Overview

Dataset statistics

Number of variables57
Number of observations353
Missing cells334
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.1 KiB
Average record size in memory493.4 B

Variable types

Categorical17
Text6
Numeric32
DateTime2

Dataset

Description충청북도 공공하수처리장 현황으로 지역, 시설명, 소재지, 용량, 처리량, 처리방법, 전화번호, 준공일, 가동개시일 등 데이터를 제공합니다
Author충청북도
URLhttps://www.data.go.kr/data/15015545/fileData.do

Alerts

시도 has constant value ""Constant
시설용량 물리적(세제곱미터-일) has constant value ""Constant
유입하수량 물리적(세제곱미터-일) has constant value ""Constant
방류량 물리적(세제곱미터-일) has constant value ""Constant
축산 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만) is highly imbalanced (95.8%)Imbalance
방류수소독방법 is highly imbalanced (70.4%)Imbalance
운영주체(자체-공기업-민간대행) is highly imbalanced (87.6%)Imbalance
안전사고건수 is highly imbalanced (97.2%)Imbalance
적용신기술 has 314 (89.0%) missing valuesMissing
전화번호 has 14 (4.0%) missing valuesMissing
지류 has 5 (1.4%) missing valuesMissing
시설용량 생물학적(세제곱미터-일) has 332 (94.1%) zerosZeros
시설용량 고도(세제곱미터-일) has 20 (5.7%) zerosZeros
유입하수량 생물학적(세제곱미터-일) has 327 (92.6%) zerosZeros
유입하수량 고도(세제곱미터-일) has 25 (7.1%) zerosZeros
방류량 생물학적(세제곱미터-일) has 328 (92.9%) zerosZeros
방류량 고도(세제곱미터-일) has 26 (7.4%) zerosZeros
유입 화학적 산소 요구량(COD) has 182 (51.6%) zerosZeros
방류 화학적 산소 요구량(COD) has 182 (51.6%) zerosZeros
방류총대장균군수 has 32 (9.1%) zerosZeros
분뇨 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만) has 341 (96.6%) zerosZeros
침출수 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만) has 344 (97.5%) zerosZeros
기타 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만) has 346 (98.0%) zerosZeros
사업비(백만원) has 5 (1.4%) zerosZeros
재생에너지이용률(퍼센트) has 309 (87.5%) zerosZeros
하수처리량당CO2배출량(kgCO2-세제곱미터) has 309 (87.5%) zerosZeros
위탁비용(백만원-년) has 130 (36.8%) zerosZeros
직원총수(명) has 248 (70.3%) zerosZeros

Reproduction

Analysis started2023-12-12 07:06:48.641631
Analysis finished2023-12-12 07:06:49.639625
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
충청북도
353 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 353
100.0%

Length

2023-12-12T16:06:49.722310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:06:49.853561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 353
100.0%

구군
Categorical

Distinct11
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
충주시
67 
옥천군
48 
청주시
42 
제천시
42 
단양군
38 
Other values (6)
116 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 67
19.0%
옥천군 48
13.6%
청주시 42
11.9%
제천시 42
11.9%
단양군 38
10.8%
영동군 35
9.9%
괴산군 28
7.9%
보은군 26
 
7.4%
진천군 14
 
4.0%
음성군 12
 
3.4%

Length

2023-12-12T16:06:49.953760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충주시 67
19.0%
옥천군 48
13.6%
청주시 42
11.9%
제천시 42
11.9%
단양군 38
10.8%
영동군 35
9.9%
괴산군 28
7.9%
보은군 26
 
7.4%
진천군 14
 
4.0%
음성군 12
 
3.4%

행정구역명
Categorical

Distinct11
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
충주시
67 
옥천군
48 
청주시
42 
제천시
42 
단양군
38 
Other values (6)
116 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 67
19.0%
옥천군 48
13.6%
청주시 42
11.9%
제천시 42
11.9%
단양군 38
10.8%
영동군 35
9.9%
괴산군 28
7.9%
보은군 26
 
7.4%
진천군 14
 
4.0%
음성군 12
 
3.4%

Length

2023-12-12T16:06:50.098077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충주시 67
19.0%
옥천군 48
13.6%
청주시 42
11.9%
제천시 42
11.9%
단양군 38
10.8%
영동군 35
9.9%
괴산군 28
7.9%
보은군 26
 
7.4%
진천군 14
 
4.0%
음성군 12
 
3.4%

시설명
Text

Distinct350
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T16:06:50.451471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length2.6713881
Min length2

Characters and Unicode

Total characters943
Distinct characters202
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)98.3%

Sample

1st row청주
2nd row내수
3rd row강내
4th row오창
5th row옥산
ValueCountFrequency (%)
대소 3
 
0.8%
덕산 2
 
0.6%
감곡 2
 
0.6%
생극 2
 
0.6%
하리 2
 
0.6%
중방 2
 
0.6%
오창 2
 
0.6%
영춘 1
 
0.3%
고당 1
 
0.3%
초강 1
 
0.3%
Other values (344) 344
95.0%
2023-12-12T16:06:50.918125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 37
 
3.9%
리 32
 
3.4%
수 27
 
2.9%
곡 24
 
2.5%
동 19
 
2.0%
성 19
 
2.0%
대 19
 
2.0%
금 18
 
1.9%
사 14
 
1.5%
오 13
 
1.4%
Other values (192) 721
76.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 898
95.2%
Decimal Number 25
 
2.7%
Space Separator 9
 
1.0%
Open Punctuation 5
 
0.5%
Close Punctuation 5
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 37
 
4.1%
리 32
 
3.6%
수 27
 
3.0%
곡 24
 
2.7%
동 19
 
2.1%
성 19
 
2.1%
대 19
 
2.1%
금 18
 
2.0%
사 14
 
1.6%
오 13
 
1.4%
Other values (185) 676
75.3%
Decimal Number
ValueCountFrequency (%)
2 13
52.0%
1 10
40.0%
3 2
 
8.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 898
95.2%
Common 44
 
4.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 37
 
4.1%
리 32
 
3.6%
수 27
 
3.0%
곡 24
 
2.7%
동 19
 
2.1%
성 19
 
2.1%
대 19
 
2.1%
금 18
 
2.0%
사 14
 
1.6%
오 13
 
1.4%
Other values (185) 676
75.3%
Common
ValueCountFrequency (%)
2 13
29.5%
1 10
22.7%
9
20.5%
( 5
 
11.4%
) 5
 
11.4%
3 2
 
4.5%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 898
95.2%
ASCII 45
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 37
 
4.1%
리 32
 
3.6%
수 27
 
3.0%
곡 24
 
2.7%
동 19
 
2.1%
성 19
 
2.1%
대 19
 
2.1%
금 18
 
2.0%
사 14
 
1.6%
오 13
 
1.4%
Other values (185) 676
75.3%
ASCII
ValueCountFrequency (%)
2 13
28.9%
1 10
22.2%
9
20.0%
( 5
 
11.1%
) 5
 
11.1%
3 2
 
4.4%
B 1
 
2.2%

소재지
Text

Distinct352
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T16:06:51.328875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length19.144476
Min length1

Characters and Unicode

Total characters6758
Distinct characters222
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique351 ?
Unique (%)99.4%

Sample

1st row충청북도 청주시 흥덕구 옥산면 미호로 555 청주 공공하수처리시설
2nd row충청북도 청원군 내수4길 115
3rd row충청북도 청주시 흥덕구 강내면 탑연리 259-1
4th row충청북도 청원군 오창제방길 281 오창공공하수처리시설
5th row충청북도 청주시 흥덕구 옥산면 신촌리 292번지
ValueCountFrequency (%)
충북 101
 
6.7%
충청북도 90
 
6.0%
옥천군 41
 
2.7%
영동군 34
 
2.3%
단양군 24
 
1.6%
충주시 24
 
1.6%
보은군 23
 
1.5%
제천시 22
 
1.5%
음성군 12
 
0.8%
살미면 12
 
0.8%
Other values (784) 1120
74.5%
2023-12-12T16:06:51.964610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1482
21.9%
면 299
 
4.4%
리 295
 
4.4%
1 247
 
3.7%
- 226
 
3.3%
충 218
 
3.2%
2 210
 
3.1%
북 207
 
3.1%
군 171
 
2.5%
5 150
 
2.2%
Other values (212) 3253
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3681
54.5%
Space Separator 1482
21.9%
Decimal Number 1351
 
20.0%
Dash Punctuation 226
 
3.3%
Other Punctuation 8
 
0.1%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 299
 
8.1%
리 295
 
8.0%
충 218
 
5.9%
북 207
 
5.6%
군 171
 
4.6%
청 146
 
4.0%
지 114
 
3.1%
천 107
 
2.9%
번 105
 
2.9%
도 100
 
2.7%
Other values (196) 1919
52.1%
Decimal Number
ValueCountFrequency (%)
1 247
18.3%
2 210
15.5%
5 150
11.1%
4 140
10.4%
3 128
9.5%
6 122
9.0%
7 99
7.3%
0 91
 
6.7%
8 87
 
6.4%
9 77
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
？ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
1482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 226
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3681
54.5%
Common 3077
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 299
 
8.1%
리 295
 
8.0%
충 218
 
5.9%
북 207
 
5.6%
군 171
 
4.6%
청 146
 
4.0%
지 114
 
3.1%
천 107
 
2.9%
번 105
 
2.9%
도 100
 
2.7%
Other values (196) 1919
52.1%
Common
ValueCountFrequency (%)
1482
48.2%
1 247
 
8.0%
- 226
 
7.3%
2 210
 
6.8%
5 150
 
4.9%
4 140
 
4.5%
3 128
 
4.2%
6 122
 
4.0%
7 99
 
3.2%
0 91
 
3.0%
Other values (6) 182
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3681
54.5%
ASCII 3075
45.5%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1482
48.2%
1 247
 
8.0%
- 226
 
7.3%
2 210
 
6.8%
5 150
 
4.9%
4 140
 
4.6%
3 128
 
4.2%
6 122
 
4.0%
7 99
 
3.2%
0 91
 
3.0%
Other values (5) 180
 
5.9%
Hangul
ValueCountFrequency (%)
면 299
 
8.1%
리 295
 
8.0%
충 218
 
5.9%
북 207
 
5.6%
군 171
 
4.6%
청 146
 
4.0%
지 114
 
3.1%
천 107
 
2.9%
번 105
 
2.9%
도 100
 
2.7%
Other values (196) 1919
52.1%
None
ValueCountFrequency (%)
？ 2
100.0%

시설용량(500세제곱미터-일 이상-미만)
Real number (ℝ)

Distinct85
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1818.5694
Minimum10
Maximum280000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:52.157439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile20
Q140
median60
Q3140
95-th percentile4000
Maximum280000
Range279990
Interquartile range (IQR)100

