Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells6
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory70.8 B

Variable types

Text2
Numeric4
Categorical2

Dataset

Description김해시 배수펌프장 현황에 대한 자료로 시설명, 위치, 관개면적, 단위용수량, 준공년도 등에 대한 데이터로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033800/fileData.do

Alerts

관개면적(ha) is highly overall correlated with 단위용수량(세제곱미터퍼세컨드)High correlation
단위용수량(세제곱미터퍼세컨드) is highly overall correlated with 관개면적(ha)High correlation
관개면적(ha) has 6 (13.0%) missing valuesMissing
위치 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:35:21.315519
Analysis finished2024-03-14 11:35:26.386989
Duration5.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size496.0 B
2024-03-14T20:35:27.022936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length7.5
Min length6

Characters and Unicode

Total characters345
Distinct characters77
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

Unique44 ?
Unique (%)95.7%

Sample

1st row청천 배수장
2nd row효동 배수장
3rd row본산 양배수장
4th row용성 양배수장
5th row고모 배수장
ValueCountFrequency (%)
배수장 13
 
18.8%
전하배수펌프장 2
 
2.9%
양배수장 2
 
2.9%
지하차도 2
 
2.9%
화현배수펌프장 1
 
1.4%
진영동산배수펌프장 1
 
1.4%
농소배수펌프장 1
 
1.4%
사덕배수펌프장 1
 
1.4%
천곡1배수펌프장 1
 
1.4%
천곡2배수펌프장 1
 
1.4%
Other values (44) 44
63.8%
2024-03-14T20:35:28.296629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 45
 
13.0%
배 42
 
12.2%
수 42
 
12.2%
펌 27
 
7.8%
프 27
 
7.8%
23
 
6.7%
동 8
 
2.3%
하 6
 
1.7%
천 6
 
1.7%
곡 5
 
1.4%
Other values (67) 114
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
91.3%
Space Separator 23
 
6.7%
Decimal Number 7
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 45
14.3%
배 42
13.3%
수 42
13.3%
펌 27
 
8.6%
프 27
 
8.6%
동 8
 
2.5%
하 6
 
1.9%
천 6
 
1.9%
곡 5
 
1.6%
차 4
 
1.3%
Other values (63) 103
32.7%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
3 1
 
14.3%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 315
91.3%
Common 30
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 45
14.3%
배 42
13.3%
수 42
13.3%
펌 27
 
8.6%
프 27
 
8.6%
동 8
 
2.5%
하 6
 
1.9%
천 6
 
1.9%
곡 5
 
1.6%
차 4
 
1.3%
Other values (63) 103
32.7%
Common
ValueCountFrequency (%)
23
76.7%
2 4
 
13.3%
1 2
 
6.7%
3 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
91.3%
ASCII 30
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 45
14.3%
배 42
13.3%
수 42
13.3%
펌 27
 
8.6%
프 27
 
8.6%
동 8
 
2.5%
하 6
 
1.9%
천 6
 
1.9%
곡 5
 
1.6%
차 4
 
1.3%
Other values (63) 103
32.7%
ASCII
ValueCountFrequency (%)
23
76.7%
2 4
 
13.3%
1 2
 
6.7%
3 1
 
3.3%

위치
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size496.0 B
2024-03-14T20:35:29.304565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.369565
Min length16

Characters and Unicode

Total characters937
Distinct characters76
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

Unique46 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 진영읍 전리 144-9
2nd row경상남도 김해시 진영읍 설창리 289-5
3rd row경상남도 김해시 한림면 가산리 303-2
4th row경상남도 김해시 진영읍 본산리 622-2
5th row경상남도 김해시 진례면 담안리 245-1
ValueCountFrequency (%)
경상남도 45
21.7%
김해시 45
21.7%
상동면 8
 
