Overview

Dataset statistics

Number of variables12
Number of observations151
Missing cells309
Missing cells (%)17.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory99.9 B

Variable types

Numeric2
Text2
Categorical7
Unsupported1

Dataset

Description부산광역시_먹는물공동시설(약수터)수질검사결과정보_20210331
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15083355

Alerts

미검사사유 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
일반세균 중온 CFU/mL is highly overall correlated with 검사여부 and 2 other fieldsHigh correlation
검사여부 is highly overall correlated with 과망간산칼륨소비량 ㎎/L and 6 other fieldsHigh correlation
검사일자 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
검사결과 is highly overall correlated with 검사여부 and 2 other fieldsHigh correlation
분원성대장균군 mL is highly overall correlated with 검사여부 and 1 other fieldsHigh correlation
암모니아성 질소 ㎎/L is highly overall correlated with 번호 and 6 other fieldsHigh correlation
번호 is highly overall correlated with 미검사사유 and 2 other fieldsHigh correlation
과망간산칼륨소비량 ㎎/L is highly overall correlated with 검사여부 and 1 other fieldsHigh correlation
총대장균군 mL has 151 (100.0%) missing valuesMissing
질산성 질소㎎/L has 79 (52.3%) missing valuesMissing
과망간산칼륨소비량 ㎎/L has 79 (52.3%) missing valuesMissing
번호 has unique valuesUnique
공동시설명 has unique valuesUnique
총대장균군 mL is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 13:15:02.304859
Analysis finished2024-03-13 13:15:03.919909
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T22:15:04.022561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.5
Q138.5
median76
Q3113.5
95-th percentile143.5
Maximum151
Range150
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.734045
Coefficient of variation (CV)0.57544796
Kurtosis-1.2
Mean76
Median Absolute Deviation (MAD)38
Skewness0
Sum11476
Variance1912.6667
MonotonicityStrictly increasing
2024-03-13T22:15:04.200879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
105 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
106 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%

공동시설명
Text

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-13T22:15:04.624114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1721854
Min length5

Characters and Unicode

Total characters1083
Distinct characters163
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

Unique151 ?
Unique (%)100.0%

Sample

1st row금정구 수박골
2nd row금정구 삼밭골
3rd row금정구 호국사
4th row금정구 참샘골
5th row금정구 정암
ValueCountFrequency (%)
부산진구 24
 
7.9%
사상구 18
 
5.9%
사하구 15
 
4.9%
금정구 15
 
4.9%
북구 13
 
4.3%
남구 12
 
3.9%
영도구 10
 
3.3%
동래구 10
 
3.3%
해운대구 10
 
3.3%
서구 7
 
2.3%
Other values (151) 170
55.9%
2024-03-13T22:15:05.173924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153
 
14.1%
구 151
 
13.9%
산 45
 
4.2%
사 44
 
4.1%
정 36
 
3.3%
수 26
 
2.4%
부 26
 
2.4%
진 24
 
2.2%
동 23
 
2.1%
금 22
 
2.0%
Other values (153) 533
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 909
83.9%
Space Separator 153
 
14.1%
Open Punctuation 8
 
0.7%
Close Punctuation 8
 
0.7%
Decimal Number 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 151
 
16.6%
산 45
 
5.0%
사 44
 
4.8%
정 36
 
4.0%
수 26
 
2.9%
부 26
 
2.9%
진 24
 
2.6%
동 23
 
2.5%
금 22
 
2.4%
상 19
 
2.1%
Other values (147) 493
54.2%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 909
83.9%
Common 174
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 151
 
16.6%
산 45
 
5.0%
사 44
 
4.8%
정 36
 
4.0%
수 26
 
2.9%
부 26
 
2.9%
진 24
 
2.6%
동 23
 
2.5%
금 22
 
2.4%
상 19
 
2.1%
Other values (147) 493
54.2%
Common
ValueCountFrequency (%)
153
87.9%
( 8
 
4.6%
) 8
 
4.6%
1 2
 
1.1%
2 2
 
1.1%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 909
83.9%
ASCII 174
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
153
87.9%
( 8
 