Descriptive statistics

Standard deviation15994.152
Coefficient of variation (CV)8.7949088
Kurtosis263.65697
Mean1818.5694
Median Absolute Deviation (MAD)30
Skewness15.544871
Sum641955
Variance2.558129 × 108
MonotonicityNot monotonic
2023-12-12T16:06:52.308806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 46
 
13.0%
60 32
 
9.1%
30 26
 
7.4%
40 22
 
6.2%
100 17
 
4.8%
20 16
 
4.5%
35 15
 
4.2%
70 14
 
4.0%
45 9
 
2.5%
25 9
 
2.5%
Other values (75) 147
41.6%
ValueCountFrequency (%)
10 5
 
1.4%
11 1
 
0.3%
12 1
 
0.3%
15 5
 
1.4%
18 1
 
0.3%
20 16
4.5%
23 1
 
0.3%
24 1
 
0.3%
25 9
 
2.5%
30 26
7.4%
ValueCountFrequency (%)
280000 1
0.3%
75000 1
0.3%
70000 1
0.3%
25000 1
0.3%
18000 1
0.3%
16600 1
0.3%
15200 1
0.3%
14000 1
0.3%
13500 1
0.3%
8000 2
0.6%

시설용량 물리적(세제곱미터-일)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
353 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 353
100.0%

Length

2023-12-12T16:06:52.442927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:06:52.537684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 353
100.0%

시설용량 생물학적(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.643059
Minimum0
Maximum14000
Zeros332
Zeros (%)94.1%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:52.620408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile21.2
Maximum14000
Range14000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation776.32673
Coefficient of variation (CV)13.467827
Kurtosis299.52882
Mean57.643059
Median Absolute Deviation (MAD)0
Skewness16.929488
Sum20348
Variance602683.19
MonotonicityNot monotonic
2023-12-12T16:06:52.776316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 332
94.1%
30 3
 
0.8%
100 3
 
0.8%
25 2
 
0.6%
50 2
 
0.6%
10 2
 
0.6%
1000 1
 
0.3%
500 1
 
0.3%
150 1
 
0.3%
35 1
 
0.3%
Other values (5) 5
 
1.4%
ValueCountFrequency (%)
0 332
94.1%
10 2
 
0.6%
20 1
 
0.3%
23 1
 
0.3%
25 2
 
0.6%
30 3
 
0.8%
35 1
 
0.3%
50 2
 
0.6%
60 1
 
0.3%
100 3
 
0.8%
ValueCountFrequency (%)
14000 1
 
0.3%
4000 1
 
0.3%
1000 1
 
0.3%
500 1
 
0.3%
150 1
 
0.3%
100 3
0.8%
60 1
 
0.3%
50 2
0.6%
35 1
 
0.3%
30 3
0.8%

시설용량 고도(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct84
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1760.9263
Minimum0
Maximum280000
Zeros20
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:52.925936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q135
median60
Q3130
95-th percentile3580
Maximum280000
Range280000
Interquartile range (IQR)95

Descriptive statistics

Standard deviation15980.249
Coefficient of variation (CV)9.0749104
Kurtosis264.81279
Mean1760.9263
Median Absolute Deviation (MAD)30
Skewness15.59503
Sum621607
Variance2.5536835 × 108
MonotonicityNot monotonic
2023-12-12T16:06:53.081145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 44
 
12.5%
60 31
 
8.8%
30 23
 
6.5%
40 22
 
6.2%
0 20
 
5.7%
20 15
 
4.2%
70 14
 
4.0%
100 14
 
4.0%
35 14
 
4.0%
45 9
 
2.5%
Other values (74) 147
41.6%
ValueCountFrequency (%)
0 20
5.7%
10 3
 
0.8%
11 1
 
0.3%
12 1
 
0.3%
15 5
 
1.4%
18 1
 
0.3%
20 15
4.2%
24 1
 
0.3%
25 7
 
2.0%
30 23
6.5%
ValueCountFrequency (%)
280000 1
 
0.3%
75000 1
 
0.3%
70000 1
 
0.3%
25000 1
 
0.3%
18000 1
 
0.3%
16600 1
 
0.3%
15200 1
 
0.3%
13500 1
 
0.3%
8000 2
0.6%
7000 3
0.8%

유입하수량(500세제곱미터-일 이상-미만)
Real number (ℝ)

Distinct308
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1624.3759
Minimum1
Maximum289244.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:53.214641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.2
Q122.6
median39.7
Q388.7
95-th percentile2154.1
Maximum289244.4
Range289243.4
Interquartile range (IQR)66.1

Descriptive statistics

Standard deviation16210.055
Coefficient of variation (CV)9.9792509
Kurtosis284.76791
Mean1624.3759
Median Absolute Deviation (MAD)21.6
Skewness16.312085
Sum573404.7
Variance2.6276588 × 108
MonotonicityNot monotonic
2023-12-12T16:06:53.349729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.6 4
 
1.1%
14.1 3
 
0.8%
27.8 3
 
0.8%
76.7 3
 
0.8%
33.3 2
 
0.6%
41.6 2
 
0.6%
70.6 2
 
0.6%
21.4 2
 
0.6%
5.2 2
 
0.6%
203.7 2
 
0.6%
Other values (298) 328
92.9%
ValueCountFrequency (%)
1.0 1
0.3%
2.4 2
0.6%
2.7 1
0.3%
3.8 1
0.3%
4.0 1
0.3%
5.0 1
0.3%
5.2 2
0.6%
5.3 1
0.3%
6.0 2
0.6%
6.9 1
0.3%
ValueCountFrequency (%)
289244.4 1
0.3%
65870.9 1
0.3%
64529.0 1
0.3%
21205.9 1
0.3%
14657.8 1
0.3%
12744.2 1
0.3%
8852.4 1
0.3%
8030.1 1
0.3%
6344.7 1
0.3%
6052.7 1
0.3%

유입하수량 물리적(세제곱미터-일)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
353 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 353
100.0%

Length

2023-12-12T16:06:53.475184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:06:53.595840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 353
100.0%

유입하수량 생물학적(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.814164
Minimum0
Maximum6052.7
Zeros327
Zeros (%)92.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:53.686376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15.66
Maximum6052.7
Range6052.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation360.97347
Coefficient of variation (CV)11.714531
Kurtosis234.03452
Mean30.814164
Median Absolute Deviation (MAD)0
Skewness14.866715
Sum10877.4
Variance130301.85
MonotonicityNot monotonic
2023-12-12T16:06:53.817454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 327
92.6%
2.4 2
 
0.6%
18.1 2
 
0.6%
30.4 1
 
0.3%
7.1 1
 
0.3%
11.4 1
 
0.3%
73.2 1
 
0.3%
261.8 1
 
0.3%
52.2 1
 
0.3%
3000.0 1
 
0.3%
Other values (15) 15
 
4.2%
ValueCountFrequency (%)
0.0 327
92.6%
2.4 2
 
0.6%
6.0 1
 
0.3%
7.1 1
 
0.3%
11.4 1
 
0.3%
14.1 1
 
0.3%
14.4 1
 
0.3%
14.9 1
 
0.3%
16.8 1
 
0.3%
18.1 2
 
0.6%
ValueCountFrequency (%)
6052.7 1
0.3%
3000.0 1
0.3%
566.8 1
0.3%
370.8 1
0.3%
261.8 1
0.3%
139.5 1
0.3%
73.2 1
0.3%
69.1 1
0.3%
52.2 1
0.3%
37.8 1
0.3%

유입하수량 고도(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct290
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1593.5618
Minimum0
Maximum289244.4
Zeros25
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:53.952860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.1
median37.7
Q379.3
95-th percentile1897.58
Maximum289244.4
Range289244.4
Interquartile range (IQR)58.2

Descriptive statistics

Standard deviation16208.041
Coefficient of variation (CV)10.170952
Kurtosis285.03651
Mean1593.5618
Median Absolute Deviation (MAD)22.1
Skewness16.323809
Sum562527.3
Variance2.6270058 × 108
MonotonicityNot monotonic
2023-12-12T16:06:54.114870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
 
7.1%
33.6 3
 
0.8%
27.8 3
 
0.8%
76.7 3
 
0.8%
34.8 2
 
0.6%
33.3 2
 
0.6%
34.7 2
 
0.6%
203.7 2
 
0.6%
70.6 2
 
0.6%
16.3 2
 
0.6%
Other values (280) 307
87.0%
ValueCountFrequency (%)
0.0 25
7.1%
1.0 1
 
0.3%
2.7 1
 
0.3%
3.8 1
 
0.3%
4.0 1
 
0.3%
5.0 1
 
0.3%
5.2 2
 
0.6%
5.3 1
 
0.3%
6.0 1
 
0.3%
6.9 1
 
0.3%
ValueCountFrequency (%)
289244.4 1
0.3%
65870.9 1
0.3%
64529.0 1
0.3%
21205.9 1
0.3%
14657.8 1
0.3%
12744.2 1
0.3%
8852.4 1
0.3%
8030.1 1
0.3%
6344.7 1
0.3%
5896.5 1
0.3%

방류량(500세제곱미터-일 이상-미만)
Real number (ℝ)

Distinct307
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1500.2272
Minimum0
Maximum263182.9
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:54.545981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q122.6
median39.6
Q386.2
95-th percentile1988.34
Maximum263182.9
Range263182.9
Interquartile range (IQR)63.6

Descriptive statistics

Standard deviation14752.008
Coefficient of variation (CV)9.8331828
Kurtosis284.44957
Mean1500.2272
Median Absolute Deviation (MAD)22
Skewness16.295763
Sum529580.2
Variance2.1762175 × 108
MonotonicityNot monotonic
2023-12-12T16:06:54.689104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.6 4
 
1.1%
14.1 3
 
0.8%
27.8 3
 
0.8%
76.7 3
 
0.8%
33.3 2
 
0.6%
41.6 2
 
0.6%
70.6 2
 
0.6%
21.4 2
 
0.6%
84.7 2
 
0.6%
5.2 2
 
0.6%
Other values (297) 328
92.9%
ValueCountFrequency (%)
0.0 1
0.3%
1.0 1
0.3%
2.4 2
0.6%
2.7 1
0.3%
3.8 1
0.3%
4.0 1
0.3%
5.0 1
0.3%
5.2 2
0.6%
5.3 1
0.3%
6.0 2
0.6%
ValueCountFrequency (%)
263182.9 1
0.3%
60364.0 1
0.3%
57677.7 1
0.3%
20229.7 1
0.3%
13640.1 1
0.3%
12718.7 1
0.3%
8852.4 1
0.3%
7698.3 1
0.3%
5922.6 1
0.3%
5733.7 1
0.3%

방류량 물리적(세제곱미터-일)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
353 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 353
100.0%

Length

2023-12-12T16:06:54.810447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:06:54.927221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 353
100.0%

방류량 생물학적(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.535694
Minimum0
Maximum5209.7
Zeros328
Zeros (%)92.9%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:55.012336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14.6
Maximum5209.7
Range5209.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation279.29609
Coefficient of variation (CV)14.296707
Kurtosis341.61216
Mean19.535694
Median Absolute Deviation (MAD)0
Skewness18.354182
Sum6896.1
Variance78006.304
MonotonicityNot monotonic
2023-12-12T16:06:55.126436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 328
92.9%
2.4 2
 