3.9%
주촌면 7
 
3.4%
한림면 6
 
2.9%
진영읍 5
 
2.4%
천곡리 4
 
1.9%
삼정동 3
 
1.4%
감노리 3
 
1.4%
매리 3
 
1.4%
Other values (72) 78
37.7%
2024-03-14T20:35:30.752279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
161
17.2%
상 53
 
5.7%
도 46
 
4.9%
시 46
 
4.9%
경 45
 
4.8%
남 45
 
4.8%
김 45
 
4.8%
해 45
 
4.8%
1 42
 
4.5%
- 36
 
3.8%
Other values (66) 373
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 545
58.2%
Decimal Number 195
 
20.8%
Space Separator 161
 
17.2%
Dash Punctuation 36
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 53
 
9.7%
도 46
 
8.4%
시 46
 
8.4%
경 45
 
8.3%
남 45
 
8.3%
김 45
 
8.3%
해 45
 
8.3%
리 29
 
5.3%
동 26
 
4.8%
면 24
 
4.4%
Other values (54) 141
25.9%
Decimal Number
ValueCountFrequency (%)
1 42
21.5%
2 28
14.4%
6 26
13.3%
4 20
10.3%
5 18
9.2%
3 17
8.7%
9 14
 
7.2%
7 11
 
5.6%
8 10
 
5.1%
0 9
 
4.6%
Space Separator
ValueCountFrequency (%)
161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 545
58.2%
Common 392
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 53
 
9.7%
도 46
 
8.4%
시 46
 
8.4%
경 45
 
8.3%
남 45
 
8.3%
김 45
 
8.3%
해 45
 
8.3%
리 29
 
5.3%
동 26
 
4.8%
면 24
 
4.4%
Other values (54) 141
25.9%
Common
ValueCountFrequency (%)
161
41.1%
1 42
 
10.7%
- 36
 
9.2%
2 28
 
7.1%
6 26
 
6.6%
4 20
 
5.1%
5 18
 
4.6%
3 17
 
4.3%
9 14
 
3.6%
7 11
 
2.8%
Other values (2) 19
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 545
58.2%
ASCII 392
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
161
41.1%
1 42
 
10.7%
- 36
 
9.2%
2 28
 
7.1%
6 26
 
6.6%
4 20
 
5.1%
5 18
 
4.6%
3 17
 
4.3%
9 14
 
3.6%
7 11
 
2.8%
Other values (2) 19
 
4.8%
Hangul
ValueCountFrequency (%)
상 53
 
9.7%
도 46
 
8.4%
시 46
 
8.4%
경 45
 
8.3%
남 45
 
8.3%
김 45
 
8.3%
해 45
 
8.3%
리 29
 
5.3%
동 26
 
4.8%
면 24
 
4.4%
Other values (54) 141
25.9%

관개면적(ha)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)95.0%
Missing6
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean44.4095
Minimum0.3
Maximum364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 B
2024-03-14T20:35:31.143936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile1.4035
Q110.525
median19.2
Q337
95-th percentile182.9
Maximum364
Range363.7
Interquartile range (IQR)26.475

Descriptive statistics

Standard deviation70.014517
Coefficient of variation (CV)1.5765662
Kurtosis11.165055
Mean44.4095
Median Absolute Deviation (MAD)14.75
Skewness3.1160002
Sum1776.38
Variance4902.0326
MonotonicityNot monotonic
2024-03-14T20:35:31.558970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
15.0 3
 
6.5%
12.0 1
 
2.2%
2.1 1
 
2.2%
0.3 1
 
2.2%
47.0 1
 
2.2%
20.0 1
 
2.2%
5.0 1
 
2.2%
34.0 1
 
2.2%
5.1 1
 
2.2%
29.0 1
 
2.2%
Other values (28) 28
60.9%
(Missing) 6
 
13.0%
ValueCountFrequency (%)
0.3 1
2.2%
0.9 1
2.2%
1.43 1
2.2%
2.1 1
2.2%
2.2 1
2.2%
4.5 1
2.2%
5.0 1
2.2%
5.1 1
2.2%
6.5 1
2.2%
10.0 1
2.2%
ValueCountFrequency (%)
364.0 1
2.2%
200.0 1
2.2%
182.0 1
2.2%
155.0 1
2.2%
103.7 1
2.2%
80.0 1
2.2%
63.0 1
2.2%
62.0 1
2.2%
47.0 1
2.2%
40.0 1
2.2%

