Overview

Dataset statistics

Number of variables31
Number of observations23
Missing cells32
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory271.6 B

Variable types

Text8
DateTime2
Numeric16
Categorical5

Dataset

Description전라남도 내 23개소 분뇨처리 시설 현황에 대한 정보를 조회하실 수 있습니다.(시설명, 소재지, 준공일, 시설용량, 연계처리량, 유입수질, 방류수질 등)
Author전라남도
URLhttps://www.data.go.kr/data/15126382/fileData.do

Alerts

연계처리장명 has 2 (8.7%) missing valuesMissing
유입수질(mg_L 개_mL)_BOD has 1 (4.3%) missing valuesMissing
유입수질(mg_L 개_mL)_SS has 1 (4.3%) missing valuesMissing
유입수질(mg_L 개_mL)_T N has 1 (4.3%) missing valuesMissing
유입수질(mg_L 개_mL)_T P has 1 (4.3%) missing valuesMissing
유입수질(mg_L 개_mL)_대장균수 has 1 (4.3%) missing valuesMissing
방류수질(m_L 개_mL)_BOD has 1 (4.3%) missing valuesMissing
방류수질(mg_L 개_mL)_SS has 1 (4.3%) missing valuesMissing
방류수질(mg_L 개_mL)_T N has 1 (4.3%) missing valuesMissing
방류수질(mg_L 개_mL)_T P has 1 (4.3%) missing valuesMissing
방류수질(mg_L 개_mL)_대장균수 has 1 (4.3%) missing valuesMissing
방류수역_지류 has 4 (17.4%) missing valuesMissing
방류수역_중권역 has 7 (30.4%) missing valuesMissing
방류수역_소권역 has 9 (39.1%) missing valuesMissing
소재지 has unique valuesUnique
전화번호 has unique valuesUnique
준공일 has unique valuesUnique
가동개시일 has unique valuesUnique
처리량(세제곱미터_일) has unique valuesUnique
사업비_백만원 has 11 (47.8%) zerosZeros
처리량(세제곱미터_일) has 1 (4.3%) zerosZeros
가동일수(일_년) has 1 (4.3%) zerosZeros
연계처리량(세제곱미터_일) has 7 (30.4%) zerosZeros
유입수질(mg_L 개_mL)_BOD has 2 (8.7%) zerosZeros
유입수질(mg_L 개_mL)_SS has 2 (8.7%) zerosZeros
유입수질(mg_L 개_mL)_T N has 2 (8.7%) zerosZeros
유입수질(mg_L 개_mL)_T P has 2 (8.7%) zerosZeros
유입수질(mg_L 개_mL)_대장균수 has 4 (17.4%) zerosZeros
방류수질(m_L 개_mL)_BOD has 3 (13.0%) zerosZeros
방류수질(mg_L 개_mL)_SS has 3 (13.0%) zerosZeros
방류수질(mg_L 개_mL)_T N has 3 (13.0%) zerosZeros
방류수질(mg_L 개_mL)_T P has 3 (13.0%) zerosZeros
방류수질(mg_L 개_mL)_대장균수 has 7 (30.4%) zerosZeros
직원총수_명 has 13 (56.5%) zerosZeros

Reproduction

Analysis started2024-03-14 18:15:58.424671
Analysis finished2024-03-14 18:15:59.698134
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-03-15T03:16:00.384787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters69
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row목포시
2nd row여수시
3rd row순천시
4th row나주시
5th row광양시
ValueCountFrequency (%)
신안군 2
 
8.7%
여수시 1
 
4.3%
진도군 1
 
4.3%
완도군 1
 
4.3%
장성군 1
 
4.3%
영광군 1
 
4.3%
함평군 1
 
4.3%
무안군 1
 
4.3%
영암군 1
 
4.3%
해남군 1
 
4.3%
Other values (12) 12
52.2%
2024-03-15T03:16:01.628666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 18
26.1%
시 5
 
7.2%
안 3
 
4.3%
성 3
 
4.3%
신 2
 
2.9%
양 2
 
2.9%
장 2
 
2.9%
영 2
 
2.9%
진 2
 
2.9%
흥 2
 
2.9%
Other values (25) 28
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 18
26.1%
시 5
 
7.2%
안 3
 
4.3%
성 3
 
4.3%
신 2
 
2.9%
양 2
 
2.9%
장 2
 
2.9%
영 2
 
2.9%
진 2
 
2.9%
흥 2
 
2.9%
Other values (25) 28
40.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 18
26.1%
시 5
 
7.2%
안 3
 
4.3%
성 3
 
4.3%
신 2
 
2.9%
양 2
 
2.9%
장 2
 
2.9%
영 2
 
2.9%
진 2
 
2.9%
흥 2
 
2.9%
Other values (25) 28
40.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 18
26.1%
시 5
 
7.2%
안 3
 
4.3%
성 3
 
4.3%
신 2
 
2.9%
양 2
 
2.9%
장 2
 
2.9%
영 2
 
2.9%
진 2
 
2.9%
흥 2
 
2.9%
Other values (25) 28
40.6%

시설명
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-03-15T03:16:02.371304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.3478261
Min length2

Characters and Unicode

Total characters169
Distinct characters42
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row북항분뇨처리시설
2nd row분뇨전처리시설
3rd row분뇨 공공처리시설
4th row나주 분뇨처리장
5th row태인분뇨처리시설
ValueCountFrequency (%)
분뇨처리시설 4
 
14.8%
분뇨처리장 2
 
7.4%
장흥분뇨위생처리장 1
 
3.7%
강진분뇨처리장 1
 
3.7%
흑산위생처리장 1
 
3.7%
진도분뇨 1
 
3.7%
완도군분뇨처리장 1
 
3.7%
영광군 1
 
3.7%
분뇨공공처리시설 1
 
3.7%
무안분뇨처리시설 1
 
3.7%
Other values (13) 13
48.1%
2024-03-15T03:16:03.596298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
처 21
12.4%
리 21
12.4%
분 19
11.2%
뇨 19
11.2%
시 11
 
6.5%
설 11
 
6.5%
장 11
 
6.5%
공 6
 
3.6%
위 5
 
3.0%
생 5
 
3.0%
Other values (32) 40
23.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
97.6%
Space Separator 4
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
처 21
12.7%
리 21
12.7%
분 19
11.5%
뇨 19
11.5%
시 11
 
6.7%
설 11
 
6.7%
장 11
 
6.7%
공 6
 
3.6%
위 5
 
3.0%
생 5
 
3.0%
Other values (31) 36
21.8%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
97.6%
Common 4
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
처 21
12.7%
리 21
12.7%
분 19
11.5%
뇨 19
11.5%
시 11
 
6.7%
설 11
 
6.7%
장 11
 
6.7%
공 6
 
3.6%
위 5
 
3.0%
생 5
 
3.0%
Other values (31) 36
21.8%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
97.6%
ASCII 4
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
처 21
12.7%
리 21
12.7%
분 19
11.5%
뇨 19
11.5%
시 11
 