0.6%
18.1 2
 
0.6%
33.6 1
 
0.3%
7.1 1
 
0.3%
11.4 1
 
0.3%
73.2 1
 
0.3%
261.8 1
 
0.3%
52.2 1
 
0.3%
37.8 1
 
0.3%
Other values (14) 14
 
4.0%
ValueCountFrequency (%)
0.0 328
92.9%
2.4 2
 
0.6%
6.0 1
 
0.3%
7.1 1
 
0.3%
11.4 1
 
0.3%
14.1 1
 
0.3%
14.4 1
 
0.3%
14.9 1
 
0.3%
16.8 1
 
0.3%
18.1 2
 
0.6%
ValueCountFrequency (%)
5209.7 1
0.3%
495.3 1
0.3%
322.4 1
0.3%
261.8 1
0.3%
121.1 1
0.3%
73.2 1
0.3%
69.1 1
0.3%
52.2 1
0.3%
37.8 1
0.3%
33.6 1
0.3%

방류량 고도(세제곱미터-일)
Real number (ℝ)

ZEROS 

Distinct288
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1480.6915
Minimum0
Maximum263182.9
Zeros26
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:55.251911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.1
median37.7
Q379.3
95-th percentile1777.4
Maximum263182.9
Range263182.9
Interquartile range (IQR)58.2

Descriptive statistics

Standard deviation14751.331
Coefficient of variation (CV)9.9624606
Kurtosis284.58971
Mean1480.6915
Median Absolute Deviation (MAD)22.1
Skewness16.301947
Sum522684.1
Variance2.1760176 × 108
MonotonicityNot monotonic
2023-12-12T16:06:55.382145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 26
 
7.4%
27.8 3
 
0.8%
76.7 3
 
0.8%
33.6 3
 
0.8%
9.2 2
 
0.6%
31.2 2
 
0.6%
21.4 2
 
0.6%
64.1 2
 
0.6%
14.1 2
 
0.6%
16.3 2
 
0.6%
Other values (278) 306
86.7%
ValueCountFrequency (%)
0.0 26
7.4%
1.0 1
 
0.3%
2.7 1
 
0.3%
3.8 1
 
0.3%
4.0 1
 
0.3%
5.0 1
 
0.3%
5.2 2
 
0.6%
5.3 1
 
0.3%
6.0 1
 
0.3%
6.9 1
 
0.3%
ValueCountFrequency (%)
263182.9 1
0.3%
60364.0 1
0.3%
57677.7 1
0.3%
20229.7 1
0.3%
13640.1 1
0.3%
12718.7 1
0.3%
8852.4 1
0.3%
7698.3 1
0.3%
5922.6 1
0.3%
5733.7 1
0.3%

유입 생화학적 산소요구량(BOD)
Real number (ℝ)

Distinct323
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean146.67507
Minimum0
Maximum356.7
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:55.508027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile52.62
Q199.7
median140.7
Q3177.9
95-th percentile284.04
Maximum356.7
Range356.7
Interquartile range (IQR)78.2

Descriptive statistics

Standard deviation66.513866
Coefficient of variation (CV)0.45347764
Kurtosis0.60062182
Mean146.67507
Median Absolute Deviation (MAD)39.2
Skewness0.73144642
Sum51776.3
Variance4424.0943
MonotonicityNot monotonic
2023-12-12T16:06:55.640654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147.8 3
 
0.8%
130.4 2
 
0.6%
180.7 2
 
0.6%
164.3 2
 
0.6%
168.3 2
 
0.6%
227.5 2
 
0.6%
126.7 2
 
0.6%
120.9 2
 
0.6%
122.5 2
 
0.6%
356.7 2
 
0.6%
Other values (313) 332
94.1%
ValueCountFrequency (%)
0.0 1
0.3%
21.4 1
0.3%
27.5 1
0.3%
31.8 1
0.3%
34.0 1
0.3%
34.5 1
0.3%
34.7 1
0.3%
35.7 1
0.3%
37.3 1
0.3%
39.2 1
0.3%
ValueCountFrequency (%)
356.7 2
0.6%
343.3 1
0.3%
338.1 1
0.3%
335.4 1
0.3%
334.2 1
0.3%
322.8 1
0.3%
319.3 1
0.3%
314.8 1
0.3%
309.3 1
0.3%
308.6 1
0.3%

방류 생물학적 산소 요구량(BOD)
Real number (ℝ)

Distinct63
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3240793
Minimum0
Maximum9.1
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:55.857603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q11.3
median2
Q33.1
95-th percentile5.5
Maximum9.1
Range9.1
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.5491615
Coefficient of variation (CV)0.66657
Kurtosis2.8241315
Mean2.3240793
Median Absolute Deviation (MAD)0.9
Skewness1.4428055
Sum820.4
Variance2.3999015
MonotonicityNot monotonic
2023-12-12T16:06:56.016589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.6 20
 
5.7%
1.5 15
 
4.2%
2.1 12
 
3.4%
1.0 12
 
3.4%
1.3 12
 
3.4%
1.2 11
 
3.1%
1.8 10
 
2.8%
1.7 10
 
2.8%
2.5 10
 
2.8%
2.3 10
 
2.8%
Other values (53) 231
65.4%
ValueCountFrequency (%)
0.0 1
 
0.3%
0.2 6
1.7%
0.3 9
2.5%
0.4 4
 
1.1%
0.5 3
 
0.8%
0.6 10
2.8%
0.7 6
1.7%
0.8 10
2.8%
0.9 6
1.7%
1.0 12
3.4%
ValueCountFrequency (%)
9.1 1
 
0.3%
8.6 1
 
0.3%
8.2 1
 
0.3%
7.8 1
 
0.3%
7.7 1
 
0.3%
6.8 2
0.6%
6.7 1
 
0.3%
6.6 2
0.6%
6.5 3
0.8%
6.4 1
 
0.3%

유입 화학적 산소 요구량(COD)
Real number (ℝ)

ZEROS 

Distinct157
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.233144
Minimum0
Maximum167.6
Zeros182
Zeros (%)51.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:56.188972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q352.2
95-th percentile110.9
Maximum167.6
Range167.6
Interquartile range (IQR)52.2

Descriptive statistics

Standard deviation39.335504
Coefficient of variation (CV)1.3010722
Kurtosis1.0728211
Mean30.233144
Median Absolute Deviation (MAD)0
Skewness1.2818158
Sum10672.3
Variance1547.2819
MonotonicityNot monotonic
2023-12-12T16:06:56.339468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 182
51.6%
40.4 3
 
0.8%
48.8 2
 
0.6%
49.6 2
 
0.6%
107.4 2
 
0.6%
54.5 2
 
0.6%
69.8 2
 
0.6%
47.1 2
 
0.6%
57.8 2
 
0.6%
80.2 2
 
0.6%
Other values (147) 152
43.1%
ValueCountFrequency (%)
0.0 182
51.6%
9.8 1
 
0.3%
10.5 1
 
0.3%
10.8 1
 
0.3%
13.5 1
 
0.3%
15.8 1
 
0.3%
16.2 1
 
0.3%
17.0 2
 
0.6%
19.2 1
 
0.3%
19.8 1
 
0.3%
ValueCountFrequency (%)
167.6 1
0.3%
166.1 1
0.3%
163.1 1
0.3%
161.4 1
0.3%
160.9 1
0.3%
141.4 1
0.3%
137.8 1
0.3%
130.8 1
0.3%
127.3 1
0.3%
125.6 1
0.3%

방류 화학적 산소 요구량(COD)
Real number (ℝ)

ZEROS 

Distinct57
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4439093
Minimum0
Maximum9.3
Zeros182
Zeros (%)51.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:56.505488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.9
95-th percentile6.94
Maximum9.3
Range9.3
Interquartile range (IQR)4.9

Descriptive statistics

Standard deviation2.7013514
Coefficient of variation (CV)1.1053403
Kurtosis-1.3049746
Mean2.4439093
Median Absolute Deviation (MAD)0
Skewness0.44959358
Sum862.7
Variance7.2972994
MonotonicityNot monotonic
2023-12-12T16:06:56.660885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 182
51.6%
5.1 8
 
2.3%
4.8 7
 
2.0%
4.4 7
 
2.0%
4.0 6
 
1.7%
5.4 6
 
1.7%
5.3 6
 
1.7%
5.5 5
 
1.4%
5.9 5
 
1.4%
6.2 5
 
1.4%
Other values (47) 116
32.9%
ValueCountFrequency (%)
0.0 182
51.6%
1.9 1
 
0.3%
2.3 1
 
0.3%
2.6 1
 
0.3%
2.7 1
 
0.3%
2.8 1
 
0.3%
2.9 2
 
0.6%
3.0 3
 
0.8%
3.1 2
 
0.6%
3.2 2
 
0.6%
ValueCountFrequency (%)
9.3 1
 
0.3%
9.1 1
 
0.3%
8.9 1
 
0.3%
8.7 1
 
0.3%
7.8 1
 
0.3%
7.6 1
 
0.3%
7.5 1
 
0.3%
7.3 1
 
0.3%
7.2 3
0.8%
7.1 4
1.1%

유입 부유물질량(SS)
Real number (ℝ)

Distinct316
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean151.35751
Minimum0
Maximum727.2
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:56.821704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53.3
Q197.9
median149.1
Q3182.1
95-th percentile260.58
Maximum727.2
Range727.2
Interquartile range (IQR)84.2

Descriptive statistics

Standard deviation79.167956
Coefficient of variation (CV)0.52305272
Kurtosis11.230377
Mean151.35751
Median Absolute Deviation (MAD)41.8
Skewness2.2953631
Sum53429.2
Variance6267.5652
MonotonicityNot monotonic
2023-12-12T16:06:56.992083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
168.8 3
 
0.8%
107.8 2
 
0.6%
174.9 2
 
0.6%
125.9 2
 
0.6%
172.2 2
 
0.6%
84.8 2
 
0.6%
116.7 2
 
0.6%
181.1 2
 
0.6%
177.1 2
 
0.6%
155.3 2
 
0.6%
Other values (306) 332
94.1%
ValueCountFrequency (%)
0.0 1
0.3%
17.4 1
0.3%
28.8 1
0.3%
34.6 1
0.3%
35.7 1
0.3%
36.1 1
0.3%
36.3 1
0.3%
37.7 1
0.3%
42.9 1
0.3%
43.3 1
0.3%
ValueCountFrequency (%)
727.2 1
0.3%
551.8 1
0.3%
500.8 1
0.3%
462.6 1
0.3%
462.0 1
0.3%
433.0 1
0.3%
416.0 1
0.3%
369.2 1
0.3%
328.9 1
0.3%
308.9 1
0.3%

방류 부유물질량(SS)
Real number (ℝ)

