Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells34
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory966.8 KiB
Average record size in memory99.0 B

Variable types

Numeric3
Text2
Categorical3
DateTime3

Dataset

Description부산광역시상수도사업본부_수용가정보시스템_계량기정보_20220131
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15100349

Alerts

급수관종류 is highly imbalanced (57.9%)Imbalance
검침코드명 is highly imbalanced (94.1%)Imbalance
연번 has unique valuesUnique
급수관연장 has 1831 (18.3%) zerosZeros

Reproduction

Analysis started2023-12-10 16:58:37.636090
Analysis finished2023-12-10 16:58:40.326056
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35252.906
Minimum2
Maximum71041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:40.418526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3437.6
Q117529
median35389.5
Q352731.5
95-th percentile67038.25
Maximum71041
Range71039
Interquartile range (IQR)35202.5

Descriptive statistics

Standard deviation20365.325
Coefficient of variation (CV)0.57769208
Kurtosis-1.1849749
Mean35252.906
Median Absolute Deviation (MAD)17598.5
Skewness-0.0026861034
Sum3.5252906 × 108
Variance4.1474645 × 108
MonotonicityNot monotonic
2023-12-11T01:58:40.619935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38025 1
 
< 0.1%
39015 1
 
< 0.1%
24689 1
 
< 0.1%
24022 1
 
< 0.1%
20366 1
 
< 0.1%
59303 1
 
< 0.1%
49005 1
 
< 0.1%
63750 1
 
< 0.1%
27723 1
 
< 0.1%
63069 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
13 1
< 0.1%
36 1
< 0.1%
40 1
< 0.1%
45 1
< 0.1%
53 1
< 0.1%
66 1
< 0.1%
68 1
< 0.1%
72 1
< 0.1%
82 1
< 0.1%
ValueCountFrequency (%)
71041 1
< 0.1%
71037 1
< 0.1%
71034 1
< 0.1%
71031 1
< 0.1%
71030 1
< 0.1%
71022 1
< 0.1%
71021 1
< 0.1%
71012 1
< 0.1%
71004 1
< 0.1%
71000 1
< 0.1%

고객번호
Text

Distinct3456
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T01:58:41.045215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60000
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

Unique1250 ?
Unique (%)12.5%

Sample

1st row43**28
2nd row19**49
3rd row09**50
4th row25**43
5th row29**90
ValueCountFrequency (%)
49**52 21
 
0.2%
49**31 19
 
0.2%
49**56 19
 
0.2%
49**81 17
 
0.2%
49**24 16
 
0.2%
50**99 16
 
0.2%
49**88 16
 
0.2%
49**49 16
 
0.2%
50**41 16
 
0.2%
49**67 16
 
0.2%
Other values (3446) 9828
98.3%
2023-12-11T01:58:41.617893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 20000
33.3%
4 5319
 
8.9%
2 4984
 
8.3%
1 4969
 
8.3%
0 4924
 
8.2%
5 4603
 
7.7%
9 3856
 
6.4%
3 3705
 
6.2%
6 2741
 
4.6%
8 2481
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40000
66.7%
Other Punctuation 20000
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5319
13.3%
2 4984
12.5%
1 4969
12.4%
0 4924
12.3%
5 4603
11.5%
9 3856
9.6%
3 3705
9.3%
6 2741
6.9%
8 2481
6.2%
7 2418
6.0%
Other Punctuation
ValueCountFrequency (%)
* 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 20000
33.3%
4 5319
 
8.9%
2 4984
 
8.3%
1 4969
 
8.3%
0 4924
 
8.2%
5 4603
 
7.7%
9 3856
 
6.4%
3 3705
 
6.2%
6 2741
 
4.6%
8 2481
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 20000
33.3%
4 5319
 
8.9%
2 4984
 
8.3%
1 4969
 
8.3%
0 4924
 
8.2%
5 4603
 
7.7%
9 3856
 
6.4%
3 3705
 
6.2%
6 2741
 
4.6%
8 2481
 
4.1%

본관종류
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
PFP
4263 
스테인레스관
2768 
닥타일주철관(시멘트)
2276 
에폭시라이닝관
 
289
닥타일주철관(에폭시)
 
281
Other values (6)
 
123

Length

Max length11
Median length7
Mean length5.9838
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowPFP
2nd row닥타일주철관(시멘트)
3rd row스테인레스관
4th row스테인레스관
5th row스테인레스관