6.7%
설 11
 
6.7%
장 11
 
6.7%
공 6
 
3.6%
위 5
 
3.0%
생 5
 
3.0%
Other values (31) 36
21.8%
ASCII
ValueCountFrequency (%)
4
100.0%

소재지
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-03-15T03:16:04.618329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length21.086957
Min length15

Characters and Unicode

Total characters485
Distinct characters94
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row전라남도 목포시 청호로 220번길33(연산동)
2nd row전라남도 여수시 신월로 284-1(웅천동)
3rd row전라남도 순천시 강변로 77
4th row전라남도 나주시 가야길 210
5th row전라남도 광양시 산업로 125
ValueCountFrequency (%)
전라남도 23
 
20.9%
신안군 2
 
1.8%
대아로 1
 
0.9%
영산로 1
 
0.9%
엄다면 1
 
0.9%
함평군 1
 
0.9%
128-1 1
 
0.9%
평용리 1
 
0.9%
무안읍 1
 
0.9%
무안군 1
 
0.9%
Other values (77) 77
70.0%
2024-03-15T03:16:06.105075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
17.9%
도 28
 
5.8%
남 25
 
5.2%
전 23
 
4.7%
라 23
 
4.7%
군 17
 
3.5%
1 14
 
2.9%
로 13
 
2.7%
3 12
 
2.5%
2 12
 
2.5%
Other values (84) 231
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 296
61.0%
Space Separator 87
 
17.9%
Decimal Number 87
 
17.9%
Dash Punctuation 11
 
2.3%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 28
 
9.5%
남 25
 
8.4%
전 23
 
7.8%
라 23
 
7.8%
군 17
 
5.7%
로 13
 
4.4%
읍 11
 
3.7%
리 7
 
2.4%
산 7
 
2.4%
면 7
 
2.4%
Other values (70) 135
45.6%
Decimal Number
ValueCountFrequency (%)
1 14
16.1%
3 12
13.8%
2 12
13.8%
6 10
11.5%
9 9
10.3%
4 7
8.0%
8 7
8.0%
5 6
6.9%
7 5
 
5.7%
0 5
 
5.7%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 296
61.0%
Common 189
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 28
 
9.5%
남 25
 
8.4%
전 23
 
7.8%
라 23
 
7.8%
군 17
 
5.7%
로 13
 
4.4%
읍 11
 
3.7%
리 7
 
2.4%
산 7
 
2.4%
면 7
 
2.4%
Other values (70) 135
45.6%
Common
ValueCountFrequency (%)
87
46.0%
1 14
 
7.4%
3 12
 
6.3%
2 12
 
6.3%
- 11
 
5.8%
6 10
 
5.3%
9 9
 
4.8%
4 7
 
3.7%
8 7
 
3.7%
5 6
 
3.2%
Other values (4) 14
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 296
61.0%
ASCII 189
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
46.0%
1 14
 
7.4%
3 12
 
6.3%
2 12
 
6.3%
- 11
 
5.8%
6 10
 
5.3%
9 9
 
4.8%
4 7
 
3.7%
8 7
 
3.7%
5 6
 
3.2%
Other values (4) 14
 
7.4%
Hangul
ValueCountFrequency (%)
도 28
 
9.5%
남 25
 
8.4%
전 23
 
7.8%
라 23
 
7.8%
군 17
 
5.7%
로 13
 
4.4%
읍 11
 
3.7%
리 7
 
2.4%
산 7
 
2.4%
면 7
 
2.4%
Other values (70) 135
45.6%

전화번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-03-15T03:16:07.006110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row061-270-8365
2nd row061-643-9496
3rd row061-749-6540
4th row061-820-8201
5th row061-797-4936
ValueCountFrequency (%)
061-270-8365 1
 
4.3%
061-430-3795 1
 
4.3%
061-240-8040 1
 
4.3%
061-544-6712 1
 
4.3%
061-550-5516 1
 
4.3%
061-390-8549 1
 
4.3%
061-350-5289 1
 
4.3%
061-320-2836 1
 
4.3%
061-450-4132 1
 
4.3%
061-470-2523 1
 
4.3%
Other values (13) 13
56.5%
2024-03-15T03:16:08.518423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
16.7%
- 46
16.7%
6 34
12.3%
1 33
12.0%
3 19
6.9%
8 18
 
6.5%
5 18
 
6.5%
4 18
 
6.5%
2 17
 
6.2%
7 15
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
20.0%
6 34
14.8%
1 33
14.3%
3 19
8.3%
8 18
 
7.8%
5 18
 
7.8%
4 18
 
7.8%
2 17
 
7.4%
7 15
 
6.5%
9 12
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
16.7%
- 46
16.7%
6 34
12.3%
1 33
12.0%
3 19
6.9%
8 18
 
6.5%
5 18
 
6.5%
4 18
 
6.5%
2 17
 
6.2%
7 15
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
16.7%
- 46
16.7%
6 34
12.3%
1 33
12.0%
3 19
6.9%
8 18
 
6.5%
5 18
 
6.5%
4 18
 
6.5%
2 17
 
6.2%
7 15
 
5.4%

준공일
Date

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
Minimum1985-12-01 00:00:00
Maximum2006-06-27 00:00:00
2024-03-15T03:16:08.982577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:16:09.377738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

가동개시일
Date

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
Minimum1989-03-01 00:00:00
Maximum2005-04-09 00:00:00
2024-03-15T03:16:09.855763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:16:10.328548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

사업비_백만원
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1147
Minimum0
Maximum3981
Zeros11
Zeros (%)47.8%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:10.686314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median162
Q32140
95-th percentile3944
Maximum3981
Range3981
Interquartile range (IQR)2140

Descriptive statistics

Standard deviation1466.1644
Coefficient of variation (CV)1.2782601
Kurtosis-0.67021091
Mean1147
Median Absolute Deviation (MAD)162
Skewness0.90109842
Sum26381
Variance2149638
MonotonicityNot monotonic
2024-03-15T03:16:11.281541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 11
47.8%
1000 1
 
4.3%
2167 1
 
4.3%
2113 1
 
4.3%
1700 1
 
4.3%
251 1
 
4.3%
3981 1
 
4.3%
1680 1
 
4.3%
162 1
 
4.3%
2524 1
 
4.3%
Other values (3) 3
 
13.0%
ValueCountFrequency (%)
0 11
47.8%
162 1
 
4.3%
251 1
 
4.3%
1000 1
 
4.3%
1680 1
 
4.3%
1700 1
 
4.3%
2113 1
 
4.3%
2167 1
 
4.3%
2524 1
 
4.3%
3051 1
 
4.3%
ValueCountFrequency (%)
3981 1
4.3%
3961 1
4.3%
3791 1
4.3%
3051 1
4.3%
2524 1
4.3%
2167 1
4.3%
2113 1
4.3%
1700 1
4.3%
1680 1
4.3%
1000 1
4.3%

시설용량(세제곱미터_일)
Real number (ℝ)

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.043478
Minimum2
Maximum330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:11.487379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile18.7
Q140
median50
Q392.5
95-th percentile294
Maximum330
Range328
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation86.842322
Coefficient of variation (CV)1.0457452
Kurtosis3.5253348
Mean83.043478
Median Absolute Deviation (MAD)20
Skewness2.0820591
Sum1910
Variance7541.5889
MonotonicityNot monotonic
2024-03-15T03:16:11.679532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
50 5
21.7%
40 3
13.0%
100 2
 