Distinct65
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3776204
Minimum0
Maximum8.6
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:57.141443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q11.2
median2.1
Q33.1
95-th percentile5.54
Maximum8.6
Range8.6
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.5982707
Coefficient of variation (CV)0.67221443
Kurtosis1.5946189
Mean2.3776204
Median Absolute Deviation (MAD)1
Skewness1.1677914
Sum839.3
Variance2.5544693
MonotonicityNot monotonic
2023-12-12T16:06:57.307952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9 18
 
5.1%
1.7 17
 
4.8%
2.8 14
 
4.0%
1.8 13
 
3.7%
0.6 13
 
3.7%
1.0 12
 
3.4%
1.4 12
 
3.4%
0.3 11
 
3.1%
2.3 10
 
2.8%
2.7 10
 
2.8%
Other values (55) 223
63.2%
ValueCountFrequency (%)
0.0 1
 
0.3%
0.1 2
 
0.6%
0.2 2
 
0.6%
0.3 11
3.1%
0.4 5
 
1.4%
0.5 4
 
1.1%
0.6 13
3.7%
0.7 5
 
1.4%
0.8 10
2.8%
0.9 18
5.1%
ValueCountFrequency (%)
8.6 2
0.6%
8.3 1
0.3%
7.8 1
0.3%
7.3 1
0.3%
7.2 1
0.3%
6.5 1
0.3%
6.4 1
0.3%
6.2 1
0.3%
6.1 2
0.6%
6.0 1
0.3%

유입 총질소(T-N)
Real number (ℝ)

Distinct338
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.756714
Minimum0
Maximum69.24
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:57.520117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.91
Q128.05
median35.93
Q341.61
95-th percentile55.688
Maximum69.24
Range69.24
Interquartile range (IQR)13.56

Descriptive statistics

Standard deviation10.935438
Coefficient of variation (CV)0.30582895
Kurtosis0.54214155
Mean35.756714
Median Absolute Deviation (MAD)6.44
Skewness0.25731841
Sum12622.12
Variance119.58381
MonotonicityNot monotonic
2023-12-12T16:06:57.674443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.53 2
 
0.6%
41.71 2
 
0.6%
33.41 2
 
0.6%
30.86 2
 
0.6%
26.21 2
 
0.6%
27.19 2
 
0.6%
25.51 2
 
0.6%
12.39 2
 
0.6%
39.51 2
 
0.6%
28.99 2
 
0.6%
Other values (328) 333
94.3%
ValueCountFrequency (%)
0.0 1
0.3%
8.22 1
0.3%
9.0 1
0.3%
12.39 2
0.6%
15.1 1
0.3%
15.19 1
0.3%
15.41 1
0.3%
15.48 1
0.3%
15.95 1
0.3%
16.22 1
0.3%
ValueCountFrequency (%)
69.24 1
0.3%
68.87 1
0.3%
68.25 1
0.3%
67.28 1
0.3%
65.99 1
0.3%
62.11 1
0.3%
61.12 1
0.3%
60.53 1
0.3%
60.0 1
0.3%
59.17 1
0.3%

방류 총질소(T-N)
Real number (ℝ)

Distinct321
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9586969
Minimum0
Maximum27.94
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:57.850217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.52
Q16.64
median9.41
Q312.92
95-th percentile17.164
Maximum27.94
Range27.94
Interquartile range (IQR)6.28

Descriptive statistics

Standard deviation4.5702948
Coefficient of variation (CV)0.45892498
Kurtosis1.013027
Mean9.9586969
Median Absolute Deviation (MAD)3.16
Skewness0.76247527
Sum3515.42
Variance20.887594
MonotonicityNot monotonic
2023-12-12T16:06:58.013415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 3
 
0.8%
10.12 3
 
0.8%
6.49 2
 
0.6%
11.91 2
 
0.6%
4.29 2
 
0.6%
5.56 2
 
0.6%
4.3 2
 
0.6%
7.38 2
 
0.6%
10.27 2
 
0.6%
12.72 2
 
0.6%
Other values (311) 331
93.8%
ValueCountFrequency (%)
0.0 1
0.3%
0.64 1
0.3%
2.18 1
0.3%
2.28 1
0.3%
2.66 1
0.3%
2.77 1
0.3%
2.87 1
0.3%
2.88 1
0.3%
2.94 1
0.3%
2.99 1
0.3%
ValueCountFrequency (%)
27.94 1
0.3%
25.91 1
0.3%
24.98 1
0.3%
24.68 1
0.3%
23.47 1
0.3%
23.4 1
0.3%
22.86 1
0.3%
22.07 1
0.3%
21.6 1
0.3%
21.18 1
0.3%

유입 총인(T-P)
Real number (ℝ)

Distinct241
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9532578
Minimum0
Maximum9.02
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:58.155675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.898
Q13.05
median3.93
Q34.68
95-th percentile6.284
Maximum9.02
Range9.02
Interquartile range (IQR)1.63

Descriptive statistics

Standard deviation1.350167
Coefficient of variation (CV)0.34153276
Kurtosis0.69620002
Mean3.9532578
Median Absolute Deviation (MAD)0.81
Skewness0.3567841
Sum1395.5
Variance1.822951
MonotonicityNot monotonic
2023-12-12T16:06:58.292447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.96 7
 
2.0%
3.88 4
 
1.1%
4.64 4
 
1.1%
3.72 4
 
1.1%
4.04 4
 
1.1%
3.9 4
 
1.1%
4.05 3
 
0.8%
2.76 3
 
0.8%
4.51 3
 
0.8%
2.87 3
 
0.8%
Other values (231) 314
89.0%
ValueCountFrequency (%)
0.0 1
0.3%
0.5 1
0.3%
0.74 1
0.3%
1.16 1
0.3%
1.21 2
0.6%
1.41 1
0.3%
1.47 1
0.3%
1.48 1
0.3%
1.49 1
0.3%
1.65 1
0.3%
ValueCountFrequency (%)
9.02 1
0.3%
8.23 1
0.3%
8.21 1
0.3%
7.76 1
0.3%
7.38 1
0.3%
7.06 1
0.3%
7.05 1
0.3%
7.02 1
0.3%
6.98 1
0.3%
6.78 1
0.3%

방류 총인(T-P)
Real number (ℝ)

Distinct164
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90495751
Minimum0
Maximum2.79
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:58.428040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q10.42
median0.85
Q31.39
95-th percentile1.888
Maximum2.79
Range2.79
Interquartile range (IQR)0.97

Descriptive statistics

Standard deviation0.60587658
Coefficient of variation (CV)0.66950832
Kurtosis-0.23924348
Mean0.90495751
Median Absolute Deviation (MAD)0.5
Skewness0.5147061
Sum319.45
Variance0.36708643
MonotonicityNot monotonic
2023-12-12T16:06:58.603592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04 8
 
2.3%
0.05 8
 
2.3%
0.86 7
 
2.0%
0.06 6
 
1.7%
0.85 6
 
1.7%
1.63 6
 
1.7%
1.58 5
 
1.4%
1.65 5
 
1.4%
0.87 5
 
1.4%
0.93 5
 
1.4%
Other values (154) 292
82.7%
ValueCountFrequency (%)
0.0 1
 
0.3%
0.02 1
 
0.3%
0.03 2
 
0.6%
0.04 8
2.3%
0.05 8
2.3%
0.06 6
1.7%
0.07 4
1.1%
0.08 3
 
0.8%
0.09 3
 
0.8%
0.1 2
 
0.6%
ValueCountFrequency (%)
2.79 1
0.3%
2.75 1
0.3%
2.62 1
0.3%
2.56 1
0.3%
2.54 1
0.3%
2.46 2
0.6%
2.35 2
0.6%
2.17 1
0.3%
2.14 1
0.3%
2.02 1
0.3%

유입총대장균군수
Real number (ℝ)

Distinct345
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129636.1
Minimum0
Maximum905000
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:58.747970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22934.4
Q165602
median125281
Q3183077
95-th percentile220615.2
Maximum905000
Range905000
Interquartile range (IQR)117475

Descriptive statistics

Standard deviation86065.325
Coefficient of variation (CV)0.66389939
Kurtosis19.159483
Mean129636.1
Median Absolute Deviation (MAD)58416
Skewness2.6328357
Sum45761542
Variance7.4072402 × 109
MonotonicityNot monotonic
2023-12-12T16:06:59.332371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
155096 2
 
0.6%
54650 2
 
0.6%
26627 2
 
0.6%
192500 2
 
0.6%
110833 2
 
0.6%
17366 2
 
0.6%
129173 2
 
0.6%
48925 2
 
0.6%
141016 1
 
0.3%
167925 1
 
0.3%
Other values (335) 335
94.9%
ValueCountFrequency (%)
0 1
0.3%
4725 1
0.3%
7850 1
0.3%
8917 1
0.3%
10858 1
0.3%
11798 1
0.3%
11983 1
0.3%
14317 1
0.3%
14719 1
0.3%
14746 1
0.3%
ValueCountFrequency (%)
905000 1
0.3%
495827 1
0.3%
483285 1
0.3%
399356 1
0.3%
363315 1
0.3%
352667 1
0.3%
328162 1
0.3%
317000 1
0.3%
295154 1
0.3%
280384 1
0.3%

방류총대장균군수
Real number (ℝ)

ZEROS 

Distinct148
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.43626
Minimum0
Maximum18280
Zeros32
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:59.494055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median30
Q393
95-th percentile792.8
Maximum18280
Range18280
Interquartile range (IQR)81

Descriptive statistics

Standard deviation996.34474
Coefficient of variation (CV)5.8117503
Kurtosis312.34275
Mean171.43626
Median Absolute Deviation (MAD)28
Skewness17.191729
Sum60517
Variance992702.83
MonotonicityNot monotonic
2023-12-12T16:06:59.650259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 43
 
12.2%
0 32
 
9.1%
2 16
 
4.5%
20 14
 
4.0%
21 10
 
2.8%
1 10
 
2.8%
22 8
 
2.3%
16 7
 
2.0%
13 5
 
1.4%
23 5
 
1.4%
Other values (138) 203
57.5%
ValueCountFrequency (%)
0 32
9.1%
1 10
 
2.8%
2 16
4.5%
3 2
 
0.6%
4 3
 
0.8%
5 4
 
1.1%
6 4
 
1.1%
7 5
 
1.4%
8 2
 
0.6%
9 4
 
1.1%
ValueCountFrequency (%)
18280 1
0.3%
1709 1
0.3%
1321 1
0.3%
1274 1
0.3%
1170 1
0.3%
1150 1
0.3%
1077 1
0.3%
1072 1
0.3%
1011 1
0.3%
912 1
0.3%

처리효율(퍼센트)
Real number (ℝ)