Common Values

ValueCountFrequency (%)
PFP 4263
42.6%
스테인레스관 2768
27.7%
닥타일주철관(시멘트) 2276
22.8%
에폭시라이닝관 289
 
2.9%
닥타일주철관(에폭시) 281
 
2.8%
기타 99
 
1.0%
<NA> 11
 
0.1%
회주철 5
 
0.1%
아연도강관 4
 
< 0.1%
PE관 3
 
< 0.1%

Length

2023-12-11T01:58:41.795254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pfp 4263
42.6%
스테인레스관 2768
27.7%
닥타일주철관(시멘트 2276
22.8%
에폭시라이닝관 289
 
2.9%
닥타일주철관(에폭시 281
 
2.8%
기타 99
 
1.0%
na 11
 
0.1%
회주철 5
 
< 0.1%
아연도강관 4
 
< 0.1%
pe관 3
 
< 0.1%

본관구경
Text

Distinct336
Distinct (%)3.4%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T01:58:42.309237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length3.5192635
Min length2

Characters and Unicode

Total characters35168
Distinct characters21
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)1.5%

Sample

1st row65*25
2nd row300
3rd row13
4th row200*50
5th row25
ValueCountFrequency (%)
100 1160
 
11.6%
25 1155
 
11.6%
40 1066
 
10.7%
50 630
 
6.3%
150 518
 
5.2%
20 462
 
4.6%
65 455
 
4.6%
200 361
 
3.6%
13 285
 
2.9%
15 231
 
2.3%
Other values (324) 3671
36.7%
2023-12-11T01:58:42.941009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12036
34.2%
5 6170
17.5%
1 4648
 
13.2%
2 3909
 
11.1%
* 3595
 
10.2%
4 1992
 
5.7%
3 1308
 
3.7%
6 1091
 
3.1%
8 404
 
1.1%
7 3
 
< 0.1%
Other values (11) 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31561
89.7%
Other Punctuation 3597
 
10.2%
Other Letter 5
 
< 0.1%
Space Separator 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12036
38.1%
5 6170
19.5%
1 4648
 
14.7%
2 3909
 
12.4%
4 1992
 
6.3%
3 1308
 
4.1%
6 1091
 
3.5%
8 404
 
1.3%
7 3
 
< 0.1%
Other Letter
ValueCountFrequency (%)
금 1
20.0%
설 1
20.0%
건 1
20.0%
우 1
20.0%
신 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 3595
99.9%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35163
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12036
34.2%
5 6170
17.5%
1 4648
 
13.2%
2 3909
 
11.1%
* 3595
 
10.2%
4 1992
 
5.7%
3 1308
 
3.7%
6 1091
 
3.1%
8 404
 
1.1%
7 3
 
< 0.1%
Other values (6) 7
 
< 0.1%
Hangul
ValueCountFrequency (%)
금 1
20.0%
설 1
20.0%
건 1
20.0%
우 1
20.0%
신 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35163
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12036
34.2%
5 6170
17.5%
1 4648
 
13.2%
2 3909
 
11.1%
* 3595
 
10.2%
4 1992
 
5.7%
3 1308
 
3.7%
6 1091
 
3.1%
8 404
 
1.1%
7 3
 
< 0.1%
Other values (6) 7
 
< 0.1%
Hangul
ValueCountFrequency (%)
금 1
20.0%
설 1
20.0%
건 1
20.0%
우 1
20.0%
신 1
20.0%

급수관종류
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
스테인레스관
5796 
PFP
3300 
기타
703 
닥타일주철관(시멘트)
 
121
닥타일주철관(에폭시)
 
49
Other values (5)
 
31

Length

Max length11
Median length6
Mean length4.8139
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowPFP
2nd row닥타일주철관(시멘트)
3rd row기타
4th row스테인레스관
5th row기타

Common Values

ValueCountFrequency (%)
스테인레스관 5796
58.0%
PFP 3300
33.0%
기타 703
 
7.0%
닥타일주철관(시멘트) 121
 
1.2%
닥타일주철관(에폭시) 49
 
0.5%
에폭시라이닝관 20
 
0.2%
<NA> 6
 
0.1%
아연도강관 3
 
< 0.1%
HI-3P 1
 
< 0.1%
PE관 1
 
< 0.1%

Length

2023-12-11T01:58:43.111917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:58:43.245263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스테인레스관 5796
58.0%
pfp 3300
33.0%
기타 703
 