8.7%
30 2
 
8.7%
240 1
 
4.3%
330 1
 
4.3%
300 1
 
4.3%
25 1
 
4.3%
95 1
 
4.3%
55 1
 
4.3%
Other values (5) 5
21.7%
ValueCountFrequency (%)
2 1
 
4.3%
18 1
 
4.3%
25 1
 
4.3%
30 2
 
8.7%
40 3
13.0%
50 5
21.7%
55 1
 
4.3%
60 1
 
4.3%
65 1
 
4.3%
90 1
 
4.3%
ValueCountFrequency (%)
330 1
 
4.3%
300 1
 
4.3%
240 1
 
4.3%
100 2
 
8.7%
95 1
 
4.3%
90 1
 
4.3%
65 1
 
4.3%
60 1
 
4.3%
55 1
 
4.3%
50 5
21.7%

처리량(세제곱미터_일)
Real number (ℝ)

UNIQUE  ZEROS 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.991304
Minimum0
Maximum140.3
Zeros1
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:11.895610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.63
Q114
median24
Q333.2
95-th percentile112.37
Maximum140.3
Range140.3
Interquartile range (IQR)19.2

Descriptive statistics

Standard deviation34.300383
Coefficient of variation (CV)1.0721783
Kurtosis5.0907123
Mean31.991304
Median Absolute Deviation (MAD)11
Skewness2.2333537
Sum735.8
Variance1176.5163
MonotonicityNot monotonic
2024-03-15T03:16:12.109124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
56.3 1
 
4.3%
140.3 1
 
4.3%
18.0 1
 
4.3%
0.2 1
 
4.3%
4.5 1
 
4.3%
12.9 1
 
4.3%
17.6 1
 
4.3%
47.6 1
 
4.3%
0.0 1
 
4.3%
31.4 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
0.0 1
4.3%
0.2 1
4.3%
4.5 1
4.3%
6.0 1
4.3%
11.1 1
4.3%
12.9 1
4.3%
15.1 1
4.3%
17.6 1
4.3%
18.0 1
4.3%
19.0 1
4.3%
ValueCountFrequency (%)
140.3 1
4.3%
118.6 1
4.3%
56.3 1
4.3%
51.0 1
4.3%
47.6 1
4.3%
35.0 1
4.3%
31.4 1
4.3%
29.3 1
4.3%
26.7 1
4.3%
26.0 1
4.3%

가동일수(일_년)
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.78261
Minimum0
Maximum366
Zeros1
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:12.401100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile146.1
Q1246.5
median300
Q3365
95-th percentile365
Maximum366
Range366
Interquartile range (IQR)118.5

Descriptive statistics

Standard deviation95.485818
Coefficient of variation (CV)0.33412047
Kurtosis2.1513373
Mean285.78261
Median Absolute Deviation (MAD)65
Skewness-1.3535868
Sum6573
Variance9117.5415
MonotonicityNot monotonic
2024-03-15T03:16:12.599836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
365 9
39.1%
249 2
 
8.7%
300 1
 
4.3%
356 1
 
4.3%
265 1
 
4.3%
243 1
 
4.3%
247 1
 
4.3%
145 1
 
4.3%
216 1
 
4.3%
246 1
 
4.3%
Other values (4) 4
17.4%
ValueCountFrequency (%)
0 1
4.3%
145 1
4.3%
156 1
4.3%
216 1
4.3%
243 1
4.3%
246 1
4.3%
247 1
4.3%
249 2
8.7%
250 1
4.3%
265 1
4.3%
ValueCountFrequency (%)
366 1
 
4.3%
365 9
39.1%
356 1
 
4.3%
300 1
 
4.3%
265 1
 
4.3%
250 1
 
4.3%
249 2
 
8.7%
247 1
 
4.3%
246 1
 
4.3%
243 1
 
4.3%

처리공법
Categorical

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size312.0 B
액상부식법
9 
전처리
3 
액상부식
2 
자연정화법
2 
전처리 후 하수연계처리
1 
Other values (6)
6 

Length

Max length17
Median length5
Mean length5.7826087
Min length3

Unique

Unique7 ?
Unique (%)30.4%

Sample

1st row전처리
2nd row전처리
3rd row전처리 후 하수연계처리
4th row액상부식법
5th row액상부식

Common Values

ValueCountFrequency (%)
액상부식법 9
39.1%
전처리 3
 
13.0%
액상부식 2
 
8.7%
자연정화법 2
 
8.7%
전처리 후 하수연계처리 1
 
4.3%
HBR-II 공법 1
 
4.3%
한외여과막 1
 
4.3%
전처리시설 1
 
4.3%
액상부식법(질소,인제거고도처리) 1
 
4.3%
세일바이오시스템 1
 
4.3%

Length

2024-03-15T03:16:12.977967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
액상부식법 9
34.6%
전처리 4
15.4%
액상부식 2
 
7.7%
자연정화법 2
 
7.7%
후 1
 
3.8%
하수연계처리 1
 
3.8%
hbr-ii 1
 
3.8%
공법 1
 
3.8%
한외여과막 1
 
3.8%
전처리시설 1
 
3.8%
Other values (3) 3
 
11.5%

연계처리장명
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing2
Missing (%)8.7%
Memory size312.0 B
2024-03-15T03:16:13.738931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.4761905
Min length2

Characters and Unicode

Total characters157
Distinct characters48
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row북항하수처리장
2nd row여수공공하수처리시설
3rd row순천공공하수처리시설
4th row나주하수
5th row태인공공폐수처리시설
ValueCountFrequency (%)
압해하수종말처리장 2
 
8.7%
북항하수처리장 1
 
4.3%
해당없음 1
 
4.3%
진도읍공공하수처리장 1
 
4.3%
장성공공하수처리시설 1
 
4.3%
분뇨처리시설 1
 
4.3%
영광군 1
 
4.3%
함평공공하수처리시설 1
 
4.3%
단독 1
 
4.3%
대불 1
 
4.3%
Other values (12) 12
52.2%
2024-03-15T03:16:14.970966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 20
12.7%
수 16
 
10.2%
처 15
 
9.6%
리 15
 
9.6%
하 14
 
8.9%
설 9
 
5.7%
시 9
 
5.7%
장 7
 
4.5%
해 4
 
2.5%
성 3
 
1.9%
Other values (38) 45
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
98.7%
Space Separator 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 20
12.9%
수 16
 
10.3%
처 15
 
9.7%
리 15
 
9.7%
하 14
 
9.0%
설 9
 
5.8%
시 9
 
5.8%
장 7
 
4.5%
해 4
 
2.6%
성 3
 
1.9%
Other values (37) 43
27.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
98.7%
Common 2
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 20
12.9%
수 16
 
10.3%
처 15
 
9.7%
리 15
 
9.7%
하 14
 
9.0%
설 9
 
5.8%
시 9
 
5.8%
장 7
 
4.5%
해 4
 
2.6%
성 3
 
1.9%
Other values (37) 43
27.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
98.7%
ASCII 2
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 20
12.9%
수 16
 