4.6%
) 8
 
4.6%
1 2
 
1.1%
2 2
 
1.1%
4 1
 
0.6%
Hangul
ValueCountFrequency (%)
구 151
 
16.6%
산 45
 
5.0%
사 44
 
4.8%
정 36
 
4.0%
수 26
 
2.9%
부 26
 
2.9%
진 24
 
2.6%
동 23
 
2.5%
금 22
 
2.4%
상 19
 
2.1%
Other values (147) 493
54.2%

검사여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
검사
77 
미검사
74 

Length

Max length3
Median length2
Mean length2.4900662
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row검사
2nd row미검사
3rd row미검사
4th row검사
5th row검사

Common Values

ValueCountFrequency (%)
검사 77
51.0%
미검사 74
49.0%

Length

2024-03-13T22:15:05.316827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:05.414078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사 77
51.0%
미검사 74
49.0%

미검사사유
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
77 
안심등급
70 
수원고갈
 
4

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row안심등급
3rd row안심등급
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 77
51.0%
안심등급 70
46.4%
수원고갈 4
 
2.6%

Length

2024-03-13T22:15:05.515599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:05.971263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 77
51.0%
안심등급 70
46.4%
수원고갈 4
 
2.6%

검사일자
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
74 
2021-02-03
12 
2021-02-22
10 
2021-02-24
8 
2021-02-25
 
7
Other values (10)
40 

Length

Max length10
Median length10
Mean length7.0596026
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-03
2nd row<NA>
3rd row<NA>
4th row2021-03-03
5th row2021-03-04

Common Values

ValueCountFrequency (%)
<NA> 74
49.0%
2021-02-03 12
 
7.9%
2021-02-22 10
 
6.6%
2021-02-24 8
 
5.3%
2021-02-25 7
 
4.6%
2021-02-08 6
 
4.0%
2021-02-19 6
 
4.0%
2021-03-03 5
 
3.3%
2021-02-04 5
 
3.3%
2021-03-18 5
 
3.3%
Other values (5) 13
 
8.6%

Length

2024-03-13T22:15:06.146029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 74
49.0%
2021-02-03 12
 
7.9%
2021-02-22 10
 
6.6%
2021-02-24 8
 
5.3%
2021-02-25 7
 
4.6%
2021-02-08 6
 
4.0%
2021-02-19 6
 
4.0%
2021-03-03 5
 
3.3%
2021-02-04 5
 
3.3%
2021-03-18 5
 
3.3%
Other values (5) 13
 
8.6%

검사결과
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
74 
적합
59 
부적합
18 

Length

Max length4
Median length3
Mean length3.0993377
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row<NA>
3rd row<NA>
4th row적합
5th row적합

Common Values

ValueCountFrequency (%)
<NA> 74
49.0%
적합 59
39.1%
부적합 18
 
11.9%

Length

2024-03-13T22:15:06.319039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:06.458987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
49.0%
적합 59
39.1%
부적합 18
 
11.9%

일반세균 중온 CFU/mL
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
74 
불검출
59 
검출
18 

Length

Max length4
Median length3
Mean length3.3708609
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불검출
2nd row<NA>
3rd row<NA>
4th row불검출
5th row불검출

Common Values

ValueCountFrequency (%)
<NA> 74
49.0%
불검출 59
39.1%
검출 18
 
11.9%

Length

2024-03-13T22:15:06.610010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:06.757989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
49.0%
불검출 59
39.1%
검출 18
 
11.9%

총대장균군 mL
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

분원성대장균군 mL
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
불검출
76 
<NA>
74 
검출
 
1

Length

Max length4
Median length3
Mean length3.4834437
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row불검출
2nd row<NA>
3rd row<NA>
4th row불검출
5th row불검출

Common Values

ValueCountFrequency (%)
불검출 76
50.3%
<NA> 74
49.0%
검출 1
 
0.7%

Length

2024-03-13T22:15:06.950659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:07.086820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불검출 76
50.3%
na 74
49.0%
검출 1
 
0.7%

암모니아성 질소 ㎎/L
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
79 
불검출
72 

Length

Max length4
Median length4
Mean length3.5231788
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불검출
2nd row<NA>
3rd row<NA>
4th row불검출
5th row불검출

Common Values

ValueCountFrequency (%)
<NA> 79
52.3%
불검출 72
47.7%

Length

2024-03-13T22:15:07.211352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:07.329589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 79
52.3%
불검출 72
47.7%

