Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells146
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_20230126
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15100349

Alerts

급수관종류 is highly imbalanced (65.9%)Imbalance
검침코드명 is highly imbalanced (68.7%)Imbalance
검침일자 has 118 (1.2%) missing valuesMissing
연번 has unique valuesUnique
급수관연장 has 2071 (20.7%) zerosZeros

Reproduction

Analysis started2023-12-10 16:58:27.862756
Analysis finished2023-12-10 16:58:29.970193
Duration2.11 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%
Mean22973.283
Minimum10
Maximum45839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:30.055698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile2411.85
Q111500
median23057.5
Q334302.25
95-th percentile43590.6
Maximum45839
Range45829
Interquartile range (IQR)22802.25

Descriptive statistics

Standard deviation13208.234
Coefficient of variation (CV)0.57493888
Kurtosis-1.1964021
Mean22973.283
Median Absolute Deviation (MAD)11358.5
Skewness0.00095627997
Sum2.2973283 × 108
Variance1.7445743 × 108
MonotonicityNot monotonic
2023-12-11T01:58:30.217355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34442 1
 
< 0.1%
2211 1
 
< 0.1%
32087 1
 
< 0.1%
31975 1
 
< 0.1%
1422 1
 
< 0.1%
40757 1
 
< 0.1%
24116 1
 
< 0.1%
15969 1
 
< 0.1%
5368 1
 
< 0.1%
35986 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
10 1
< 0.1%
11 1
< 0.1%
30 1
< 0.1%
36 1
< 0.1%
44 1
< 0.1%
54 1
< 0.1%
55 1
< 0.1%
59 1
< 0.1%
62 1
< 0.1%
63 1
< 0.1%
ValueCountFrequency (%)
45839 1
< 0.1%
45838 1
< 0.1%
45832 1
< 0.1%
45829 1
< 0.1%
45828 1
< 0.1%
45820 1
< 0.1%
45810 1
< 0.1%
45807 1
< 0.1%
45803 1
< 0.1%
45794 1
< 0.1%

고객번호
Text

Distinct5544
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T01:58:30.606429image/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

Unique3179 ?
Unique (%)31.8%

Sample

1st row*55*29
2nd row*98*93
3rd row*17*37
4th row*36*35
5th row*50*55
ValueCountFrequency (%)
94*26 18
 
0.2%
15*91 16
 
0.2%
52*54 16
 
0.2%
98*93 15
 
0.1%
02*58 15
 
0.1%
02*78 13
 
0.1%
28*78 13
 
0.1%
96*05 13
 
0.1%
80*96 13
 
0.1%
82*19 12
 
0.1%
Other values (5534) 9856
98.6%
2023-12-11T01:58:31.081371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 20000
33.3%
1 4539
 
7.6%
0 4482
 
7.5%
9 4343
 
7.2%
8 4057
 
6.8%
2 4038
 
6.7%
3 3944
 
6.6%
5 3911
 
6.5%
7 3717
 
6.2%
4 3681
 
6.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4539
11.3%
0 4482
11.2%
9 4343
10.9%
8 4057
10.1%
2 4038
10.1%
3 3944
9.9%
5 3911
9.8%
7 3717
9.3%
4 3681
9.2%
6 3288
8.2%
Other Punctuation
ValueCountFrequency (%)
* 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 20000
33.3%
1 4539
 
7.6%
0 4482
 
7.5%
9 4343
 
7.2%
8 4057
 
6.8%
2 4038
 
6.7%
3 3944
 
6.6%
5 3911
 
6.5%
7 3717
 
6.2%
4 3681
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 20000
33.3%
1 4539
 
7.6%
0 4482
 
7.5%
9 4343
 
7.2%
8 4057
 
6.8%
2 4038
 
6.7%
3 3944
 
6.6%
5 3911
 
6.5%
7 3717
 
6.2%
4 3681
 
6.1%

본관종류
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
스테인레스관
3520 
PFP
3433 
닥타일주철관(시멘트)
2325 
에폭시라이닝관
 
274
기타
 
209
Other values (8)
 
239

Length

Max length11
Median length7
Mean length6.1612
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
스테인레스관 3520
35.2%
PFP 3433
34.3%
닥타일주철관(시멘트) 2325
23.2%
에폭시라이닝관 274
 