Distinct66
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.71983
Minimum0
Maximum99.9
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:06:59.807297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile94.06
Q197.6
median98.5
Q399.2
95-th percentile99.7
Maximum99.9
Range99.9
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation5.5472201
Coefficient of variation (CV)0.056766576
Kurtosis275.37888
Mean97.71983
Median Absolute Deviation (MAD)0.8
Skewness-15.695449
Sum34495.1
Variance30.771651
MonotonicityNot monotonic
2023-12-12T16:06:59.960918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.8 18
 
5.1%
99.1 17
 
4.8%
99.0 17
 
4.8%
99.6 16
 
4.5%
99.2 15
 
4.2%
98.1 15
 
4.2%
99.5 15
 
4.2%
99.4 15
 
4.2%
98.6 14
 
4.0%
98.5 13
 
3.7%
Other values (56) 198
56.1%
ValueCountFrequency (%)
0.0 1
0.3%
87.4 1
0.3%
88.3 1
0.3%
89.3 1
0.3%
90.9 1
0.3%
91.3 1
0.3%
91.4 1
0.3%
92.0 1
0.3%
92.1 1
0.3%
92.2 2
0.6%
ValueCountFrequency (%)
99.9 3
 
0.8%
99.8 5
 
1.4%
99.7 11
3.1%
99.6 16
4.5%
99.5 15
4.2%
99.4 15
4.2%
99.3 11
3.1%
99.2 15
4.2%
99.1 17
4.8%
99.0 17
4.8%

처리부하량(킬로그램 당 생화학적 산소유구량(BOD-D))
Real number (ℝ)

Distinct194
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean319.85042
Minimum0
Maximum44445.5
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:00.101473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q12.6
median5.7
Q314.2
95-th percentile435.02
Maximum44445.5
Range44445.5
Interquartile range (IQR)11.6

Descriptive statistics

Standard deviation2731.7966
Coefficient of variation (CV)8.5408564
Kurtosis203.41855
Mean319.85042
Median Absolute Deviation (MAD)4.1
Skewness13.527237
Sum112907.2
Variance7462712.4
MonotonicityNot monotonic
2023-12-12T16:07:00.244236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.1 7
 
2.0%
3.2 7
 
2.0%
1.3 6
 
1.7%
1.7 6
 
1.7%
0.5 6
 
1.7%
2.9 5
 
1.4%
3.6 5
 
1.4%
1.4 5
 
1.4%
5.0 5
 
1.4%
10.2 5
 
1.4%
Other values (184) 296
83.9%
ValueCountFrequency (%)
0.0 1
 
0.3%
0.1 3
0.8%
0.2 1
 
0.3%
0.3 2
 
0.6%
0.4 4
1.1%
0.5 6
1.7%
0.6 4
1.1%
0.7 1
 
0.3%
0.8 2
 
0.6%
0.9 4
1.1%
ValueCountFrequency (%)
44445.5 1
0.3%
19694.6 1
0.3%
14940.1 1
0.3%
5595.7 1
0.3%
3483.9 1
0.3%
2887.7 1
0.3%
2414.1 1
0.3%
2047.7 1
0.3%
1705.2 1
0.3%
1702.8 1
0.3%

처리방법
Text

Distinct77
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T16:07:00.481214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length5.7648725
Min length2

Characters and Unicode

Total characters2035
Distinct characters115
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)10.2%

Sample

1st row표준활성슬러지법,CNR
2nd rowHDF
3rd rowSMMIAR
4th rowKSMBR
5th rowSBR,섬유디스크필터
ValueCountFrequency (%)
ksmbr 48
 
12.7%
sbr 40
 
10.6%
km-sbr 31
 
8.2%
dmbr 25
 
6.6%
분리막 14
 
3.7%
호기성침전지하수고도처리 14
 
3.7%
ic-sbr 14
 
3.7%
smmiar 12
 
3.2%
fnr 11
 
2.9%
접촉산화법 11
 
2.9%
Other values (70) 158
41.8%
2023-12-12T16:07:00.975492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 239
 
11.7%
R 233
 
11.4%
S 219
 
10.8%
M 167
 
8.2%
K 104
 
5.1%
- 74
 
3.6%
I 50
 
2.5%
D 46
 
2.3%
A 43
 
2.1%
N 37
 
1.8%
Other values (105) 823
40.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1273
62.6%
Other Letter 602
29.6%
Dash Punctuation 74
 
3.6%
Other Punctuation 26
 
1.3%
Space Separator 25
 
1.2%
Lowercase Letter 19
 
0.9%
Decimal Number 15
 
0.7%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 32
 
5.3%
화 30
 
5.0%
기 28
 
4.7%
촉 26
 
4.3%
접 26
 
4.3%
수 25
 
4.2%
법 25
 
4.2%
산 25
 
4.2%
성 22
 
3.7%
지 19
 
3.2%
Other values (67) 344
57.1%
Uppercase Letter
ValueCountFrequency (%)
B 239
18.8%
R 233
18.3%
S 219
17.2%
M 167
13.1%
K 104
8.2%
I 50
 
3.9%
D 46
 
3.6%
A 43
 
3.4%
N 37
 
2.9%
C 33
 
2.6%
Other values (11) 102
8.0%
Lowercase Letter
ValueCountFrequency (%)
i 4
21.1%
e 3
15.8%
o 3
15.8%
d 2
10.5%
h 1
 
5.3%
a 1
 
5.3%
l 1
 
5.3%
u 1
 
5.3%
y 1
 
5.3%
n 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
3 8
53.3%
2 7
46.7%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Symbol
ValueCountFrequency (%)
ⓢ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1292
63.5%
Hangul 602
29.6%
Common 141
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 32
 
5.3%
화 30
 
5.0%
기 28
 
4.7%
촉 26
 
4.3%
접 26
 
4.3%
수 25
 
4.2%
법 25
 
4.2%
산 25
 
4.2%
성 22
 
3.7%
지 19
 
3.2%
Other values (67) 344
57.1%
Latin
ValueCountFrequency (%)
B 239
18.5%
R 233
18.0%
S 219
17.0%
M 167
12.9%
K 104
8.0%
I 50
 
3.9%
D 46
 
3.6%
A 43
 
3.3%
N 37
 
2.9%
C 33
 
2.6%
Other values (22) 121
9.4%
Common
ValueCountFrequency (%)
- 74
52.5%
, 26
 
18.4%
25
 
17.7%
3 8
 
5.7%
2 7
 
5.0%
ⓢ 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1432
70.4%
Hangul 602
29.6%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 239
16.7%
R 233
16.3%
S 219
15.3%
M 167
11.7%
K 104
7.3%
- 74
 
5.2%
I 50
 
3.5%
D 46
 
3.2%
A 43
 
3.0%
N 37
 
2.6%
Other values (27) 220
15.4%
Hangul
ValueCountFrequency (%)
리 32
 
5.3%
화 30
 
5.0%
기 28
 
4.7%
촉 26
 
4.3%
접 26
 
4.3%
수 25
 
4.2%
법 25
 
4.2%
산 25
 
4.2%
성 22
 
3.7%
지 19
 
3.2%
Other values (67) 344
57.1%
Enclosed Alphanum
ValueCountFrequency (%)
ⓢ 1
100.0%

적용신기술
Text

MISSING 

Distinct26
Distinct (%)66.7%
Missing314
Missing (%)89.0%
Memory size2.9 KiB
2023-12-12T16:07:01.245404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length41
Mean length12.179487
Min length2

Characters and Unicode

Total characters475
Distinct characters113
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)53.8%

Sample

1st rowKSMBR,IPR
2nd row선회와류식 SBR
3rd rowKS-MBR Process(침지형막분리공법)
4th row선회와류식 SBR공법
5th rowPSBR
ValueCountFrequency (%)
km-sbr 7
 
9.0%
이용한 6
 
7.7%
aosb 4
 
5.1%
해당없음 3
 
3.8%
인 2
 
2.6%
bcs-2 2
 
2.6%
발포성형한 2
 
2.6%
인공여재를 2
 
2.6%
총인처리기술 2
 
2.6%
선회와류식 2
 
2.6%
Other values (44) 46
59.0%
2023-12-12T16:07:01.645771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
8.2%
S 30
 
6.3%
B 25
 
5.3%
R 21
 
4.4%
- 15
 
3.2%
M 13
 
2.7%
K 11
 
2.3%
A 11
 
2.3%
공 9
 
1.9%
리 9
 
1.9%
Other values (103) 292
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 235
49.5%
Uppercase Letter 140
29.5%
Space Separator 39
 
8.2%
Decimal Number 16
 
3.4%
Dash Punctuation 15
 
3.2%
Lowercase Letter 13
 
2.7%
Other Punctuation 6
 
1.3%
Open Punctuation 5
 
1.1%
Close Punctuation 5
 
1.1%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 9
 
3.8%
리 9
 
3.8%
인 9
 
3.8%
기 8
 
3.4%
를 8
 
3.4%
용 8
 
3.4%
법 8
 
3.4%
한 8
 
3.4%
술 7
 
3.0%
이 7
 
3.0%
Other values (70) 154
65.5%
Uppercase Letter
ValueCountFrequency (%)
S 30
21.4%
B 25
17.9%
R 21
15.0%
M 13
9.3%
K 11
 
7.9%
A 11
 
7.9%
P 5
 
3.6%
O 5
 
3.6%
C 5
 
3.6%
H 4
 
2.9%
Other values (6) 10
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 2
15.4%
c 2
15.4%
o 2
15.4%
r 2
15.4%
p 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
3 5
31.2%
2 5
31.2%
4 3
18.8%
1 2
 
12.5%
6 1
 
6.2%
Space Separator
ValueCountFrequency (%)
39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
∥ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 235
49.5%
Latin 153
32.2%
Common 87
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 9
 
3.8%
리 9
 
3.8%
인 9
 
3.8%
기 8
 
3.4%
를 8
 
3.4%
용 8
 
3.4%
법 8
 
3.4%
한 8
 
3.4%
술 7
 
3.0%
이 7
 
3.0%
Other values (70) 154
65.5%
Latin
ValueCountFrequency (%)
S 30
19.6%
B 25
16.3%
R 21
13.7%
M 13
8.5%
K 11
 
7.2%
A 11
 
7.2%
P 5
 
3.3%
O 5
 
3.3%
C 5
 
3.3%
H 4
 
2.6%
Other values (12) 23
15.0%
Common
ValueCountFrequency (%)
39
44.8%
- 15
 
17.2%
, 6
 
6.9%
3 5
 
5.7%
( 5
 
5.7%
) 5
 
5.7%
2 5
 
5.7%
4 3
 
3.4%
1 2
 
2.3%
6 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239
50.3%
Hangul 235
49.5%
Math Operators 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
16.3%
S 30
12.6%
B 25
 
10.5%
R 21
 
8.8%
- 15
 
6.3%
M 13
 
5.4%
K 11
 
4.6%
A 11
 
4.6%
, 6
 
2.5%
P 5
 
2.1%
Other values (22) 63
26.4%
Hangul
ValueCountFrequency (%)
공 9
 
3.8%
리 9
 
3.8%
인 9
 
3.8%
기 8
 
3.4%
를 8
 
3.4%
용 8
 
3.4%
법 8
 
3.4%
한 8
 
3.4%
술 7
 
3.0%
이 7
 
3.0%
Other values (70) 154
65.5%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%