10.3%
처 15
 
9.7%
리 15
 
9.7%
하 14
 
9.0%
설 9
 
5.8%
시 9
 
5.8%
장 7
 
4.5%
해 4
 
2.6%
성 3
 
1.9%
Other values (37) 43
27.7%
ASCII
ValueCountFrequency (%)
2
100.0%

연계처리량(세제곱미터_일)
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.643478
Minimum0
Maximum126.3
Zeros7
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:15.348969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median18
Q326.5
95-th percentile112.37
Maximum126.3
Range126.3
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation34.312161
Coefficient of variation (CV)1.3923425
Kurtosis4.6832208
Mean24.643478
Median Absolute Deviation (MAD)17.8
Skewness2.2004399
Sum566.8
Variance1177.3244
MonotonicityNot monotonic
2024-03-15T03:16:15.735987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 7
30.4%
56.3 1
 
4.3%
126.3 1
 
4.3%
4.5 1
 
4.3%
19.4 1
 
4.3%
27.7 1
 
4.3%
24.0 1
 
4.3%
25.3 1
 
4.3%
20.2 1
 
4.3%
17.0 1
 
4.3%
Other values (7) 7
30.4%
ValueCountFrequency (%)
0.0 7
30.4%
0.2 1
 
4.3%
4.5 1
 
4.3%
17.0 1
 
4.3%
17.2 1
 
4.3%
18.0 1
 
4.3%
19.4 1
 
4.3%
20.2 1
 
4.3%
20.5 1
 
4.3%
24.0 1
 
4.3%
ValueCountFrequency (%)
126.3 1
4.3%
118.6 1
4.3%
56.3 1
4.3%
36.6 1
4.3%
35.0 1
4.3%
27.7 1
4.3%
25.3 1
4.3%
24.0 1
4.3%
20.5 1
4.3%
20.2 1
4.3%

유입수질(mg_L 개_mL)_BOD
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean2861.0455
Minimum0
Maximum11388.4
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:16.096363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.665
Q1372.65
median2577.55
Q33869.225
95-th percentile6542.225
Maximum11388.4
Range11388.4
Interquartile range (IQR)3496.575

Descriptive statistics

Standard deviation2783.2495
Coefficient of variation (CV)0.97280856
Kurtosis2.8625445
Mean2861.0455
Median Absolute Deviation (MAD)2005.85
Skewness1.4237273
Sum62943
Variance7746477.9
MonotonicityNot monotonic
2024-03-15T03:16:16.479095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
8.7%
3443.2 1
 
4.3%
6578.5 1
 
4.3%
3951.2 1
 
4.3%
2436.1 1
 
4.3%
33.3 1
 
4.3%
125.0 1
 
4.3%
1552.5 1
 
4.3%
173.6 1
 
4.3%
1572.9 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
0.0 2
8.7%
33.3 1
4.3%
125.0 1
4.3%
139.3 1
4.3%
173.6 1
4.3%
969.8 1
4.3%
1552.5 1
4.3%
1572.9 1
4.3%
2389.5 1
4.3%
2436.1 1
4.3%
ValueCountFrequency (%)
11388.4 1
4.3%
6578.5 1
4.3%
5853.0 1
4.3%
5367.0 1
4.3%
5081.4 1
4.3%
3951.2 1
4.3%
3623.3 1
4.3%
3443.2 1
4.3%
2785.2 1
4.3%
2760.8 1
4.3%

유입수질(mg_L 개_mL)_TOC
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
0.0
18 
<NA>
2 
1506.7
 
1
2457.2
 
1
1927.1
 
1

Length

Max length6
Median length3
Mean length3.4782609
Min length3

Unique

Unique3 ?
Unique (%)13.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row1506.7
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 18
78.3%
<NA> 2
 
8.7%
1506.7 1
 
4.3%
2457.2 1
 
4.3%
1927.1 1
 
4.3%

Length

2024-03-15T03:16:16.914439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:16:17.260970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 18
78.3%
na 2
 
8.7%
1506.7 1
 
4.3%
2457.2 1
 
4.3%
1927.1 1
 
4.3%

유입수질(mg_L 개_mL)_SS
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean4713.7864
Minimum0
Maximum14987.9
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:17.585116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.275
Q11071.325
median4687.85
Q35689.2
95-th percentile11292.21
Maximum14987.9
Range14987.9
Interquartile range (IQR)4617.875

Descriptive statistics

Standard deviation4029.3381
Coefficient of variation (CV)0.85479862
Kurtosis0.65676287
Mean4713.7864
Median Absolute Deviation (MAD)1743.05
Skewness0.88191034
Sum103703.3
Variance16235565
MonotonicityNot monotonic
2024-03-15T03:16:18.006333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
8.7%
4935.9 1
 
4.3%
5757.6 1
 
4.3%
4851.0 1
 
4.3%
460.1 1
 
4.3%
2905.0 1
 
4.3%
105.5 1
 
4.3%
2984.6 1
 
4.3%
425.8 1
 
4.3%
5329.8 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
0.0 2
8.7%
105.5 1
4.3%
112.8 1
4.3%
425.8 1
4.3%
460.1 1
4.3%
2905.0 1
4.3%
2984.6 1
4.3%
3588.3 1
4.3%
4350.0 1
4.3%
4524.7 1
4.3%
ValueCountFrequency (%)
14987.9 1
4.3%
11352.8 1
4.3%
10141.0 1
4.3%
9800.6 1
4.3%
6281.2 1
4.3%
5757.6 1
4.3%
5484.0 1
4.3%
5329.8 1
4.3%
5324.7 1
4.3%
4935.9 1
4.3%

유입수질(mg_L 개_mL)_T N
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean531.85205
Minimum0
Maximum2220.2
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:18.383566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.28765
Q1122.74975
median393.4565
Q3632.77025
95-th percentile1569.0499
Maximum2220.2
Range2220.2
Interquartile range (IQR)510.0205

Descriptive statistics

Standard deviation541.5646
Coefficient of variation (CV)1.0182618
Kurtosis3.8049246
Mean531.85205
Median Absolute Deviation (MAD)269.7325
Skewness1.7880331
Sum11700.745
Variance293292.21
MonotonicityNot monotonic
2024-03-15T03:16:18.752598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
8.7%
390.995 1
 
4.3%
395.918 1
 
4.3%
351.584 1
 
4.3%
580.671 1
 
4.3%
66.84 1
 
4.3%
38.658 1
 
4.3%
549.891 1
 
4.3%
25.753 1
 
4.3%
575.163 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
0.0 2
8.7%
25.753 1
4.3%
38.658 1
4.3%
66.84 1
4.3%
95.833 1
4.3%
203.5 1
4.3%
321.834 1
4.3%
351.584 1
4.3%
375.6 1
4.3%
390.995 1
4.3%
ValueCountFrequency (%)
2220.2 1
4.3%
1596.0 1
4.3%
1056.998 1
4.3%
889.0 1
4.3%
705.822 1
4.3%
635.298 1
4.3%
625.187 1
4.3%
580.671 1
4.3%
575.163 1
4.3%
549.891 1
4.3%