단위용수량(세제곱미터퍼세컨드)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2402174
Minimum0.04
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 B
2024-03-14T20:35:31.973576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.19
Q10.7575
median1.65
Q32.8925
95-th percentile13.665
Maximum22
Range21.96
Interquartile range (IQR)2.135

Descriptive statistics

Standard deviation4.7936011
Coefficient of variation (CV)1.4794072
Kurtosis7.6025005
Mean3.2402174
Median Absolute Deviation (MAD)1.14
Skewness2.7522412
Sum149.05
Variance22.978611
MonotonicityNot monotonic
2024-03-14T20:35:32.583805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.5 2
 
4.3%
6.0 2
 
4.3%
3.0 2
 
4.3%
0.33 2
 
4.3%
1.0 2
 
4.3%
0.08 1
 
2.2%
0.89 1
 
2.2%
0.87 1
 
2.2%
1.6 1
 
2.2%
2.78 1
 
2.2%
Other values (31) 31
67.4%
ValueCountFrequency (%)
0.04 1
2.2%
0.08 1
2.2%
0.16 1
2.2%
0.28 1
2.2%
0.33 2
4.3%
0.38 1
2.2%
0.39 1
2.2%
0.5 2
4.3%
0.65 1
2.2%
0.75 1
2.2%
ValueCountFrequency (%)
22.0 1
2.2%
20.0 1
2.2%
14.33 1
2.2%
11.67 1
2.2%
8.33 1
2.2%
6.0 2
4.3%
5.6 1
2.2%
3.67 1
2.2%
3.0 2
4.3%
2.9 1
2.2%

준공년도(재준공년도)
Categorical

Distinct22
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size496.0 B
2012
10 
2018
4 
2021
4 
2002
3 
2010
3 
Other values (17)
22 

Length

Max length10
Median length4
Mean length4.5217391
Min length4

Unique

Unique12 ?
Unique (%)26.1%

Sample

1st row2003
2nd row1984
3rd row1993
4th row2000
5th row2017

Common Values

ValueCountFrequency (%)
2012 10
21.7%
2018 4
 
8.7%
2021 4
 
8.7%
2002 3
 
6.5%
2010 3
 
6.5%
1993 2
 
4.3%
2000 2
 
4.3%
2015 2
 
4.3%
2006 2
 
4.3%
2009 2
 
4.3%
Other values (12) 12
26.1%

Length

2024-03-14T20:35:32.993044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2012 10
21.7%
2021 4
 
8.7%
2018 4
 
8.7%
2002 3
 
6.5%
2010 3
 
6.5%
1993 2
 
4.3%
2000 2
 
4.3%
2015 2
 
4.3%
2006 2
 
4.3%
2009 2
 
4.3%
Other values (12) 12
26.1%

관리부서
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size496.0 B
김해시 하수과
26 
김해시 건설과
14 
김해시 도로과
6 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row김해시 건설과
2nd row김해시 건설과
3rd row김해시 건설과
4th row김해시 건설과
5th row김해시 건설과

Common Values

ValueCountFrequency (%)
김해시 하수과 26
56.5%
김해시 건설과 14
30.4%
김해시 도로과 6
 
13.0%

Length

2024-03-14T20:35:33.364161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:35:33.667223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해시 46
50.0%
하수과 26
28.3%
건설과 14
 
15.2%
도로과 6
 
6.5%

위도
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.269385
Minimum35.19957
Maximum35.386677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 B
2024-03-14T20:35:34.012707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.19957
5-th percentile35.202536
Q135.223809
median35.2395
Q335.31815
95-th percentile35.350554
Maximum35.386677
Range0.18710683
Interquartile range (IQR)0.09434034