분뇨 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6263456
Minimum0
Maximum530.3
Zeros341
Zeros (%)96.6%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:01.817501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum530.3
Range530.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34.548838
Coefficient of variation (CV)9.5271775
Kurtosis170.55455
Mean3.6263456
Median Absolute Deviation (MAD)0
Skewness12.470421
Sum1280.1
Variance1193.6222
MonotonicityNot monotonic
2023-12-12T16:07:01.977379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 341
96.6%
530.3 1
 
0.3%
269.9 1
 
0.3%
248.4 1
 
0.3%
47.5 1
 
0.3%
13.6 1
 
0.3%
13.4 1
 
0.3%
28.9 1
 
0.3%
8.9 1
 
0.3%
67.6 1
 
0.3%
Other values (3) 3
 
0.8%
ValueCountFrequency (%)
0.0 341
96.6%
8.9 1
 
0.3%
13.0 1
 
0.3%
13.4 1
 
0.3%
13.6 1
 
0.3%
16.9 1
 
0.3%
21.7 1
 
0.3%
28.9 1
 
0.3%
47.5 1
 
0.3%
67.6 1
 
0.3%
ValueCountFrequency (%)
530.3 1
0.3%
269.9 1
0.3%
248.4 1
0.3%
67.6 1
0.3%
47.5 1
0.3%
28.9 1
0.3%
21.7 1
0.3%
16.9 1
0.3%
13.6 1
0.3%
13.4 1
0.3%

축산 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0.0
350 
10.5
 
1
104.2
 
1
39.7
 
1

Length

Max length5
Median length3
Mean length3.0113314
Min length3

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 350
99.2%
10.5 1
 
0.3%
104.2 1
 
0.3%
39.7 1
 
0.3%

Length

2023-12-12T16:07:02.145985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:02.285895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 350
99.2%
10.5 1
 
0.3%
104.2 1
 
0.3%
39.7 1
 
0.3%

침출수 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4365439
Minimum0
Maximum109
Zeros344
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:02.416080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum109
Range109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.5920656
Coefficient of variation (CV)6.6771824
Kurtosis64.945566
Mean1.4365439
Median Absolute Deviation (MAD)0
Skewness7.6353768
Sum507.1
Variance92.007723
MonotonicityNot monotonic
2023-12-12T16:07:02.536451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 344
97.5%
109.0 1
 
0.3%
74.4 1
 
0.3%
36.1 1
 
0.3%
59.7 1
 
0.3%
40.0 1
 
0.3%
53.9 1
 
0.3%
56.4 1
 
0.3%
47.0 1
 
0.3%
30.6 1
 
0.3%
ValueCountFrequency (%)
0.0 344
97.5%
30.6 1
 
0.3%
36.1 1
 
0.3%
40.0 1
 
0.3%
47.0 1
 
0.3%
53.9 1
 
0.3%
56.4 1
 
0.3%
59.7 1
 
0.3%
74.4 1
 
0.3%
109.0 1
 
0.3%
ValueCountFrequency (%)
109.0 1
 
0.3%
74.4 1
 
0.3%
59.7 1
 
0.3%
56.4 1
 
0.3%
53.9 1
 
0.3%
47.0 1
 
0.3%
40.0 1
 
0.3%
36.1 1
 
0.3%
30.6 1
 
0.3%
0.0 344
97.5%

기타 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7135977
Minimum0
Maximum1579
Zeros346
Zeros (%)98.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:02.646684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1579
Range1579
Interquartile range (IQR)0

Descriptive statistics

Standard deviation106.09701
Coefficient of variation (CV)10.922524
Kurtosis177.35093
Mean9.7135977
Median Absolute Deviation (MAD)0
Skewness13.07754
Sum3428.9
Variance11256.575
MonotonicityNot monotonic
2023-12-12T16:07:02.767565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 346
98.0%
263.4 1
 
0.3%
1174.3 1
 
0.3%
32.1 1
 
0.3%
143.3 1
 
0.3%
165.4 1
 
0.3%
71.4 1
 
0.3%
1579.0 1
 
0.3%
ValueCountFrequency (%)
0.0 346
98.0%
32.1 1
 
0.3%
71.4 1
 
0.3%
143.3 1
 
0.3%
165.4 1
 
0.3%
263.4 1
 
0.3%
1174.3 1
 
0.3%
1579.0 1
 
0.3%
ValueCountFrequency (%)
1579.0 1
 
0.3%
1174.3 1
 
0.3%
263.4 1
 
0.3%
165.4 1
 
0.3%
143.3 1
 
0.3%
71.4 1
 
0.3%
32.1 1
 
0.3%
0.0 346
98.0%

전화번호
Text

MISSING 

Distinct53
Distinct (%)15.6%
Missing14
Missing (%)4.0%
Memory size2.9 KiB
2023-12-12T16:07:03.009958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0059
Min length12

Characters and Unicode

Total characters4070
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)8.8%

Sample

1st row043-201-4815
2nd row043-214-8185
3rd row043-235-8187
4th row043-216-0738
5th row043-711-1243
ValueCountFrequency (%)
043-857-8434 55
16.2%
043-642-4687 41
12.1%
043-733-9982 36
10.6%
043-745-1550 29
 
8.6%
043-421-8613 29
 
8.6%
043-832-8770 22
 
6.5%
043-544-1274 18
 
5.3%
043-201-4822 15
 
4.4%
043-201-4814 10
 
2.9%
043-539-7665 10
 
2.9%
Other values (41) 74
21.8%
2023-12-12T16:07:03.450894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 739
18.2%
- 678
16.7%
3 596
14.6%
0 473
11.6%
8 352
8.6%
7 281
 
6.9%
2 261
 
6.4%
5 237
 
5.8%
1 193
 
4.7%
6 159
 
3.9%
Other values (2) 101
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3390
83.3%
Dash Punctuation 678
 
16.7%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 739
21.8%
3 596
17.6%
0 473
14.0%
8 352
10.4%
7 281
 
8.3%
2 261
 
7.7%
5 237
 
7.0%
1 193
 
5.7%
6 159
 
4.7%
9 99
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 678
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4070
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 739
18.2%
- 678
16.7%
3 596
14.6%
0 473
11.6%
8 352
8.6%
7 281
 
6.9%
2 261
 
6.4%
5 237
 
5.8%
1 193
 
4.7%
6 159
 
3.9%
Other values (2) 101
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 739
18.2%
- 678
16.7%
3 596
14.6%
0 473
11.6%
8 352
8.6%
7 281
 
6.9%
2 261
 
6.4%
5 237
 
5.8%
1 193
 
4.7%
6 159
 
3.9%
Other values (2) 101
 
2.5%

준공일
Date

Distinct222
Distinct (%)63.1%
Missing1
Missing (%)0.3%
Memory size2.9 KiB
Minimum1986-10-31 00:00:00
Maximum2021-12-13 00:00:00
2023-12-12T16:07:03.641589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:07:03.780901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

가동개시일
Date

Distinct217
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum1986-11-01 00:00:00
Maximum2021-12-13 00:00:00
2023-12-12T16:07:03.957224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:07:04.149660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업비(백만원)
Real number (ℝ)

ZEROS 

Distinct311
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4933.0408
Minimum0
Maximum210009
Zeros5
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:04.336941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile133.08
Q1349
median1259
Q33022
95-th percentile21175
Maximum210009
Range210009
Interquartile range (IQR)2673

Descriptive statistics

Standard deviation15465.299
Coefficient of variation (CV)3.1350438
Kurtosis96.183255
Mean4933.0408
Median Absolute Deviation (MAD)1030
Skewness8.5650939
Sum1741363.4
Variance2.3917547 × 108
MonotonicityNot monotonic
2023-12-12T16:07:04.493663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400.0 5
 
1.4%
0.0 5
 
1.4%
1000.0 4
 
1.1%
200.0 3
 
0.8%
292.0 3
 
0.8%
526.0 3
 
0.8%
320.0 2
 
0.6%
222.0 2
 
0.6%
3022.0 2
 
0.6%
2924.0 2
 
0.6%
Other values (301) 322
91.2%
ValueCountFrequency (%)
0.0 5
1.4%
76.7 1
 
0.3%
90.7 1
 
0.3%
98.4 1
 
0.3%
98.7 1
 
0.3%
99.0 1
 
0.3%
104.0 1
 
0.3%
111.9 1
 
0.3%
120.0 1
 
0.3%
124.0 2
 
0.6%
ValueCountFrequency (%)
210009.0 1
0.3%
107388.0 1
0.3%
84184.0 1
0.3%
66142.0 1
0.3%
62897.0 1
0.3%
60000.0 1
0.3%
51576.0 1
0.3%
43925.0 1
0.3%
39363.0 1
0.3%
33877.0 1
0.3%

방류수소독방법
Categorical

IMBALANCE 

Distinct8
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
염소 자외선 오존 기타
303 
자외선
 
23
<NA>
 
14
염소
 
4
자외선 오존 기타
 
3
Other values (3)
 
6

Length

Max length12
Median length12
Mean length10.929178
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
염소 자외선 오존 기타 303
85.8%
자외선 23
 
6.5%
<NA> 14
 
4.0%
염소 4
 
1.1%
자외선 오존 기타 3
 
0.8%
염소 오존 기타 3
 
0.8%
기타 2
 
0.6%
염소 자외선 1
 
0.3%

Length

2023-12-12T16:07:04.661830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:04.806721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자외선 330
25.9%
염소 311
24.4%
기타 311
24.4%
오존 309
24.2%
na 14
 
1.1%

수계
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
한강
197 
금강
156 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한강 197
55.8%
금강 156
44.2%

Length

2023-12-12T16:07:04.958630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:05.066510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한강 197
55.8%
금강 156
44.2%

지류
Text

MISSING 

Distinct86
Distinct (%)24.7%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2023-12-12T16:07:05.304067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7413793
Min length2

Characters and Unicode

Total characters954
Distinct characters100
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

Unique36 ?
Unique (%)10.3%

Sample

1st row미호천
2nd row석화천
3rd row미호천
4th row미호천
5th row병천천
ValueCountFrequency (%)
달천 44
 
12.6%
금강 31
 
8.9%
남한강 23
 
6.6%
보청천 18
 
5.1%
미호천 16
 
4.6%
한강 12
 
3.4%
하일천 11
 
3.1%
석화천 10
 
2.9%
영동천 8
 
2.3%
매포천 8
 
2.3%
Other values (77) 169
48.3%
2023-12-12T16:07:05.739917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 285
29.9%
강 76
 
8.0%
달 49
 
5.1%
한 44
 
4.6%
금 34
 
3.6%
남 28
 
2.9%
보 25
 
2.6%
청 21
 
2.2%
미 21
 
2.2%
동 19
 
2.0%
Other values (90) 352
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 952
99.8%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 285
29.9%
강 76
 