유입수질(mg_L 개_mL)_T P
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean96.289773
Minimum0
Maximum361.5
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:19.097706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1957
Q137.09525
median86.177
Q3127.16675
95-th percentile258.0645
Maximum361.5
Range361.5
Interquartile range (IQR)90.0715

Descriptive statistics

Standard deviation90.019107
Coefficient of variation (CV)0.93487714
Kurtosis2.5023176
Mean96.289773
Median Absolute Deviation (MAD)48.2865
Skewness1.4013014
Sum2118.375
Variance8103.4397
MonotonicityNot monotonic
2024-03-15T03:16:19.499141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
8.7%
48.944 1
 
4.3%
102.242 1
 
4.3%
83.254 1
 
4.3%
120.806 1
 
4.3%
5.465 1
 
4.3%
4.762 1
 
4.3%
58.836 1
 
4.3%
3.914 1
 
4.3%
262.81 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
0.0 2
8.7%
3.914 1
4.3%
4.762 1
4.3%
5.465 1
4.3%
36.3 1
4.3%
39.481 1
4.3%
48.944 1
4.3%
53.127 1
4.3%
58.836 1
4.3%
83.254 1
4.3%
ValueCountFrequency (%)
361.5 1
4.3%
262.81 1
4.3%
167.9 1
4.3%
167.0 1
4.3%
153.712 1
4.3%
129.287 1
4.3%
120.806 1
4.3%
115.314 1
4.3%
114.621 1
4.3%
102.242 1
4.3%

유입수질(mg_L 개_mL)_대장균수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)86.4%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean24657918
Minimum0
Maximum5.4 × 108
Zeros4
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:19.854187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17064.5
median38465.5
Q3246942
95-th percentile433739.45
Maximum5.4 × 108
Range5.4 × 108
Interquartile range (IQR)239877.5

Descriptive statistics

Standard deviation1.1510335 × 108
Coefficient of variation (CV)4.6680076
Kurtosis21.999927
Mean24657918
Median Absolute Deviation (MAD)38465.5
Skewness4.6904046
Sum5.424742 × 108
Variance1.3248781 × 1016
MonotonicityNot monotonic
2024-03-15T03:16:20.062682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 4
17.4%
260000 1
 
4.3%
380567 1
 
4.3%
540000000 1
 
4.3%
210000 1
 
4.3%
1500 1
 
4.3%
41009 1
 
4.3%
232608 1
 
4.3%
20901 1
 
4.3%
229118 1
 
4.3%
Other values (9) 9
39.1%
ValueCountFrequency (%)
0 4
17.4%
1500 1
 
4.3%
3000 1
 
4.3%
19258 1
 
4.3%
20901 1
 
4.3%
22135 1
 
4.3%
25649 1
 
4.3%
37811 1
 
4.3%
39120 1
 
4.3%
41009 1
 
4.3%
ValueCountFrequency (%)
540000000 1
4.3%
436538 1
4.3%
380567 1
4.3%
263269 1
4.3%
260000 1
4.3%
251720 1
4.3%
232608 1
4.3%
229118 1
4.3%
210000 1
4.3%
41009 1
4.3%

방류수질(m_L 개_mL)_BOD
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)90.9%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean394.62727
Minimum0
Maximum5853
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:20.368253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.85
median5.4
Q372.925
95-th percentile2040.38
Maximum5853
Range5853
Interquartile range (IQR)71.075

Descriptive statistics

Standard deviation1299.9429
Coefficient of variation (CV)3.2941032
Kurtosis16.440971
Mean394.62727
Median Absolute Deviation (MAD)5.4
Skewness3.9794422
Sum8681.8
Variance1689851.7
MonotonicityNot monotonic
2024-03-15T03:16:20.760598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 3
 
13.0%
6.4 1
 
4.3%
3.4 1
 
4.3%
0.9 1
 
4.3%
77.8 1
 
4.3%
4.2 1
 
4.3%
1.8 1
 
4.3%
2.0 1
 
4.3%
4.4 1
 
4.3%
2134.2 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
0.0 3
13.0%
0.9 1
 
4.3%
1.7 1
 
4.3%
1.8 1
 
4.3%
2.0 1
 
4.3%
3.4 1
 
4.3%
3.8 1
 
4.3%
4.2 1
 
4.3%
4.4 1
 
4.3%
6.4 1
 
4.3%
ValueCountFrequency (%)
5853.0 1
4.3%
2134.2 1
4.3%
257.8 1
4.3%
113.3 1
4.3%
100.5 1
4.3%
77.8 1
4.3%
58.3 1
4.3%
36.4 1
4.3%
13.4 1
4.3%
8.5 1
4.3%

방류수질(mg_L 개_mL)_TOC
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
0.0
18 
<NA>
2 
40.5
 
1
52.1
 
1
23.4
 
1

Length

Max length4
Median length3
Mean length3.2173913
Min length3

Unique

Unique3 ?
Unique (%)13.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row40.5
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 18
78.3%
<NA> 2
 
8.7%
40.5 1
 
4.3%
52.1 1
 
4.3%
23.4 1
 
4.3%

Length

2024-03-15T03:16:21.172210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:16:21.506486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 18
78.3%
na 2
 
8.7%
40.5 1
 
4.3%
52.1 1
 
4.3%
23.4 1
 
4.3%

방류수질(mg_L 개_mL)_SS
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)86.4%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean770.22273
Minimum0
Maximum10141
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:21.800992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.725
median7
Q3168.05
95-th percentile4374.25
Maximum10141
Range10141
Interquartile range (IQR)165.325

Descriptive statistics

Standard deviation2313.3707
Coefficient of variation (CV)3.0035087
Kurtosis14.046056
Mean770.22273
Median Absolute Deviation (MAD)7
Skewness3.6761599
Sum16944.9
Variance5351684
MonotonicityNot monotonic
2024-03-15T03:16:22.009920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 3
 
13.0%
3.1 2
 
8.7%
1.5 1
 
4.3%
10.0 1
 
4.3%
278.6 1
 
4.3%
2.8 1
 
4.3%
2.9 1
 
4.3%
2.7 1
 
4.3%
4532.6 1
 
4.3%
4.0 1
 
4.3%
Other values (9) 9
39.1%
ValueCountFrequency (%)
0.0 3
13.0%
1.5 1
 
4.3%
2.3 1
 
4.3%
2.7 1
 
4.3%
2.8 1
 
4.3%
2.9 1
 
4.3%
3.1 2
8.7%
4.0 1
 
4.3%
10.0 1
 
4.3%
11.6 1
 
4.3%
ValueCountFrequency (%)
10141.0 1
4.3%
4532.6 1
4.3%
1365.6 1
4.3%
278.6 1
4.3%
247.9 1
4.3%
205.1 1
4.3%
56.9 1
4.3%
45.2 1
4.3%
28.0 1
4.3%
11.6 1
4.3%

방류수질(mg_L 개_mL)_T N
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)90.9%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean99.914636
Minimum0
Maximum889
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:22.206086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.12625
median21.4625
Q363.377
95-th percentile365.945
Maximum889
Range889
Interquartile range (IQR)54.25075