2.7%
기타 209
 
2.1%
닥타일주철관(에폭시) 190
 
1.9%
<NA> 24
 
0.2%
회주철 9
 
0.1%
HI-3P 6
 
0.1%
PE관 4
 
< 0.1%
Other values (3) 6
 
0.1%

Length

2023-12-11T01:58:31.258716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
스테인레스관 3520
35.2%
pfp 3433
34.3%
닥타일주철관(시멘트 2325
23.2%
에폭시라이닝관 274
 
2.7%
기타 209
 
2.1%
닥타일주철관(에폭시 190
 
1.9%
na 24
 
0.2%
회주철 9
 
0.1%
hi-3p 6
 
0.1%
pe관 4
 
< 0.1%
Other values (3) 6
 
0.1%

본관구경
Text

Distinct379
Distinct (%)3.8%
Missing18
Missing (%)0.2%
Memory size156.2 KiB
2023-12-11T01:58:31.566164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length3.7407333
Min length2

Characters and Unicode

Total characters37340
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)1.7%

Sample

1st row200
2nd row150*50*32
3rd row40
4th row150
5th row150*80
ValueCountFrequency (%)
100 1153
 
11.6%
25 1020
 
10.2%
40 724
 
7.3%
50 569
 
5.7%
150 536
 
5.4%
20 505
 
5.1%
65 425
 
4.3%
15 384
 
3.8%
200 354
 
3.5%
13 324
 
3.2%
Other values (369) 3988
40.0%
2023-12-11T01:58:32.028659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12724
34.1%
5 6670
17.9%
1 5140
13.8%
* 4160
 
11.1%
2 4069
 
10.9%
4 1785
 
4.8%
3 1254
 
3.4%
6 1229
 
3.3%
8 295
 
0.8%
7 5
 
< 0.1%
Other values (5) 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33172
88.8%
Other Punctuation 4162
 
11.1%
Dash Punctuation 4
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12724
38.4%
5 6670
20.1%
1 5140
15.5%
2 4069
 
12.3%
4 1785
 
5.4%
3 1254
 
3.8%
6 1229
 
3.7%
8 295
 
0.9%
7 5
 
< 0.1%
9 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
* 4160
> 99.9%
. 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12724
34.1%
5 6670
17.9%
1 5140
13.8%
* 4160
 
11.1%
2 4069
 
10.9%
4 1785
 
4.8%
3 1254
 
3.4%
6 1229
 
3.3%
8 295
 
0.8%
7 5
 
< 0.1%
Other values (5) 9
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12724
34.1%
5 6670
17.9%
1 5140
13.8%
* 4160
 
11.1%
2 4069
 
10.9%
4 1785
 
4.8%
3 1254
 
3.4%
6 1229
 
3.3%
8 295
 
0.8%
7 5
 
< 0.1%
Other values (5) 9
 
< 0.1%

급수관종류
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
스테인레스관
7378 
PFP
1465 
기타
1014 
닥타일주철관(시멘트)
 
71
닥타일주철관(에폭시)
 
35
Other values (6)
 
37

Length

Max length15
Median length6
Mean length5.2067
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
스테인레스관 7378
73.8%
PFP 1465
 
14.6%
기타 1014
 
10.1%
닥타일주철관(시멘트) 71
 
0.7%
닥타일주철관(에폭시) 35
 
0.4%
<NA> 18
 
0.2%
에폭시라이닝관 12
 
0.1%
아연도강관 3
 
< 0.1%
이중보온스테인레스관(sts) 2
 
< 0.1%
CPVC 1
 
< 0.1%

Length

2023-12-11T01:58:32.181186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
스테인레스관 7378
73.8%
pfp 1465
 
14.6%
기타 1014
 
10.1%
닥타일주철관(시멘트 71
 
0.7%
닥타일주철관(에폭시 35
 
0.4%
na 18
 
0.2%
에폭시라이닝관 12
 
0.1%
아연도강관 3
 
< 0.1%
이중보온스테인레스관(sts 2
 
< 0.1%
cpvc 1
 
< 0.1%

계량기구경
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean17.872274
Minimum15
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:32.278219image/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 deviation11.778846
Coefficient of variation (CV)0.65905691
Kurtosis111.43701
Mean17.872274
Median Absolute Deviation (MAD)0
Skewness8.866875
Sum178687
Variance138.74121
MonotonicityNot monotonic
2023-12-11T01:58:32.379471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
15 8342
83.4%
20 617
 