7.0%
닥타일주철관(시멘트 121
 
1.2%
닥타일주철관(에폭시 49
 
0.5%
에폭시라이닝관 20
 
0.2%
na 6
 
0.1%
아연도강관 3
 
< 0.1%
hi-3p 1
 
< 0.1%
pe관 1
 
< 0.1%

계량기구경
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.4896
Minimum15
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:43.383136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q115
median15
Q315
95-th percentile25
Maximum300
Range285
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.49879
Coefficient of variation (CV)0.78415921
Kurtosis112.32381
Mean18.4896
Median Absolute Deviation (MAD)0
Skewness9.0372735
Sum184896
Variance210.21491
MonotonicityNot monotonic
2023-12-11T01:58:43.507373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
15 7992
79.9%
20 949
 
9.5%
25 584
 
5.8%
40 150
 
1.5%
50 97
 
1.0%
80 81
 
0.8%
32 58
 
0.6%
100 46
 
0.5%
150 30
 
0.3%
200 5
 
0.1%
Other values (2) 8
 
0.1%
ValueCountFrequency (%)
15 7992
79.9%
20 949
 
9.5%
25 584
 
5.8%
32 58
 
0.6%
40 150
 
1.5%
50 97
 
1.0%
80 81
 
0.8%
100 46
 
0.5%
150 30
 
0.3%
200 5
 
0.1%
ValueCountFrequency (%)
300 3
 
< 0.1%
250 5
 
0.1%
200 5
 
0.1%
150 30
 
0.3%
100 46
 
0.5%
80 81
 
0.8%
50 97
 
1.0%
40 150
 
1.5%
32 58
 
0.6%
25 584
5.8%

급수관연장
Real number (ℝ)

ZEROS 

Distinct65
Distinct (%)0.7%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.3730238
Minimum0
Maximum266
Zeros1831
Zeros (%)18.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:43.651086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q36
95-th percentile15
Maximum266
Range266
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.1638999
Coefficient of variation (CV)1.6382028
Kurtosis231.29307
Mean4.3730238
Median Absolute Deviation (MAD)2
Skewness9.5412341
Sum43704
Variance51.321462
MonotonicityNot monotonic
2023-12-11T01:58:43.785522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2929
29.3%
0 1831
18.3%
6 724
 
7.2%
4 659
 
6.6%
3 622
 
6.2%
2 602
 
6.0%
5 576
 
5.8%
8 360
 
3.6%
7 281
 
2.8%
10 235
 
2.4%
Other values (55) 1175
11.8%
ValueCountFrequency (%)
0 1831
18.3%
1 2929
29.3%
2 602
 
6.0%
3 622
 
6.2%
4 659
 
6.6%
5 576
 
5.8%
6 724
 
7.2%
7 281
 
2.8%
8 360
 
3.6%
9 187
 
1.9%
ValueCountFrequency (%)
266 1
< 0.1%
156 1
< 0.1%
126 1
< 0.1%
113 1
< 0.1%
110 1
< 0.1%
105 1
< 0.1%
86 1
< 0.1%
78 1
< 0.1%
73 1
< 0.1%
70 2
< 0.1%

계량기설치일자
Date

Distinct332
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-04 00:00:00
Maximum2021-12-31 00:00:00
2023-12-11T01:58:43.934698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:44.098503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검침일자
Date

Distinct147
Distinct (%)1.5%
Missing21
Missing (%)0.2%
Memory size156.2 KiB
Minimum2013-06-01 00:00:00
Maximum2022-05-17 00:00:00
2023-12-11T01:58:44.599919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:44.845868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검침코드명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상
9812 
전화검침
 
58
급수중지
 
57
이사정산
 
38
<NA>
 
21
Other values (3)
 
14

Length

Max length5
Median length2
Mean length2.0382
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 9812
98.1%
전화검침 58
 
0.6%
급수중지 57
 
0.6%
이사정산 38
 
0.4%
<NA> 21
 
0.2%
자가검침 6
 
0.1%
계량기교체 6
 
0.1%
정수처분 2
 
< 0.1%

Length

2023-12-11T01:58:45.046291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:58:45.220738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 9812
98.1%
전화검침 58
 