Descriptive statistics

Standard deviation203.50144
Coefficient of variation (CV)2.0367531
Kurtosis11.14436
Mean99.914636
Median Absolute Deviation (MAD)14.707
Skewness3.1726986
Sum2198.122
Variance41412.837
MonotonicityNot monotonic
2024-03-15T03:16:22.514434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 3
 
13.0%
17.6 1
 
4.3%
12.11 1
 
4.3%
25.8 1
 
4.3%
275.6 1
 
4.3%
7.011 1
 
4.3%
13.104 1
 
4.3%
11.965 1
 
4.3%
15.584 1
 
4.3%
259.656 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
0.0 3
13.0%
6.5 1
 
4.3%
7.011 1
 
4.3%
8.18 1
 
4.3%
11.965 1
 
4.3%
12.11 1
 
4.3%
13.104 1
 
4.3%
15.584 1
 
4.3%
17.6 1
 
4.3%
25.325 1
 
4.3%
ValueCountFrequency (%)
889.0 1
4.3%
370.7 1
4.3%
275.6 1
4.3%
259.656 1
4.3%
82.4 1
4.3%
67.54 1
4.3%
50.888 1
4.3%
31.54 1
4.3%
27.619 1
4.3%
25.8 1
4.3%

방류수질(mg_L 개_mL)_T P
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)90.9%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean204.66186
Minimum0
Maximum4167
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:22.889616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25925
median1.2955
Q319.13725
95-th percentile160.745
Maximum4167
Range4167
Interquartile range (IQR)18.878

Descriptive statistics

Standard deviation885.72638
Coefficient of variation (CV)4.3277549
Kurtosis21.916967
Mean204.66186
Median Absolute Deviation (MAD)1.2955
Skewness4.6780017
Sum4502.561
Variance784511.22
MonotonicityNot monotonic
2024-03-15T03:16:23.251346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 3
 
13.0%
0.29 1
 
4.3%
0.416 1
 
4.3%
1.878 1
 
4.3%
27.6 1
 
4.3%
0.302 1
 
4.3%
0.249 1
 
4.3%
0.051 1
 
4.3%
0.713 1
 
4.3%
31.863 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
0.0 3
13.0%
0.051 1
 
4.3%
0.2 1
 
4.3%
0.249 1
 
4.3%
0.29 1
 
4.3%
0.302 1
 
4.3%
0.35 1
 
4.3%
0.416 1
 
4.3%
0.713 1
 
4.3%
1.878 1
 
4.3%
ValueCountFrequency (%)
4167.0 1
4.3%
167.0 1
4.3%
41.9 1
4.3%
31.863 1
4.3%
27.6 1
4.3%
20.114 1
4.3%
16.207 1
4.3%
12.705 1
4.3%
7.123 1
4.3%
6.6 1
4.3%

방류수질(mg_L 개_mL)_대장균수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)72.7%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean18684.182
Minimum0
Maximum353678
Zeros7
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:23.579740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median31.5
Q3145
95-th percentile21849.55
Maximum353678
Range353678
Interquartile range (IQR)145

Descriptive statistics

Standard deviation75071.616
Coefficient of variation (CV)4.0179237
Kurtosis21.664112
Mean18684.182
Median Absolute Deviation (MAD)31.5
Skewness4.6403964
Sum411052
Variance5.6357475 × 109
MonotonicityNot monotonic
2024-03-15T03:16:23.954242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 7
30.4%
30 1
 
4.3%
46 1
 
4.3%
39 1
 
4.3%
2 1
 
4.3%
28 1
 
4.3%
100 1
 
4.3%
353678 1
 
4.3%
6238 1
 
4.3%
33 1
 
4.3%
Other values (6) 6
26.1%
ValueCountFrequency (%)
0 7
30.4%
2 1
 
4.3%
15 1
 
4.3%
28 1
 
4.3%
30 1
 
4.3%
33 1
 
4.3%
39 1
 
4.3%
46 1
 
4.3%
100 1
 
4.3%
133 1
 
4.3%
ValueCountFrequency (%)
353678 1
4.3%
22135 1
4.3%
16426 1
4.3%
12000 1
4.3%
6238 1
4.3%
149 1
4.3%
133 1
4.3%
100 1
4.3%
46 1
4.3%
39 1
4.3%

방류수역_수계
Categorical

Distinct9
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size312.0 B
영산강
9 
섬진강
4 
<NA>
3 
연안
2 
섬진강남해권수계
1 
Other values (4)
4 

Length

Max length8
Median length3
Mean length3.4782609
Min length2

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row영산강
2nd row섬진강
3rd row<NA>
4th row<NA>
5th row섬진강남해권수계

Common Values

ValueCountFrequency (%)
영산강 9
39.1%
섬진강 4
17.4%
<NA> 3
 
13.0%
연안 2
 
8.7%
섬진강남해권수계 1
 
4.3%
섬진강(남해) 1
 
4.3%
남해 1
 
4.3%
연안(서해) 1
 
4.3%
서해 1
 
4.3%

Length

2024-03-15T03:16:24.384202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:16:24.739896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영산강 9
39.1%
섬진강 4
17.4%
na 3
 
13.0%
연안 2
 
8.7%
섬진강남해권수계 1
 
4.3%
섬진강(남해 1
 
4.3%
남해 1
 
4.3%
연안(서해 1
 
4.3%
서해 1
 
4.3%

방류수역_지류
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing4
Missing (%)17.4%
Memory size312.0 B
2024-03-15T03:16:25.430151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.8421053
Min length2

Characters and Unicode

Total characters73
Distinct characters38
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

Unique17 ?
Unique (%)89.5%

Sample

1st row연안지류
2nd row남해서부
3rd row남해(해양방류)
4th row담양천
5th row묘천
ValueCountFrequency (%)
남해서부 2
 
10.0%
서해안 1
 
5.0%
연안지류 1
 
5.0%
탐진강 1
 
5.0%
황룡강 1
 
5.0%
와탄천 1
 
5.0%
지류 1
 
5.0%
영산강 1
 
5.0%
사마천 1
 
5.0%
해남방조제 1
 
5.0%
Other values (9) 9
45.0%
2024-03-15T03:16:26.519044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 7
 
9.6%
해 6
 
8.2%
남 4
 
5.5%
강 4
 
5.5%
서 3
 
4.1%
부 3
 
4.1%
지 3
 
4.1%
연 3
 
4.1%
류 3
 
4.1%
진 3
 
4.1%
Other values (28) 34
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
95.9%
Space Separator 1
 
1.4%
Close Punctuation 1
 
1.4%
Open Punctuation 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 7
 
10.0%
해 6
 
8.6%
남 4
 
5.7%
강 4
 
5.7%
서 3
 
4.3%
부 3
 
4.3%
지 3
 
4.3%
연 3
 
4.3%
류 3
 
4.3%
진 3
 
4.3%
Other values (25) 31
44.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
95.9%
Common 3
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 7
 
