
 
6.9%
마 20
 
6.2%
안 19
 
5.9%
소 15
 
4.7%
분 14
 
4.4%
무 14
 
4.4%
동 14
 
4.4%
독 13
 
4.1%
Other values (76) 132
41.2%
Common
ValueCountFrequency (%)
39
92.9%
1 2
 
4.8%
, 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
88.4%
ASCII 42
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
92.9%
1 2
 
4.8%
, 1
 
2.4%
Hangul
ValueCountFrequency (%)
자 34
 
10.6%
기 23
 
7.2%
의 22
 
6.9%
마 20
 
6.2%
안 19
 
5.9%
소 15
 
4.7%
분 14
 
4.4%
무 14
 
4.4%
동 14
 
4.4%
독 13
 
4.1%
Other values (76) 132
41.2%

규격명
Text

Distinct28
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T19:03:40.449878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length24
Mean length7.9444444
Min length2

Characters and Unicode

Total characters429
Distinct characters91
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

Unique22 ?
Unique (%)40.7%

Sample

1st row설천면 노량리 405,406번지
2nd row신축 1식
3rd row개보수 11식
4th rowHTT-971
5th rowHTT-971
ValueCountFrequency (%)
80a 14
20.9%
htt-971 8
 
11.9%
사파머신 4
 
6.0%
mc-02 3
 
4.5%
htt-10 2
 
3.0%
없음 2
 
3.0%
255l/rt25har4dww 1
 
1.5%
1.2m 1
 
1.5%
2구 1
 
1.5%
철골 1
 
1.5%
Other values (30) 30
44.8%
2023-12-12T19:03:40.890934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 56
 
13.1%
1 30
 
7.0%
T 25
 
5.8%
- 21
 
4.9%
2 18
 
4.2%
5 17
 
4.0%
H 17
 
4.0%
8 16
 
3.7%
9 14
 
3.3%
a 14
 
3.3%
Other values (81) 201
46.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 187
43.6%
Uppercase Letter 86
20.0%
Other Letter 67
 
15.6%
Other Punctuation 31
 
7.2%
Dash Punctuation 21
 
4.9%
Lowercase Letter 20
 
4.7%
Space Separator 13
 
3.0%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 5
 
7.5%
파 4
 
6.0%
머 4
 
6.0%
사 4
 
6.0%
기 2
 
3.0%
서 2
 
3.0%
음 2
 
3.0%
없 2
 
3.0%
식 2
 
3.0%
설 1
 
1.5%
Other values (39) 39
58.2%
Uppercase Letter
ValueCountFrequency (%)
T 25
29.1%
H 17
19.8%
W 7
 
8.1%
D 6
 
7.0%
M 5
 
5.8%
C 4
 
4.7%
A 4
 
4.7%
S 4
 
4.7%
R 2
 
2.3%
P 2
 
2.3%
Other values (8) 10
 
11.6%
Decimal Number
ValueCountFrequency (%)
0 56
29.9%
1 30
16.0%
2 18
 
9.6%
5 17
 
9.1%
8 16
 
8.6%
9 14
 
7.5%
7 13
 
7.0%
4 9
 
4.8%
6 9
 
4.8%
3 5
 
2.7%
Other Punctuation
ValueCountFrequency (%)
* 13
41.9%
, 8
25.8%
. 4
 
12.9%
/ 3
 
9.7%
\ 1
 
3.2%
" 1
 
3.2%
& 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
a 14
70.0%
m 4
 
20.0%
g 2
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 256
59.7%
Latin 106
24.7%
Hangul 67
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 5
 
7.5%
파 4
 
6.0%
머 4
 
6.0%
사 4
 
6.0%
기 2
 
3.0%
서 2
 
3.0%
음 2
 
3.0%
없 2
 
3.0%
식 2
 
3.0%
설 1
 
1.5%
Other values (39) 39
58.2%
Common
ValueCountFrequency (%)
0 56
21.9%
1 30
11.7%
- 21
 
8.2%
2 18
 
7.0%
5 17
 
6.6%
8 16
 
6.2%
9 14
 
5.5%
7 13
 
5.1%
* 13
 
5.1%
13
 
5.1%
Other values (11) 45
17.6%
Latin
ValueCountFrequency (%)
T 25
23.6%
H 17
16.0%
a 14
13.2%
W 7
 