질산성 질소㎎/L
Text

MISSING 

Distinct40
Distinct (%)55.6%
Missing79
Missing (%)52.3%
Memory size1.3 KiB
2024-03-13T22:15:07.523146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7361111
Min length1

Characters and Unicode

Total characters197
Distinct characters14
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

Unique22 ?
Unique (%)30.6%

Sample

1st row1.5
2nd row2.5
3rd row1.9
4th row2.1
5th row1
ValueCountFrequency (%)
1.5 6
 
8.3%
2.3 5
 
6.9%
2 4
 
5.6%
1.1 4
 
5.6%
0.9 3
 
4.2%
1.6 3
 
4.2%
1.9 3
 
4.2%
3.9 2
 
2.8%
1.4 2
 
2.8%
1 2
 
2.8%
Other values (30) 38
52.8%
2024-03-13T22:15:07.894105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 60
30.5%
1 32
16.2%
2 22
 
11.2%
3 16
 
8.1%
9 11
 
5.6%
6 10
 
5.1%
0 9
 
4.6%
5 8
 
4.1%
8 8
 
4.1%
4 8
 
4.1%
Other values (4) 13
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 131
66.5%
Other Punctuation 60
30.5%
Other Letter 6
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
24.4%
2 22
16.8%
3 16
12.2%
9 11
 
8.4%
6 10
 
7.6%
0 9
 
6.9%
5 8
 
6.1%
8 8
 
6.1%
4 8
 
6.1%
7 7
 
5.3%
Other Letter
ValueCountFrequency (%)
불 2
33.3%
검 2
33.3%
출 2
33.3%
Other Punctuation
ValueCountFrequency (%)
. 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191
97.0%
Hangul 6
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 60
31.4%
1 32
16.8%
2 22
 
11.5%
3 16
 
8.4%
9 11
 
5.8%
6 10
 
5.2%
0 9
 
4.7%
5 8
 
4.2%
8 8
 
4.2%
4 8
 
4.2%
Hangul
ValueCountFrequency (%)
불 2
33.3%
검 2
33.3%
출 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 191
97.0%
Hangul 6
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 60
31.4%
1 32
16.8%
2 22
 
11.5%
3 16
 
8.4%
9 11
 
5.8%
6 10
 
5.2%
0 9
 
4.7%
5 8
 
4.2%
8 8
 
4.2%
4 8
 
4.2%
Hangul
ValueCountFrequency (%)
불 2
33.3%
검 2
33.3%
출 2
33.3%

과망간산칼륨소비량 ㎎/L
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)9.7%
Missing79
Missing (%)52.3%
Infinite0
Infinite (%)0.0%
Mean0.62083333
Minimum0.3
Maximum7.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T22:15:08.049927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4
Q10.4
median0.5
Q30.6
95-th percentile0.6
Maximum7.5
Range7.2
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.86674679
Coefficient of variation (CV)1.3961022
Kurtosis58.195653
Mean0.62083333
Median Absolute Deviation (MAD)0.1
Skewness7.4347286
Sum44.7
Variance0.75125
MonotonicityNot monotonic
2024-03-13T22:15:08.163620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.5 27
 