10.0%
해 6
 
8.6%
남 4
 
5.7%
강 4
 
5.7%
서 3
 
4.3%
부 3
 
4.3%
지 3
 
4.3%
연 3
 
4.3%
류 3
 
4.3%
진 3
 
4.3%
Other values (25) 31
44.3%
Common
ValueCountFrequency (%)
1
33.3%
) 1
33.3%
( 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
95.9%
ASCII 3
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 7
 
10.0%
해 6
 
8.6%
남 4
 
5.7%
강 4
 
5.7%
서 3
 
4.3%
부 3
 
4.3%
지 3
 
4.3%
연 3
 
4.3%
류 3
 
4.3%
진 3
 
4.3%
Other values (25) 31
44.3%
ASCII
ValueCountFrequency (%)
1
33.3%
) 1
33.3%
( 1
33.3%

방류수역_중권역
Text

MISSING 

Distinct14
Distinct (%)87.5%
Missing7
Missing (%)30.4%
Memory size312.0 B
2024-03-15T03:16:27.173328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.125
Min length2

Characters and Unicode

Total characters66
Distinct characters37
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)75.0%

Sample

1st row영산강하구언
2nd row여수시
3rd row남해서부
4th row영산강상류
5th row섬진곡성
ValueCountFrequency (%)
영산강 3
16.7%
와탄천 2
 
11.1%
영산강하구언 1
 
5.6%
여수시 1
 
5.6%
남해서부 1
 
5.6%
영산강상류 1
 
5.6%
섬진곡성 1
 
5.6%
탐진강 1
 
5.6%
섬진강 1
 
5.6%
서남해 1
 
5.6%
Other values (5) 5
27.8%
2024-03-15T03:16:28.292499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
강 8
 
12.1%
영 6
 
9.1%
산 5
 
7.6%
진 3
 
4.5%
수 2
 
3.0%
2
 
3.0%
류 2
 
3.0%
서 2
 
3.0%
해 2
 
3.0%
남 2
 
3.0%
Other values (27) 32
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
97.0%
Space Separator 2
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 8
 
12.5%
영 6
 
9.4%
산 5
 
7.8%
진 3
 
4.7%
수 2
 
3.1%
류 2
 
3.1%
서 2
 
3.1%
해 2
 
3.1%
남 2
 
3.1%
섬 2
 
3.1%
Other values (26) 30
46.9%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
97.0%
Common 2
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 8
 
12.5%
영 6
 
9.4%
산 5
 
7.8%
진 3
 
4.7%
수 2
 
3.1%
류 2
 
3.1%
서 2
 
3.1%
해 2
 
3.1%
남 2
 
3.1%
섬 2
 
3.1%
Other values (26) 30
46.9%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
97.0%
ASCII 2
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
강 8
 
12.5%
영 6
 
9.4%
산 5
 
7.8%
진 3
 
4.7%
수 2
 
3.1%
류 2
 
3.1%
서 2
 
3.1%
해 2
 
3.1%
남 2
 
3.1%
섬 2
 
3.1%
Other values (26) 30
46.9%
ASCII
ValueCountFrequency (%)
2
100.0%

방류수역_소권역
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing9
Missing (%)39.1%
Memory size312.0 B
2024-03-15T03:16:28.998495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.2857143
Min length2

Characters and Unicode

Total characters46
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row영산강하구언
2nd row여수시
3rd row담양천
4th row곡성읍
5th row섬진강
ValueCountFrequency (%)
영산강하구언 1
 
7.1%
여수시 1
 
7.1%
담양천 1
 
7.1%
곡성읍 1
 
7.1%
섬진강 1
 
7.1%
남해 1
 
7.1%
강진만 1
 
7.1%
해남방조제 1
 
7.1%
태봉천 1
 
7.1%
함평천 1
 
7.1%
Other values (4) 4
28.6%
2024-03-15T03:16:30.107876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 4
 
8.7%
강 4
 
8.7%
해 3
 
6.5%
남 2
 
4.3%
진 2
 
4.3%
제 1
 
2.2%
태 1
 
2.2%
봉 1
 
2.2%
함 1
 
2.2%
평 1
 
2.2%
Other values (26) 26
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 4
 
8.7%
강 4
 
8.7%
해 3
 
6.5%
남 2
 
4.3%
진 2
 
4.3%
제 1
 
2.2%
태 1
 
2.2%
봉 1
 
2.2%
함 1
 
2.2%
평 1
 
2.2%
Other values (26) 26
56.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 4
 
8.7%
강 4
 
8.7%
해 3
 
6.5%
남 2
 
4.3%
진 2
 
4.3%
제 1
 
2.2%
태 1
 
2.2%
봉 1
 
2.2%
함 1
 
2.2%
평 1
 
2.2%
Other values (26) 26
56.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 4
 
8.7%
강 4
 
8.7%
해 3
 
6.5%
남 2
 
4.3%
진 2
 
4.3%
제 1
 
2.2%
태 1
 
2.2%
봉 1
 
2.2%
함 1
 
2.2%
평 1
 
2.2%
Other values (26) 26
56.5%

운영주체
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size312.0 B
자체
8 
민간위탁
8 
자체(직영)
6 
직영
1 

Length

Max length6
Median length4
Mean length3.7391304
Min length2

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row자체
2nd row민간위탁
3rd row자체
4th row민간위탁
5th row자체

Common Values

ValueCountFrequency (%)
자체 8
34.8%
민간위탁 8
34.8%
자체(직영) 6
26.1%
직영 1
 
4.3%

Length

2024-03-15T03:16:30.736901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:16:31.087190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체 8
34.8%
민간위탁 8
34.8%
자체(직영 6
26.1%
직영 1
 
4.3%

직원총수_명
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7826087
Minimum0
Maximum47
Zeros13
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T03:16:31.448090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile13
Maximum47
Range47
Interquartile range (IQR)2

Descriptive statistics

Standard deviation10.126278
Coefficient of variation (CV)2.6770619
Kurtosis16.461289
Mean3.7826087
Median Absolute Deviation (MAD)0
Skewness3.9071903
Sum87
Variance102.5415
MonotonicityNot monotonic
2024-03-15T03:16:31.838856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 13
56.5%
1 4
 