6.6%
D 6
 
5.7%
M 5
 
4.7%
C 4
 
3.8%
A 4
 
3.8%
S 4
 
3.8%
m 4
 
3.8%
Other values (11) 16
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 362
84.4%
Hangul 67
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 56
15.5%
1 30
 
8.3%
T 25
 
6.9%
- 21
 
5.8%
2 18
 
5.0%
5 17
 
4.7%
H 17
 
4.7%
8 16
 
4.4%
9 14
 
3.9%
a 14
 
3.9%
Other values (32) 134
37.0%
Hangul
ValueCountFrequency (%)
신 5
 
7.5%
파 4
 
6.0%
머 4
 
6.0%
사 4
 
6.0%
기 2
 
3.0%
서 2
 
3.0%
음 2
 
3.0%
없 2
 
3.0%
식 2
 
3.0%
설 1
 
1.5%
Other values (39) 39
58.2%

취득일자
Date

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2016-03-30 00:00:00
Maximum2017-12-19 00:00:00
2023-12-12T19:03:41.053727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:41.236885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

단가
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7741595.6
Minimum50000
Maximum1.3 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T19:03:41.418263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50000
5-th percentile135000
Q1337500
median1700000
Q35000000
95-th percentile27000000
Maximum1.3 × 108
Range1.2995 × 108
Interquartile range (IQR)4662500

Descriptive statistics

Standard deviation19307496
Coefficient of variation (CV)2.4939945
Kurtosis31.46306
Mean7741595.6
Median Absolute Deviation (MAD)1592500
Skewness5.2571516
Sum4.1804616 × 108
Variance3.7277942 × 1014
MonotonicityNot monotonic
2023-12-12T19:03:41.602282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
5000000 14
25.9%
1700000 6
 
11.1%
1650000 3
 
5.6%
450000 2
 
3.7%
300000 2
 
3.7%
135000 2
 
3.7%
190000 2
 
3.7%
200000 2
 
3.7%
130000000 1
 
1.9%
4180000 1
 
1.9%
Other values (19) 19
35.2%
ValueCountFrequency (%)
50000 1
1.9%
80000 1
1.9%
135000 2
3.7%
173160 1
1.9%
190000 2
3.7%
200000 2
3.7%
230000 1
1.9%
240000 1
1.9%
260000 1
1.9%
300000 2
3.7%
ValueCountFrequency (%)
130000000 1
1.9%
50000000 1
1.9%
40000000 1
1.9%
20000000 1
1.9%
19700000 1
1.9%
17600000 1
1.9%
15000000 1
1.9%
11800000 1
1.9%
8200000 1
1.9%
8003000 1
1.9%

수량
Real number (ℝ)

Distinct6
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5185185
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T19:03:41.787050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile10
Maximum197
Range196
Interquartile range (IQR)0

Descriptive statistics

Standard deviation35.542555
Coefficient of variation (CV)4.1723869
Kurtosis24.459306
Mean8.5185185
Median Absolute Deviation (MAD)0
Skewness5.0375702
Sum460
Variance1263.2732
MonotonicityNot monotonic
2023-12-12T19:03:41.950633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 46
85.2%
10 3
 
5.6%
2 2
 
3.7%
5 1
 
1.9%
197 1
 
1.9%
178 1
 
1.9%
ValueCountFrequency (%)
1 46
85.2%
2 2
 
3.7%
5 1
 
1.9%
10 3
 
5.6%
178 1
 
1.9%
197 1
 
1.9%
ValueCountFrequency (%)
197 1
 
1.9%
178 1
 
1.9%
10 3
 
5.6%
5 1
 
1.9%
2 2
 
3.7%
1 46
85.2%

취득가액
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10612307
Minimum50000
Maximum1.3 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T19:03:42.128516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50000
5-th percentile190000
Q11350000
median3520000
Q35000000
95-th percentile53150000
Maximum1.3 × 108
Range1.2995 × 108
Interquartile range (IQR)3650000