Descriptive statistics

Standard deviation0.053727077
Coefficient of variation (CV)0.0015233347
Kurtosis-1.2927122
Mean35.269385
Median Absolute Deviation (MAD)0.03774425
Skewness0.39214484
Sum1622.3917
Variance0.0028865988
MonotonicityNot monotonic
2024-03-14T20:35:34.463805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
35.29844174 1
 
2.2%
35.35081214 1
 
2.2%
35.31451926 1
 
2.2%
35.28494329 1
 
2.2%
35.21623204 1
 
2.2%
35.21029114 1
 
2.2%
35.23764264 1
 
2.2%
35.23479851 1
 
2.2%
35.23298993 1
 
2.2%
35.31508591 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
35.19957 1
2.2%
35.19983079 1
2.2%
35.19995145 1
2.2%
35.21029114 1
2.2%
35.2138008 1
2.2%
35.21623204 1
2.2%
35.21660932 1
2.2%
35.22015309 1
2.2%
35.22021029 1
2.2%
35.22078997 1
2.2%
ValueCountFrequency (%)
35.38667683 1
2.2%
35.36119096 1
2.2%
35.35081214 1
2.2%
35.34977783 1
2.2%
35.3460077 1
2.2%
35.33652374 1
2.2%
35.32929999 1
2.2%
35.3208428 1
2.2%
35.31988957 1
2.2%
35.31848973 1
2.2%

경도
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.85193
Minimum128.71297
Maximum128.99359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 B
2024-03-14T20:35:34.884613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.71297
5-th percentile128.74025
Q1128.80503
median128.84692
Q3128.90351
95-th percentile128.95354
Maximum128.99359
Range0.2806239
Interquartile range (IQR)0.09847975

Descriptive statistics

Standard deviation0.06829224
Coefficient of variation (CV)0.00053000555
Kurtosis-0.6906093
Mean128.85193
Median Absolute Deviation (MAD)0.050269
Skewness-0.059776449
Sum5927.1889
Variance0.00466383
MonotonicityNot monotonic
2024-03-14T20:35:35.320985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
128.7392014 1
 
2.2%
128.9213794 1
 
2.2%
128.7353339 1
 
2.2%
128.7129693 1
 
2.2%
128.8310159 1
 
2.2%
128.8284841 1
 
2.2%
128.8306853 1
 
2.2%
128.8313703 1
 
2.2%
128.8322088 1
 
2.2%
128.797969 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
128.7129693 1
2.2%
128.7353339 1
2.2%
128.7392014 1
2.2%
128.7433869 1
2.2%
128.750328 1
2.2%
128.7626559 1
2.2%
128.76778 1
2.2%
128.7739442 1
2.2%
128.797969 1
2.2%
128.8025665 1
2.2%
ValueCountFrequency (%)
128.9935932 1
2.2%
128.961357 1
2.2%
128.9552508 1
2.2%
128.9483951 1
2.2%
128.9405374 1
2.2%
128.9391251 1
2.2%
128.9272765 1
2.2%
128.9264886 1
2.2%
128.9225459 1
2.2%
128.9213794 1
2.2%