17.9%
0.4 20
 
13.2%
0.6 19
 
12.6%
0.3 3
 
2.0%
0.7 1
 
0.7%
7.5 1
 
0.7%
2.7 1
 
0.7%
(Missing) 79
52.3%
ValueCountFrequency (%)
0.3 3
 
2.0%
0.4 20
13.2%
0.5 27
17.9%
0.6 19
12.6%
0.7 1
 
0.7%
2.7 1
 
0.7%
7.5 1
 
0.7%
ValueCountFrequency (%)
7.5 1
 
0.7%
2.7 1
 
0.7%
0.7 1
 
0.7%
0.6 19
12.6%
0.5 27
17.9%
0.4 20
13.2%
0.3 3
 
2.0%

Interactions

2024-03-13T22:15:03.156811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:02.914631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:03.250553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:03.029530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:15:08.271116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호검사여부미검사사유검사일자검사결과일반세균 중온 CFU/mL분원성대장균군 mL질산성 질소㎎/L과망간산칼륨소비량 ㎎/L
번호1.0000.4960.8880.9470.3500.3500.0000.0000.000
검사여부0.4961.000NaNNaNNaNNaNNaNNaNNaN
미검사사유0.888NaN1.000NaNNaNNaNNaNNaNNaN
검사일자0.947NaNNaN1.0000.5870.5870.0000.0000.000
검사결과0.350NaNNaN0.5871.0000.9980.0000.0000.000
일반세균 중온 CFU/mL0.350NaNNaN0.5870.9981.0000.0000.0000.000
분원성대장균군 mL0.000NaNNaN0.0000.0000.0001.0000.0000.000
질산성 질소㎎/L0.000NaNNaN0.0000.0000.0000.0001.0000.000
과망간산칼륨소비량 ㎎/L0.000NaNNaN0.0000.0000.0000.0000.0001.000
2024-03-13T22:15:08.430148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미검사사유일반세균 중온 CFU/mL검사여부검사일자검사결과분원성대장균군 mL암모니아성 질소 ㎎/L
미검사사유1.000NaN1.000NaNNaNNaNNaN
일반세균 중온 CFU/mLNaN1.0001.0000.4220.9630.0001.000
검사여부1.0001.0001.0001.0001.0001.0001.000
검사일자NaN0.4221.0001.0000.4220.0001.000
검사결과NaN0.9631.0000.4221.0000.0001.000
분원성대장균군 mLNaN0.0001.0000.0000.0001.0001.000
암모니아성 질소 ㎎/LNaN1.0001.0001.0001.0001.0001.000
2024-03-13T22:15:08.571914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호과망간산칼륨소비량 ㎎/L검사여부미검사사유검사일자검사결과일반세균 중온 CFU/mL분원성대장균군 mL암모니아성 질소 ㎎/L
번호1.000-0.1780.3530.6770.7490.1610.1610.0001.000
과망간산칼륨소비량 ㎎/L-0.1781.0001.0000.0000.0000.0000.0000.0001.000
검사여부0.3531.0001.0001.0001.0001.0001.0001.0001.000
미검사사유0.6770.0001.0001.0000.0000.0000.0000.0000.000
검사일자0.7490.0001.0000.0001.0000.4220.4220.0001.000
검사결과0.1610.0001.0000.0000.4221.0000.9630.0001.000
일반세균 중온 CFU/mL0.1610.0001.0000.0000.4220.9631.0000.0001.000
분원성대장균군 mL0.0000.0001.0000.0000.0000.0000.0001.0001.000
암모니아성 질소 ㎎/L1.0001.0001.0000.0001.0001.0001.0001.0001.000

Missing values

2024-03-13T22:15:03.421683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:15:03.639914image/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.
2024-03-13T22:15:03.805043image/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

번호공동시설명검사여부미검사사유검사일자검사결과일반세균 중온 CFU/mL총대장균군 mL분원성대장균군 mL암모니아성 질소 ㎎/L질산성 질소㎎/L과망간산칼륨소비량 ㎎/L
01금정구 수박골검사<NA>2021-03-03적합불검출<NA>불검출불검출1.50.5
12금정구 삼밭골미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
23금정구 호국사미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
34금정구 참샘골검사<NA>2021-03-03적합불검출<NA>불검출불검출2.50.3
45금정구 정암검사<NA>2021-03-04적합불검출<NA>불검출불검출1.90.6
56금정구 물망골미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
67금정구 용머리검사<NA>2021-03-04적합불검출<NA>불검출불검출2.10.6
78금정구 제일미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
89금정구 서곡검사<NA>2021-03-03적합불검출<NA>불검출불검출10.5
910금정구 서천미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
번호공동시설명검사여부미검사사유검사일자검사결과일반세균 중온 CFU/mL총대장균군 mL분원성대장균군 mL암모니아성 질소 ㎎/L질산성 질소㎎/L과망간산칼륨소비량 ㎎/L
141142해운대구 체육공원미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
142143해운대구 초록공원미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
143144해운대구 장산검사<NA>2021-02-17적합불검출<NA>불검출불검출6.60.5
144145해운대구 장천사미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
145146해운대구 체육공원내검사<NA>2021-02-17적합불검출<NA>불검출불검출1.60.5
146147해운대구 옥천사미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
147148해운대구 고씨제당미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
148149해운대구 장산제일미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
149150해운대구 장산산림욕장미검사안심등급<NA><NA><NA><NA><NA><NA><NA><NA>
150151해운대구 초록공원위검사<NA>2021-02-17적합불검출<NA>불검출불검출1.50.5