0.6%
급수중지 57
 
0.6%
이사정산 38
 
0.4%
na 21
 
0.2%
자가검침 6
 
0.1%
계량기교체 6
 
0.1%
정수처분 2
 
< 0.1%

자료등록일시
Date

Distinct1590
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-05-18 01:00:08
Maximum2022-05-18 01:34:23
2023-12-11T01:58:45.388053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:45.528282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T01:58:39.279086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:38.542183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:38.912524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:39.392350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:38.653057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:39.069937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:39.516945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:38.779582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:39.172414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:58:45.640488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번본관종류급수관종류계량기구경급수관연장검침코드명
연번1.0000.3730.4460.0700.0470.053
본관종류0.3731.0000.5760.1920.0300.000
급수관종류0.4460.5761.0000.6480.4360.087
계량기구경0.0700.1920.6481.0000.3590.135
급수관연장0.0470.0300.4360.3591.0000.000
검침코드명0.0530.0000.0870.1350.0001.000
2023-12-11T01:58:45.780412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수관종류본관종류검침코드명
급수관종류1.0000.3070.046
본관종류0.3071.0000.000
검침코드명0.0460.0001.000
2023-12-11T01:58:45.927158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번계량기구경급수관연장본관종류급수관종류검침코드명
연번1.000-0.0260.0360.1220.2210.027
계량기구경-0.0261.0000.2450.0980.4150.047
급수관연장0.0360.2451.0000.0150.2480.000
본관종류0.1220.0980.0151.0000.3070.000
급수관종류0.2210.4150.2480.3071.0000.046
검침코드명0.0270.0470.0000.0000.0461.000

Missing values

2023-12-11T01:58:39.756667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:58:39.999419image/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.
2023-12-11T01:58:40.225457image/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

연번고객번호본관종류본관구경급수관종류계량기구경급수관연장계량기설치일자검침일자검침코드명자료등록일시
380243802543**28PFP65*25PFP15202021-05-252022-03-31정상2022-05-18 01:31:43
179311793219**49닥타일주철관(시멘트)300닥타일주철관(시멘트)150152021-08-192022-04-30정상2022-05-18 01:20:09
519565195709**50스테인레스관13기타1502021-06-212022-03-31정상2022-05-18 01:33:37
231532315425**43스테인레스관200*50스테인레스관1512021-10-132022-03-31정상2022-05-18 01:25:18
639336393429**90스테인레스관25기타1502021-04-132022-03-31정상2022-05-18 01:34:14
449664496744**74닥타일주철관(시멘트)150PFP1582021-08-032022-03-31정상2022-05-18 01:32:30
517405174149**63스테인레스관25스테인레스관15192021-07-262022-03-31정상2022-05-18 01:33:40
2022202312**47PFP32스테인레스관1502021-12-062022-04-29정상2022-05-18 01:01:41
280932809426**85PFP80스테인레스관15192021-09-032022-05-02정상2022-05-18 01:26:41
284832848428**62닥타일주철관(시멘트)300닥타일주철관(시멘트)1502662021-06-152022-04-30정상2022-05-18 01:26:37
연번고객번호본관종류본관구경급수관종류계량기구경급수관연장계량기설치일자검침일자검침코드명자료등록일시
130761307712**91닥타일주철관(시멘트)100스테인레스관1512021-09-232022-03-31정상2022-05-18 01:14:12
101151011609**99PFP100*40스테인레스관1522021-06-222022-03-31정상2022-05-18 01:11:29
542585425950**15PFP80*25PFP1512021-07-292022-03-31정상2022-05-18 01:33:53
102771027811**84PFP40스테인레스관1512021-08-312022-03-31정상2022-05-18 01:11:17
545115451249**08PFP40PFP1582021-10-182022-04-30정상2022-05-18 01:33:52
560445604550**85PFP65PFP15122021-09-282022-04-30정상2022-05-18 01:33:48
408294083044**99PFP25PFP1552021-09-062022-04-30정상2022-05-18 01:32:12
682056820650**40PFP20PFP1502021-06-292022-04-01정상2022-05-18 01:34:17
301553015630**84에폭시라이닝관50스테인레스관1562021-07-222022-03-31정상2022-05-18 01:28:17
203282032922**96PFP100*50스테인레스관1512021-06-052022-03-31정상2022-05-18 01:22:26