8.0%
달 49
 
5.1%
한 44
 
4.6%
금 34
 
3.6%
남 28
 
2.9%
보 25
 
2.6%
청 21
 
2.2%
미 21
 
2.2%
동 19
 
2.0%
Other values (89) 350
36.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 952
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 285
29.9%
강 76
 
8.0%
달 49
 
5.1%
한 44
 
4.6%
금 34
 
3.6%
남 28
 
2.9%
보 25
 
2.6%
청 21
 
2.2%
미 21
 
2.2%
동 19
 
2.0%
Other values (89) 350
36.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 952
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 285
29.9%
강 76
 
8.0%
달 49
 
5.1%
한 44
 
4.6%
금 34
 
3.6%
남 28
 
2.9%
보 25
 
2.6%
청 21
 
2.2%
미 21
 
2.2%
동 19
 
2.0%
Other values (89) 350
36.8%
ASCII
ValueCountFrequency (%)
2
100.0%

세부단위구역
Categorical

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
남한강상류
167 
대청댐
93 
미호천
44 
남한강하류
30 
용담댐
18 

Length

Max length5
Median length5
Mean length4.1189802
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
남한강상류 167
47.3%
대청댐 93
26.3%
미호천 44
 
12.5%
남한강하류 30
 
8.5%
용담댐 18
 
5.1%
금강하류 1
 
0.3%

Length

2023-12-12T16:07:05.911974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:06.032822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남한강상류 167
47.3%
대청댐 93
26.3%
미호천 44
 
12.5%
남한강하류 30
 
8.5%
용담댐 18
 
5.1%
금강하류 1
 
0.3%

지역구분
Categorical

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
500톤 미만 50톤 이상
199 
50톤 미만
112 
500톤 이상(Ⅱ지역)
24 
500톤 이상(Ⅲ지역)
 
10
50톤미만(수변구역)
 
5

Length

Max length14
Median length14
Mean length11.209632
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row500톤 이상(Ⅱ지역)
2nd row500톤 이상(Ⅱ지역)
3rd row500톤 이상(Ⅱ지역)
4th row500톤 이상(Ⅱ지역)
5th row500톤 이상(Ⅱ지역)

Common Values

ValueCountFrequency (%)
500톤 미만 50톤 이상 199
56.4%
50톤 미만 112
31.7%
500톤 이상(Ⅱ지역) 24
 
6.8%
500톤 이상(Ⅲ지역) 10
 
2.8%
50톤미만(수변구역) 5
 
1.4%
500톤 이상(Ⅰ지역) 3
 
0.8%

Length

2023-12-12T16:07:06.168799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:06.288789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 311
28.3%
50톤 311
28.3%
500톤 236
21.5%
이상 199
18.1%
이상(ⅱ지역 24
 
2.2%
이상(ⅲ지역 10
 
0.9%
50톤미만(수변구역 5
 
0.5%
이상(ⅰ지역 3
 
0.3%

중권역
Categorical

Distinct12
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
충주댐
139 
미호천
44 
대청댐
34 
남한강상류
28 
대청댐상류
28 
Other values (7)
80 

Length

Max length5
Median length3
Mean length3.3711048
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
충주댐 139
39.4%
미호천 44
 
12.5%
대청댐 34
 
9.6%
남한강상류 28
 
7.9%
대청댐상류 28
 
7.9%
보청천 23
 
6.5%
충주댐하류 17
 
4.8%
영동천 16
 
4.5%
달천 13
 
3.7%
초강 8
 
2.3%
Other values (2) 3
 
0.8%

Length

2023-12-12T16:07:06.405088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충주댐 139
39.4%
미호천 44
 
12.5%
대청댐 34
 
9.6%
남한강상류 28
 
7.9%
대청댐상류 28
 
7.9%
보청천 23
 
6.5%
충주댐하류 17
 
4.8%
영동천 16
 
4.5%
달천 13
 
3.7%
초강 8
 
2.3%
Other values (2) 3
 
0.8%

역 번호
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Ⅰa
255 
Ⅰb
53 
Ⅲ
44 
Ⅱ
 
1

Length

Max length2
Median length2
Mean length1.8725212
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
Ⅰa 255
72.2%
Ⅰb 53
 
15.0%
Ⅲ 44
 
12.5%
Ⅱ 1
 
0.3%

Length

2023-12-12T16:07:06.520538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:06.610289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ⅰa 255
72.2%
ⅰb 53
 
15.0%
ⅲ 44
 
12.5%
ⅱ 1
 
0.3%

재생에너지이용률(퍼센트)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7362606
Minimum0
Maximum48.6
Zeros309
Zeros (%)87.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:06.984365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12.64
Maximum48.6
Range48.6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8164773
Coefficient of variation (CV)3.3500025
Kurtosis22.484366
Mean1.7362606
Median Absolute Deviation (MAD)0
Skewness4.37653
Sum612.9
Variance33.831409
MonotonicityNot monotonic
2023-12-12T16:07:07.116123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 309
87.5%
3.3 2
 
0.6%
5.7 2
 
0.6%
3.5 2
 
0.6%
19.3 1
 
0.3%
0.5 1
 
0.3%
10.2 1
 
0.3%
10.1 1
 
0.3%
11.2 1
 
0.3%
9.7 1
 
0.3%
Other values (32) 32
 
9.1%
ValueCountFrequency (%)
0.0 309
87.5%
0.5 1
 
0.3%
2.6 1
 
0.3%
3.3 2
 
0.6%
3.5 2
 
0.6%
4.1 1
 
0.3%
5.7 2
 
0.6%
5.9 1
 
0.3%
6.4 1
 
0.3%
6.6 1
 
0.3%
ValueCountFrequency (%)
48.6 1
0.3%
37.4 1
0.3%
33.7 1
0.3%
32.0 1
0.3%
26.4 1
0.3%
23.9 1
0.3%
23.8 1
0.3%
22.3 1
0.3%
21.8 1
0.3%
20.9 1
0.3%

연간 총 전력사용량(kWh-년)
Real number (ℝ)

Distinct351
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317569.05
Minimum0
Maximum37747770
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:07.240447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7780.6
Q120382
median40808
Q372438
95-th percentile881256
Maximum37747770
Range37747770
Interquartile range (IQR)52056

Descriptive statistics

Standard deviation2126540.3
Coefficient of variation (CV)6.6963087
Kurtosis274.86182
Mean317569.05
Median Absolute Deviation (MAD)23273
Skewness15.798742
Sum1.1210187 × 108
Variance4.5221739 × 1012
MonotonicityNot monotonic
2023-12-12T16:07:07.415045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52665.0 2
 
0.6%
35533.0 2
 
0.6%
37747770.0 1
 
0.3%
123263.0 1
 
0.3%
89013.0 1
 
0.3%
92333.0 1
 
0.3%
93814.0 1
 
0.3%
46506.0 1
 
0.3%
99606.0 1
 
0.3%
39853.0 1
 
0.3%
Other values (341) 341
96.6%
ValueCountFrequency (%)
0.0 1
0.3%
269.0 1
0.3%
1808.0 1
0.3%
2336.0 1
0.3%
2467.0 1
0.3%
2827.0 1
0.3%
2914.0 1
0.3%
3045.0 1
0.3%
4029.0 1
0.3%
4160.0 1
0.3%
ValueCountFrequency (%)
37747770.0 1
0.3%
6377655.0 1
0.3%
6128592.0 1
0.3%
4883402.0 1
0.3%
4438008.0 1
0.3%
4069314.0 1
0.3%
3368170.0 1
0.3%
3272844.0 1
0.3%
3072294.0 1
0.3%
2312351.0 1
0.3%

하수처리량당CO2배출량(kgCO2-세제곱미터)
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2362606
Minimum0
Maximum832.8
Zeros309
Zeros (%)87.5%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:07.541802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24.54
Maximum832.8
Range832.8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation62.880034
Coefficient of variation (CV)7.6345367
Kurtosis137.71322
Mean8.2362606
Median Absolute Deviation (MAD)0
Skewness11.361247
Sum2907.4
Variance3953.8986
MonotonicityNot monotonic
2023-12-12T16:07:07.666183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 309
87.5%
2.6 3
 
0.8%
2.5 3
 
0.8%
5.1 2
 
0.6%
27.3 2
 
0.6%
286.1 1
 
0.3%
2.3 1
 
0.3%
3.7 1
 
0.3%
5.4 1
 
0.3%
0.1 1
 
0.3%
Other values (29) 29
 
8.2%
ValueCountFrequency (%)
0.0 309
87.5%
0.1 1
 
0.3%
0.8 1
 
0.3%
2.2 1
 
0.3%
2.3 1
 
0.3%
2.4 1
 
0.3%
2.5 3
 
0.8%
2.6 3
 
0.8%
3.6 1
 
0.3%
3.7 1
 
0.3%
ValueCountFrequency (%)
832.8 1
0.3%
743.1 1
0.3%
286.1 1
0.3%
183.9 1
0.3%
157.7 1
0.3%
85.4 1
0.3%
80.3 1
0.3%
62.7 1
0.3%
42.5 1
0.3%
35.9 1
0.3%

운영주체(자체-공기업-민간대행)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
민간(대행)
347 
자체
 
6

Length

Max length6
Median length6
Mean length5.9320113
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간(대행)
2nd row민간(대행)
3rd row민간(대행)
4th row민간(대행)
5th row민간(대행)

Common Values

ValueCountFrequency (%)
민간(대행) 347
98.3%
자체 6
 
1.7%

Length

2023-12-12T16:07:07.809980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:07.912507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간(대행 347
98.3%
자체 6
 
1.7%

위탁업체명
Categorical

Distinct17
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
환경시설관리주식회사
62 
환경시설관리주식회사,(주)호암엔지니어링
61 
(주)대신환경기술
41 
(주)에코비트워터,의림환경에너텍(주
37 
용진환경(주)
35 
Other values (12)
117 

Length

Max length41
Median length32
Mean length12.943343
Min length4

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row(주)건양기술공사건축사무소,(주)홍익기술단,청수기술환경(주),㈜에코비트워터
2nd row(주)영진엔지니어링,환경시설관리(주)
3rd row(주)영진엔지니어링,환경시설관리(주)
4th row(주)영진엔지니어링,환경시설관리주식회사
5th row(주)건양기술공사건축사무소,(주)동명기술공단종합건축사사무소

Common Values

ValueCountFrequency (%)
환경시설관리주식회사 62
17.6%
환경시설관리주식회사,(주)호암엔지니어링 61
17.3%
(주)대신환경기술 41
11.6%
(주)에코비트워터,의림환경에너텍(주 37
10.5%
용진환경(주) 35
9.9%
(주)에코비트워터 28
7.9%
테크로스환경서비스 27
7.6%
(주)푸른환경산업 16
 