6.2%
25 565
 
5.7%
40 185
 
1.8%
50 122
 
1.2%
32 61
 
0.6%
80 43
 
0.4%
100 34
 
0.3%
150 22
 
0.2%
200 6
 
0.1%
(Missing) 2
 
< 0.1%
ValueCountFrequency (%)
15 8342
83.4%
20 617
 
6.2%
25 565
 
5.7%
32 61
 
0.6%
40 185
 
1.8%
50 122
 
1.2%
80 43
 
0.4%
100 34
 
0.3%
150 22
 
0.2%
200 6
 
0.1%
ValueCountFrequency (%)
300 1
 
< 0.1%
200 6
 
0.1%
150 22
 
0.2%
100 34
 
0.3%
80 43
 
0.4%
50 122
 
1.2%
40 185
 
1.8%
32 61
 
0.6%
25 565
5.7%
20 617
6.2%

급수관연장
Real number (ℝ)

ZEROS 

Distinct66
Distinct (%)0.7%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.4190352
Minimum0
Maximum350
Zeros2071
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:58:32.499660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q34
95-th percentile12
Maximum350
Range350
Interquartile range (IQR)3

Descriptive statistics

Standard deviation7.6032018
Coefficient of variation (CV)2.2237857
Kurtosis623.42425
Mean3.4190352
Median Absolute Deviation (MAD)1
Skewness18.101032
Sum34163
Variance57.808678
MonotonicityNot monotonic
2023-12-11T01:58:32.625062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3732
37.3%
0 2071
20.7%
4 618
 
6.2%
3 596
 
6.0%
2 569
 
5.7%
6 533
 
5.3%
5 473
 
4.7%
8 256
 
2.6%
7 251
 
2.5%
10 154
 
1.5%
Other values (56) 739
 
7.4%
ValueCountFrequency (%)
0 2071
20.7%
1 3732
37.3%
2 569
 
5.7%
3 596
 
6.0%
4 618
 
6.2%
5 473
 
4.7%
6 533
 
5.3%
7 251
 
2.5%
8 256
 
2.6%
9 118
 
1.2%
ValueCountFrequency (%)
350 1
< 0.1%
260 1
< 0.1%
164 1
< 0.1%
148 1
< 0.1%
130 1
< 0.1%
105 2
< 0.1%
96 1
< 0.1%
95 1
< 0.1%
94 1
< 0.1%
85 1
< 0.1%

계량기설치일자
Date

Distinct330
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-03 00:00:00
Maximum2022-12-30 00:00:00
2023-12-11T01:58:32.745751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:32.853777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검침일자
Date

MISSING 

Distinct142
Distinct (%)1.4%
Missing118
Missing (%)1.2%
Memory size156.2 KiB
Minimum2013-08-03 00:00:00
Maximum2023-01-17 00:00:00
2023-12-11T01:58:32.958087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:33.063119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검침코드명
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상
8037 
계량기교체
1303 
전화검침
 
240
급수중지
 
192
<NA>
 
118
Other values (5)
 
110

Length

Max length5
Median length2
Mean length2.5229
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 8037
80.4%
계량기교체 1303
 
13.0%
전화검침 240
 
2.4%
급수중지 192
 
1.9%
<NA> 118
 
1.2%
이사정산 53
 
0.5%
자가검침 30
 
0.3%
정수처분 23
 
0.2%
인터넷 2
 
< 0.1%
ARS검침 2
 
< 0.1%

Length

2023-12-11T01:58:33.167003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:58:33.263574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 8037
80.4%
계량기교체 1303
 