Descriptive statistics

Standard deviation21817574
Coefficient of variation (CV)2.0558747
Kurtosis17.150525
Mean10612307
Median Absolute Deviation (MAD)2045000
Skewness3.7855798
Sum5.730646 × 108
Variance4.7600656 × 1014
MonotonicityNot monotonic
2023-12-12T19:03:42.317335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5000000 14
25.9%
1700000 6
 
11.1%
1650000 3
 
5.6%
450000 2
 
3.7%
1350000 2
 
3.7%
190000 2
 
3.7%
130000000 1
 
1.9%
17600000 1
 
1.9%
4180000 1
 
1.9%
700000 1
 
1.9%
Other values (21) 21
38.9%
ValueCountFrequency (%)
50000 1
1.9%
80000 1
1.9%
190000 2
3.7%
200000 1
1.9%
230000 1
1.9%
240000 1
1.9%
260000 1
1.9%
300000 1
1.9%
450000 2
3.7%
700000 1
1.9%
ValueCountFrequency (%)
130000000 1
1.9%
59100000 1
1.9%
59000000 1
1.9%
50000000 1
1.9%
40000000 1
1.9%
35600000 1
1.9%
20000000 1
1.9%
19700000 1
1.9%
17600000 1
1.9%
16400000 1
1.9%

설치(시설)주소
Text

Distinct44
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T19:03:42.702893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length24.981481
Min length19

Characters and Unicode

Total characters1349
Distinct characters99
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)72.2%

Sample

1st row경상남도 남해군 설천면 노량리 405
2nd row경상남도 남해군 창선면 흥선로1505번길 20-26
3rd row경상남도 남해군 남해읍 스포츠로65번길 25-7 외 10개소
4th row경상남도 남해군 남해읍 망운로 188
5th row경상남도 남해군 삼동면 금송로 264
ValueCountFrequency (%)
경상남도 54
18.4%
남해군 53
18.1%
남해읍 18
 
6.1%
12 13
 
4.4%
망운로9번길 8
 
2.7%
한아름크리닝 8
 
2.7%
서면 8
 
2.7%
망운로 7
 
2.4%
창선면 5
 
1.7%
9번길 5
 
1.7%
Other values (88) 114
38.9%
2023-12-12T19:03:43.216022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
240
17.8%
남 145
 
10.7%
해 78
 
5.8%
경 62
 
4.6%
상 61
 
4.5%
군 57
 
4.2%
도 55
 
4.1%
로 46
 
3.4%
2 45
 
3.3%
1 44
 
3.3%
Other values (89) 516
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 887
65.8%
Space Separator 240
 
17.8%
Decimal Number 206
 
15.3%
Dash Punctuation 13
 
1.0%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 145
16.3%
해 78
 
8.8%
경 62
 
7.0%
상 61
 
6.9%
군 57
 
6.4%
도 55
 
6.2%
로 46
 
5.2%
면 37
 
4.2%
길 24
 
2.7%
리 24
 
2.7%
Other values (76) 298
33.6%
Decimal Number
ValueCountFrequency (%)
2 45
21.8%
1 44
21.4%
9 19
9.2%
7 17
 
8.3%
5 16
 
7.8%
4 14
 
6.8%
0 14
 
6.8%
3 13
 
6.3%
6 13
 
6.3%
8 11
 
5.3%
Space Separator
ValueCountFrequency (%)
240
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 887
65.8%
Common 462
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 145
16.3%
해 78
 
8.8%
경 62
 
7.0%
상 61
 
6.9%
군 57
 
6.4%
도 55
 
6.2%
로 46
 
5.2%
면 37
 
4.2%
길 24
 
2.7%
리 24
 
2.7%
Other values (76) 298
33.6%
Common
ValueCountFrequency (%)
240
51.9%
2 45
 
9.7%
1 44
 
9.5%
9 19
 
4.1%
7 17
 
3.7%
5 16
 
3.5%
4 14
 
3.0%
0 14
 
3.0%
3 13
 
2.8%
6 13
 
2.8%
Other values (3) 27
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 887
65.8%
ASCII 462
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
240
51.9%
2 45
 