17.4%
3 2
 
8.7%
13 2
 
8.7%
47 1
 
4.3%
4 1
 
4.3%
ValueCountFrequency (%)
0 13
56.5%
1 4
 
17.4%
3 2
 
8.7%
4 1
 
4.3%
13 2
 
8.7%
47 1
 
4.3%
ValueCountFrequency (%)
47 1
 
4.3%
13 2
 
8.7%
4 1
 
4.3%
3 2
 
8.7%
1 4
 
17.4%
0 13
56.5%

Sample

시군시설명소재지전화번호준공일가동개시일사업비_백만원시설용량(세제곱미터_일)처리량(세제곱미터_일)가동일수(일_년)처리공법연계처리장명연계처리량(세제곱미터_일)유입수질(mg_L 개_mL)_BOD유입수질(mg_L 개_mL)_TOC유입수질(mg_L 개_mL)_SS유입수질(mg_L 개_mL)_T N유입수질(mg_L 개_mL)_T P유입수질(mg_L 개_mL)_대장균수방류수질(m_L 개_mL)_BOD방류수질(mg_L 개_mL)_TOC방류수질(mg_L 개_mL)_SS방류수질(mg_L 개_mL)_T N방류수질(mg_L 개_mL)_T P방류수질(mg_L 개_mL)_대장균수방류수역_수계방류수역_지류방류수역_중권역방류수역_소권역운영주체직원총수_명
0목포시북항분뇨처리시설전라남도 목포시 청호로 220번길33(연산동)061-270-83652004-03-302005-04-09024056.3300전처리북항하수처리장56.33443.20.04935.9390.99548.9442600000.00.00.00.00.00영산강연안지류영산강하구언영산강하구언자체0
1여수시분뇨전처리시설전라남도 여수시 신월로 284-1(웅천동)061-643-94962005-01-012005-01-010330140.3356전처리여수공공하수처리시설126.36578.50.05757.6395.918102.2422632693.80.03.18.180.3533섬진강남해서부여수시여수시민간위탁47
2순천시분뇨 공공처리시설전라남도 순천시 강변로 77061-749-65402002-06-182002-06-18100030051.0265전처리 후 하수연계처리순천공공하수처리시설36.65853.00.010141.0889.0167.0221355853.00.010141.0889.0167.022135<NA><NA><NA><NA>자체0
3나주시나주 분뇨처리장전라남도 나주시 가야길 210061-820-82011990-03-011990-03-012167100118.6243액상부식법나주하수118.65081.41506.75484.0635.298115.31408.540.528.031.5412.7050<NA><NA><NA><NA>민간위탁3
4광양시태인분뇨처리시설전라남도 광양시 산업로 125061-797-49361993-02-261993-02-2621135035.0365액상부식태인공공폐수처리시설35.0969.80.04524.7203.536.3378111.70.02.36.50.2133섬진강남해권수계남해(해양방류)남해서부<NA>자체0
5담양군담양군 분뇨처리시설전라남도 담양군 담양읍 강쟁길 49-68061-380-29271999-09-011999-10-0117005015.1247HBR-II 공법담양공공하수처리시설18.011388.40.014987.92220.2361.5251720113.30.01365.682.441.916426영산강담양천영산강상류담양천자체(직영)0
6곡성군곡성위생처리장전라남도 곡성군 오곡면 곡고로 54-8061-360-81791997-03-151997-05-102513029.3365액상부식법곡성20.5139.30.0112.895.83339.48139120100.50.045.225.32520.11412000섬진강묘천섬진곡성곡성읍자체0
7구례군분뇨및가축분뇨공공처리시설전라남도 구례군 마산면 섬진강대로 5363061-780-81412000-10-292000-10-3002511.1145액상부식법공공하수처리시설17.22760.80.03588.3375.689.125649257.80.0205.1370.76.6149섬진강(남해)하수연계처리<NA><NA>민간위탁3
8고흥군분뇨처리장전라남도 고흥군 도덕면 신양리 고흥로 689-122061-830-53281996-07-011996-08-0109525.0365한외여과막<NA>0.25367.00.06281.2625.187129.2871925836.40.011.627.6194167.015남해섬진강영산강섬진강직영0
9보성군위생처리장전라남도 보성군 미력면 덕림리 792061-853-02711997-08-312000-06-03398110019.0249액상부식법보성공공하수처리시설17.02785.22457.211352.81056.998153.712058.352.1247.950.88816.2070<NA>하수연계<NA><NA>민간위탁1
시군시설명소재지전화번호준공일가동개시일사업비_백만원시설용량(세제곱미터_일)처리량(세제곱미터_일)가동일수(일_년)처리공법연계처리장명연계처리량(세제곱미터_일)유입수질(mg_L 개_mL)_BOD유입수질(mg_L 개_mL)_TOC유입수질(mg_L 개_mL)_SS유입수질(mg_L 개_mL)_T N유입수질(mg_L 개_mL)_T P유입수질(mg_L 개_mL)_대장균수방류수질(m_L 개_mL)_BOD방류수질(mg_L 개_mL)_TOC방류수질(mg_L 개_mL)_SS방류수질(mg_L 개_mL)_T N방류수질(mg_L 개_mL)_T P방류수질(mg_L 개_mL)_대장균수방류수역_수계방류수역_지류방류수역_중권역방류수역_소권역운영주체직원총수_명
13해남군해남분뇨처리장전라남도 해남군 해남읍 용정리 950061-530-36942006-06-272003-07-0109024.0365전처리시설해남 하수처리장24.01572.90.05329.8575.163262.812291184.40.03.115.5840.713100영산강해남방조제영암방조제해남방조제자체(직영)0
14영암군대불전라남도 영암군 삼호읍 대아로 37061-470-25231997-03-311997-07-012524406.0365전처리대불0.0173.60.0425.825.7533.914209012.00.02.711.9650.05128연안(서해)서해안<NA><NA>자체(직영)0
15무안군무안분뇨처리시설전라남도 무안군 무안읍 평용리 128-1061-450-41321993-12-311993-12-3137914031.4365액상부식법(질소,인제거고도처리)단독0.01552.51927.12984.6549.89158.8362326081.823.42.913.1040.2492서해사마천와탄천태봉천자체0
16함평군분뇨공공처리시설전라남도 함평군 엄다면 영산로 3416-88061-320-28362000-11-252000-11-250400.0249액상부식법함평공공하수처리시설0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>영산강영산강 지류영산강 하류함평천자체(직영)13
17영광군영광군 분뇨처리시설전라남도 영광읍 와룡로 396061-350-52891985-12-011989-03-0130516547.6250액상부식법영광군 분뇨처리시설27.7125.0<NA>105.538.6584.762410094.2<NA>2.87.0110.30239연안와탄천와탄천와탄천자체(직영)0
18장성군분뇨처리시설전라남도 장성군 황룡면 신호리 716-16061-390-85491994-10-241994-10-2405017.6366세일바이오시스템장성공공하수처리시설19.40.00.00.00.00.0077.80.0278.6275.627.60영산강황룡강황룡강황룡강민간위탁1
19완도군완도군분뇨처리장전라남도 완도군 완도읍 청해진서로 112-64061-550-55161997-12-241997-12-2439616012.9156액상부식법<NA>0.033.30.02905.066.845.46515000.90.010.025.81.8780섬진강남해서부완도완도자체0
20진도군진도분뇨전라남도 진도군 진도읍 포산리 620061-544-67122003-03-012003-03-010304.5365협잡물처리진도읍공공하수처리장4.52436.10.0460.1580.671120.8062100003.40.01.512.110.41646연안진도천소포만담수호연안해역민간위탁13
21신안군흑산위생처리장전라남도 신안군 흑산면 예리 산4061-240-80402001-01-192001-01-19020.20자연정화법압해하수종말처리장0.00.00.00.00.00.000.00.00.00.00.00영산강<NA><NA><NA>자체0
22신안군압해위생처리장전라남도 신안군 압해읍 추섬길 313061-240-88702001-01-172001-01-1701818.0365자연정화법압해하수종말처리장0.03951.20.04851.0351.58483.2545400000000.00.00.00.00.00영산강<NA><NA><NA>자체0