13.0%
전화검침 240
 
2.4%
급수중지 192
 
1.9%
na 118
 
1.2%
이사정산 53
 
0.5%
자가검침 30
 
0.3%
정수처분 23
 
0.2%
인터넷 2
 
< 0.1%
ars검침 2
 
< 0.1%

자료등록일시
Date

Distinct1567
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-18 01:00:10
Maximum2023-01-18 01:31:17
2023-12-11T01:58:33.376871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:33.698307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T01:58:29.174335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:28.655559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:28.912800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:29.278143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:28.733752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:28.996299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:29.377217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:28.818007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:58:29.083151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:58:33.775801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번본관종류급수관종류계량기구경급수관연장검침코드명
연번1.0000.2690.5400.0470.0380.210
본관종류0.2691.0000.7850.2750.0650.080
급수관종류0.5400.7851.0000.7070.2220.163
계량기구경0.0470.2750.7071.0000.2340.276
급수관연장0.0380.0650.2220.2341.0000.000
검침코드명0.2100.0800.1630.2760.0001.000
2023-12-11T01:58:33.859907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수관종류본관종류검침코드명
급수관종류1.0000.4790.074
본관종류0.4791.0000.034
검침코드명0.0740.0341.000
2023-12-11T01:58:33.931404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번계량기구경급수관연장본관종류급수관종류검침코드명
연번1.0000.051-0.0870.1160.1920.097
계량기구경0.0511.0000.3020.1110.4710.141
급수관연장-0.0870.3021.0000.0320.1080.000
본관종류0.1160.1110.0321.0000.4790.034
급수관종류0.1920.4710.1080.4791.0000.074
검침코드명0.0970.1410.0000.0340.0741.000

Missing values

2023-12-11T01:58:29.523343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:58:29.718896image/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.
2023-12-11T01:58:29.863641image/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
3444134442*55*29닥타일주철관(시멘트)200PFP1542022-12-272022-10-27정상2023-01-18 01:29:53
3996339964*98*93PFP150*50*32기타1502022-09-162022-11-29정상2023-01-18 01:30:50
4419244193*17*37PFP40PFP1572022-04-242022-12-30정상2023-01-18 01:31:10
2205122052*36*35닥타일주철관(시멘트)150스테인레스관1572022-12-262022-12-31급수중지2023-01-18 01:21:57
52825283*50*55닥타일주철관(시멘트)150*80PFP5052022-02-152023-01-05정상2023-01-18 01:05:33
4504145042*46*45PFP40스테인레스관1502022-05-182022-12-05정상2023-01-18 01:31:14
2648226483*07*13닥타일주철관(시멘트)200스테인레스관1552022-02-152022-11-29정상2023-01-18 01:25:41
26472648*16*43PFP300*25스테인레스관2522022-04-122022-12-28정상2023-01-18 01:03:07
3262332624*13*89닥타일주철관(시멘트)200PFP4062022-10-192023-01-02전화검침2023-01-18 01:29:05
2832728328*25*72닥타일주철관(시멘트)100PFP1522022-02-102022-11-29정상2023-01-18 01:26:25
연번고객번호본관종류본관구경급수관종류계량기구경급수관연장계량기설치일자검침일자검침코드명자료등록일시
2974629747*96*69닥타일주철관(시멘트)100PFP1562022-12-072022-12-30계량기교체2023-01-18 01:27:11
40324033*36*30스테인레스관20스테인레스관1512022-11-052023-01-01계량기교체2023-01-18 01:04:52
3145731458*37*30PFP100PFP20122022-04-252022-12-30정상2023-01-18 01:28:38
1318913190*61*76PFP65스테인레스관1512022-11-102023-01-02계량기교체2023-01-18 01:14:02
3055230553*21*88스테인레스관20기타1502022-07-192022-12-29정상2023-01-18 01:28:16
2669326694*24*60PFP150*65*25PFP1532022-08-222022-11-29정상2023-01-18 01:26:39
46194620*59*99에폭시라이닝관200*50스테인레스관1522022-11-042023-01-02계량기교체2023-01-18 01:04:34
4113641137*06*98스테인레스관20스테인레스관2022022-01-122022-11-29정상2023-01-18 01:30:57
3729537296*31*46PFP40기타1502022-08-242022-12-06정상2023-01-18 01:30:31
2639726398*98*60PFP40스테인레스관1532022-05-262022-11-29정상2023-01-18 01:25:39