Interactions

2024-03-14T20:35:24.657120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:21.802328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:22.831345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:23.827856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:24.920578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:22.060748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:23.080817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:23.988836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:25.166870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:22.305531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:23.310862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:24.137399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:25.430396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:22.589424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:23.565242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:24.393853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:35:35.597891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명위치관개면적(ha)단위용수량(세제곱미터퍼세컨드)준공년도(재준공년도)관리부서위도경도
시설명1.0001.0000.9021.0000.9951.0000.9830.953
위치1.0001.0001.0001.0001.0001.0001.0001.000
관개면적(ha)0.9021.0001.0000.7190.3550.0000.0000.525
단위용수량(세제곱미터퍼세컨드)1.0001.0000.7191.0000.0000.0000.0000.635
준공년도(재준공년도)0.9951.0000.3550.0001.0000.6680.8500.826
관리부서1.0001.0000.0000.0000.6681.0000.5910.404
위도0.9831.0000.0000.0000.8500.5911.0000.642
경도0.9531.0000.5250.6350.8260.4040.6421.000
2024-03-14T20:35:35.791889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리부서준공년도(재준공년도)
관리부서1.0000.328
준공년도(재준공년도)0.3281.000
2024-03-14T20:35:35.938735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관개면적(ha)단위용수량(세제곱미터퍼세컨드)위도경도준공년도(재준공년도)관리부서
관개면적(ha)1.0000.6460.1160.4030.0380.000
단위용수량(세제곱미터퍼세컨드)0.6461.0000.0150.2780.0000.000
위도0.1160.0151.000-0.0480.4180.393
경도0.4030.278-0.0481.0000.3980.235
준공년도(재준공년도)0.0380.0000.4180.3981.0000.328
관리부서0.0000.0000.3930.2350.3281.000

Missing values

2024-03-14T20:35:25.785612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:35:26.219954image/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

시설명위치관개면적(ha)단위용수량(세제곱미터퍼세컨드)준공년도(재준공년도)관리부서위도경도
0청천 배수장경상남도 김해시 진영읍 전리 144-915.02.562003김해시 건설과35.298442128.739201
1효동 배수장경상남도 김해시 진영읍 설창리 289-515.01.081984김해시 건설과35.302875128.773944
2본산 양배수장경상남도 김해시 한림면 가산리 303-236.01.71993김해시 건설과35.3293128.750328
3용성 양배수장경상남도 김해시 진영읍 본산리 622-212.00.782000김해시 건설과35.320843128.743387
4고모 배수장경상남도 김해시 진례면 담안리 245-124.02.22017김해시 건설과35.26471128.762656
5모정 배수장경상남도 김해시 한림면 금곡리 971-122.22.161993김해시 건설과35.349778128.807838
6양지 배수장경상남도 김해시 생림면 도요리 590-210.72.41998(2008)김해시 건설과35.386677128.845201
7매리 배수장경상남도 김해시 상동면 매리 123422.01.41997(2012)김해시 건설과35.31782128.955251
8대감 배수장경상남도 김해시 상동면 매리 산86-330.03.671976김해시 건설과35.318397128.948395
9새들재 배수장경상남도 김해시 상동면 매리 124614.01.82000(2012)김해시 건설과35.31989128.961357
시설명위치관개면적(ha)단위용수량(세제곱미터퍼세컨드)준공년도(재준공년도)관리부서위도경도
36신곡배수펌프장경상남도 김해시 상동면 감노리 231-30155.02.872002김해시 하수과35.346008128.927277
37화현배수펌프장경상남도 김해시 상동면 감노리 68462.00.52002김해시 하수과35.336524128.939125
38안막배수펌프장부산광역시 강서구 대저1동 670-23335.58.332021김해시 하수과35.231951128.993593
39능동교배수펌프장경상남도 김해시 부곡동 1167-11.430.332022김해시 하수과35.19957128.8041
40불암동 지하차도경상남도 김해시 불암동221-2<NA>0.652010김해시 도로과35.220153128.926489
41동김해 지하차도경상남도 김해시 삼정동169-1<NA>0.282009김해시 도로과35.228349128.904754
42장유 무계지하차도경상남도 김해시 무계동391-16<NA>0.92000김해시 도로과35.199831128.811806
43진례 테크노벨리 배수장경상남도 김해시 진례면 고모리1304-6<NA>0.752018김해시 도로과35.27544128.76778
44한림 장방배수장경상남도 김해시 한림면 장방리1253-60<NA>0.392004김해시 도로과35.31849128.802567
45주촌 천곡 맨홀 펌프장경상남도 김해시 주촌면 천곡리119-19번지<NA>0.042012김해시 도로과35.241357128.829284