9.7%
1 44
 
9.5%
9 19
 
4.1%
7 17
 
3.7%
5 16
 
3.5%
4 14
 
3.0%
0 14
 
3.0%
3 13
 
2.8%
6 13
 
2.8%
Other values (3) 27
 
5.8%
Hangul
ValueCountFrequency (%)
남 145
16.3%
해 78
 
8.8%
경 62
 
7.0%
상 61
 
6.9%
군 57
 
6.4%
도 55
 
6.2%
로 46
 
5.2%
면 37
 
4.2%
길 24
 
2.7%
리 24
 
2.7%
Other values (76) 298
33.6%

Interactions

2023-12-12T19:03:38.933854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.098748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.562080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:39.038362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.225540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.695904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:39.148011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.394679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:03:38.814491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:03:43.348746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취득재산명규격명취득일자단가수량취득가액설치(시설)주소
취득재산명1.0000.9980.9811.0001.0001.0000.000
규격명0.9981.0000.9851.0001.0001.0000.000
취득일자0.9810.9851.0000.9711.0000.9750.000
단가1.0001.0000.9711.0000.0000.9960.944
수량1.0001.0001.0000.0001.0000.9701.000
취득가액1.0001.0000.9750.9960.9701.0000.000
설치(시설)주소0.0000.0000.0000.9441.0000.0001.000
2023-12-12T19:03:43.486351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단가수량취득가액
단가1.000-0.2730.827
수량-0.2731.0000.210
취득가액0.8270.2101.000

Missing values

2023-12-12T19:03:39.317687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:03:39.511918image/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

취득재산명규격명취득일자단가수량취득가액설치(시설)주소
0토지설천면 노량리 405,406번지2016-03-301300000001130000000경상남도 남해군 설천면 노량리 405
1사랑의 집 1식신축 1식2016-12-1240000000140000000경상남도 남해군 창선면 흥선로1505번길 20-26
2사랑의 집수리개보수 11식2016-06-2250000000150000000경상남도 남해군 남해읍 스포츠로65번길 25-7 외 10개소
3안마의자HTT-9712016-04-22170000011700000경상남도 남해군 남해읍 망운로 188
4안마의자HTT-9712016-04-22165000011650000경상남도 남해군 삼동면 금송로 264
5안마의자HTT-9712016-04-22165000011650000경상남도 남해군 남면 남면로 326
6안마의자HTT-9712016-04-22160000011600000경상남도 남해군 남해읍 망운로 188
7안마의자HTT-9712016-04-22165000011650000경상남도 남해군 남면 남면로 326
8안마의자 및 좌식형 안마의자 수리(HTT-971)2등급, MC-022016-12-222400001240000경상남도 남해군 남해읍 강진만로160
9안마의자 수리HTT-102016-12-223000001300000경상남도 남해군 이동면 난음로 211
취득재산명규격명취득일자단가수량취득가액설치(시설)주소
44자동 소독분무기80a2017-12-11500000015000000경상남도 남해군 고현면 남치리 548
45자동 소독분무기80a2017-12-11500000015000000경상남도 남해군 설천면 진목리 1227
46농산물 집하장391.342017-12-1117600000117600000경상남도 남해군 서면 스포츠로 470번길 10
47농산물 집하장146.72017-07-1720000000120000000경상남도 남해군 서면 서호리 714-1
48환풍기1.2m2017-08-3030000019759100000경상남도 남해군 남해읍 망운로 9번길 12
49급수기2구2017-09-2920000017835600000경상남도 남해군 남해읍 망운로 9번길 12
50농기계 보관창고철골2017-09-25800300018003000경상남도 남해군 창선면 상죽리 422-1
51컴퓨터DM400S6Z-E301C, 24\" 삼성컴퓨터2017-12-19110000011100000경상남도 남해군 남해읍 망운로 9번길 12 민주평화통일자문회의남해군협의회
52냉장고255L/RT25HAR4DWW2017-12-194500001450000경상남도 남해군남해읍 망운로 9번길 12 민주평화통일자문회의남해군협의회
53의자 및 책상W1600*D1200*H720책상, W400*D575*H600 서랍장, W620*D640*H1150 의자2017-12-194500001450000경상남도 남해군 남해읍 망운로 9번길 12 민주평화통일자문회의남해군협의회

Duplicate rows

Most frequently occurring

취득재산명규격명취득일자단가수량취득가액설치(시설)주소# duplicates
0안마의자HTT-9712016-04-22165000011650000경상남도 남해군 남면 남면로 3262