4.5%
청수기술환경(주) 15
 
4.2%
(주)두현이엔씨,(주)홍익기술단 13
 
3.7%
Other values (7) 18
 
5.1%

Length

2023-12-12T16:07:08.068980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환경시설관리주식회사 62
17.6%
환경시설관리주식회사,(주)호암엔지니어링 61
17.3%
주)대신환경기술 41
11.6%
주)에코비트워터,의림환경에너텍(주 38
10.8%
용진환경(주 35
9.9%
주)에코비트워터 28
7.9%
테크로스환경서비스 27
7.6%
주)푸른환경산업 16
 
4.5%
청수기술환경(주 15
 
4.2%
주)두현이엔씨,(주)홍익기술단 13
 
3.7%
Other values (6) 17
 
4.8%

위탁비용(백만원-년)
Real number (ℝ)

ZEROS 

Distinct131
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.69065
Minimum0
Maximum6757
Zeros130
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:08.259789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15.5
Q333
95-th percentile865.2
Maximum6757
Range6757
Interquartile range (IQR)33

Descriptive statistics

Standard deviation625.88819
Coefficient of variation (CV)4.181211
Kurtosis57.647665
Mean149.69065
Median Absolute Deviation (MAD)15.5
Skewness6.9286724
Sum52840.8
Variance391736.03
MonotonicityNot monotonic
2023-12-12T16:07:08.448678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 130
36.8%
32.7 27
 
7.6%
17.4 16
 
4.5%
15.5 10
 
2.8%
9.3 7
 
2.0%
6.2 6
 
1.7%
18.6 6
 
1.7%
10.8 4
 
1.1%
12.4 4
 
1.1%
13.9 4
 
1.1%
Other values (121) 139
39.4%
ValueCountFrequency (%)
0.0 130
36.8%
3.7 1
 
0.3%
4.6 3
 
0.8%
6.2 6
 
1.7%
7.7 3
 
0.8%
9.3 7
 
2.0%
10.4 3
 
0.8%
10.8 4
 
1.1%
12.4 4
 
1.1%
13.0 1
 
0.3%
ValueCountFrequency (%)
6757.0 1
0.3%
5751.0 1
0.3%
3423.0 1
0.3%
2795.0 1
0.3%
2776.0 1
0.3%
2648.0 1
0.3%
2441.3 1
0.3%
2285.0 1
0.3%
2015.4 1
0.3%
1835.2 1
0.3%

위탁계약기간
Categorical

Distinct24
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2021-01-01~2025-12-31
137 
2020-01-08~2024-12-31
41 
2015-08-07~2021-12-31
38 
2017-01-03~2022-02-28
30 
2017-04-08~2022-08-03
27 
Other values (19)
80 

Length

Max length21
Median length21
Mean length20.711048
Min length4

Unique

Unique7 ?
Unique (%)2.0%

Sample

1st row2019-01-01~2024-12-31
2nd row2018-01-01~2022-12-31
3rd row2018-01-01~2022-12-31
4th row2018-01-01~2022-12-31
5th row2018-01-01~2022-12-31

Common Values

ValueCountFrequency (%)
2021-01-01~2025-12-31 137
38.8%
2020-01-08~2024-12-31 41
 
11.6%
2015-08-07~2021-12-31 38
 
10.8%
2017-01-03~2022-02-28 30
 
8.5%
2017-04-08~2022-08-03 27
 
7.6%
2017-25-07~2022-07-24 19
 
5.4%
2020-01-01~2024-12-31 13
 
3.7%
2018-01-09~2023-08-31 9
 
2.5%
2018-01-01~2022-12-31 9
 
2.5%
<NA> 6
 
1.7%
Other values (14) 24
 
6.8%

Length

2023-12-12T16:07:08.656640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-01~2025-12-31 137
38.8%
2020-01-08~2024-12-31 41
 
11.6%
2015-08-07~2021-12-31 38
 
10.8%
2017-01-03~2022-02-28 30
 
8.5%
2017-04-08~2022-08-03 27
 
7.6%
2017-25-07~2022-07-24 19
 
5.4%
2020-01-01~2024-12-31 13
 
3.7%
2018-01-09~2023-08-31 9
 
2.5%
2018-01-01~2022-12-31 9
 
2.5%
na 6
 
1.7%
Other values (14) 24
 
6.8%

직원총수(명)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3739377
Minimum0
Maximum57
Zeros248
Zeros (%)70.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T16:07:08.825387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile19
Maximum57
Range57
Interquartile range (IQR)4

Descriptive statistics

Standard deviation10.676631
Coefficient of variation (CV)1.9867427
Kurtosis7.5586678
Mean5.3739377
Median Absolute Deviation (MAD)0
Skewness2.5071394
Sum1897
Variance113.99046
MonotonicityNot monotonic
2023-12-12T16:07:08.929720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 248
70.3%
19 63
 
17.8%
1 11
 
3.1%
6 5
 
1.4%
57 5
 
1.4%
4 3
 
0.8%
8 2
 
0.6%
2 2
 
0.6%
10 2
 
0.6%
51 1
 
0.3%
Other values (11) 11
 
3.1%
ValueCountFrequency (%)
0 248
70.3%
1 11
 
3.1%
2 2
 
0.6%
3 1
 
0.3%
4 3
 
0.8%
6 5
 
1.4%
8 2
 
0.6%
10 2
 
0.6%
13 1
 
0.3%
17 1
 
0.3%
ValueCountFrequency (%)
57 5
 
1.4%
51 1
 
0.3%
45 1
 
0.3%
41 1
 
0.3%
31 1
 
0.3%
30 1
 
0.3%
28 1
 
0.3%
23 1
 
0.3%
22 1
 
0.3%
19 63
17.8%

안전사고건수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
352 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 352
99.7%
1 1
 
0.3%

Length

2023-12-12T16:07:09.059893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:09.179022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 352
99.7%
1 1
 
0.3%

Sample

시도구군행정구역명시설명소재지시설용량(500세제곱미터-일 이상-미만)시설용량 물리적(세제곱미터-일)시설용량 생물학적(세제곱미터-일)시설용량 고도(세제곱미터-일)유입하수량(500세제곱미터-일 이상-미만)유입하수량 물리적(세제곱미터-일)유입하수량 생물학적(세제곱미터-일)유입하수량 고도(세제곱미터-일)방류량(500세제곱미터-일 이상-미만)방류량 물리적(세제곱미터-일)방류량 생물학적(세제곱미터-일)방류량 고도(세제곱미터-일)유입 생화학적 산소요구량(BOD)방류 생물학적 산소 요구량(BOD)유입 화학적 산소 요구량(COD)방류 화학적 산소 요구량(COD)유입 부유물질량(SS)방류 부유물질량(SS)유입 총질소(T-N)방류 총질소(T-N)유입 총인(T-P)방류 총인(T-P)유입총대장균군수방류총대장균군수처리효율(퍼센트)처리부하량(킬로그램 당 생화학적 산소유구량(BOD-D))처리방법적용신기술분뇨 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)축산 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)침출수 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)기타 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)전화번호준공일가동개시일사업비(백만원)방류수소독방법수계지류세부단위구역지역구분중권역역 번호재생에너지이용률(퍼센트)연간 총 전력사용량(kWh-년)하수처리량당CO2배출량(kgCO2-세제곱미터)운영주체(자체-공기업-민간대행)위탁업체명위탁비용(백만원-년)위탁계약기간직원총수(명)안전사고건수
0충청북도청주시청주시청주충청북도 청주시 흥덕구 옥산면 미호로 555 청주 공공하수처리시설28000000280000289244.400.0289244.4263182.900.0263182.9154.91.20.00.0158.23.843.311.444.260.091410163899.244445.5표준활성슬러지법,CNR<NA>530.30.0109.0263.4043-201-48151992-04-231992-05-01210009.0자외선금강미호천미호천500톤 이상(Ⅱ지역)미호천Ⅲ3.337747770.0286.1민간(대행)(주)건양기술공사건축사무소,(주)홍익기술단,청수기술환경(주),㈜에코비트워터6757.02019-01-01~2024-12-31510
1충청북도청주시청주시내수충청북도 청원군 내수4길 11580000080005000.300.05000.35121.200.05121.2185.91.50.00.0152.93.061.129.044.450.071453731399.2922.1HDF<NA>269.90.00.00.0043-214-81852006-06-302006-07-0131518.0자외선금강석화천미호천500톤 이상(Ⅱ지역)미호천Ⅲ2.64438008.027.5민간(대행)(주)영진엔지니어링,환경시설관리(주)2795.02018-01-01~2022-12-31180
2충청북도청주시청주시강내충청북도 청주시 흥덕구 강내면 탑연리 259-140000040002938.100.02938.12984.100.02984.1238.91.70.00.0261.32.769.2411.55.330.041583531299.3697.0SMMIAR<NA>0.00.00.00.0043-235-81872012-11-212012-11-2121053.0자외선금강미호천미호천500톤 이상(Ⅱ지역)미호천Ⅲ11.4958757.025.5민간(대행)(주)영진엔지니어링,환경시설관리(주)1044.02018-01-01~2022-12-3160
3충청북도청주시청주시오창충청북도 청원군 오창제방길 281 오창공공하수처리시설33000033001758.800.01758.81613.400.01613.4268.51.60.00.0307.82.668.878.536.050.051747731399.4469.4KSMBRKSMBR,IPR0.00.00.00.0043-216-07382012-06-052012-06-0526036.0자외선금강미호천미호천500톤 이상(Ⅱ지역)미호천Ⅲ5.71713347.023.9민간(대행)(주)영진엔지니어링,환경시설관리주식회사1125.02018-01-01~2022-12-3160
4충청북도청주시청주시옥산충청북도 청주시 흥덕구 옥산면 신촌리 292번지26000026002035.700.02035.71778.900.01778.9173.81.30.00.0157.31.849.673.935.440.04170356499.3351.3SBR,섬유디스크필터선회와류식 SBR0.00.00.00.0043-711-12432015-09-212015-10-2620350.0자외선금강병천천미호천500톤 이상(Ⅱ지역)미호천Ⅲ18.1556090.023.0민간(대행)(주)건양기술공사건축사무소,(주)동명기술공단종합건축사사무소900.02018-01-01~2022-12-3160
5충청북도청주시청주시오송충청북도 청주시 흥덕구 오송읍 서평리 581-2420000020001188.000.01188.01169.500.01169.5192.41.10.00.0222.01.358.767.125.360.061515481099.4227.2KSMBRKS-MBR Process(침지형막분리공법)0.00.00.00.0043-236-58162014-03-212014-05-1421358.0<NA>금강미호천미호천500톤 이상(Ⅱ지역)미호천Ⅲ11.11127644.032.4민간(대행)(주)영진엔지니어링,환경시설관리주식회사842.02018-01-01~2022-12-3160
6충청북도청주시청주시남이청주시 서원구 남이면 청남로 89610000010001131.400.01131.41102.500.01102.5255.41.50.00.0273.21.865.992.287.060.039050002799.4287.2선회와류식 SBR,섬유디스크필터선회와류식 SBR공법0.00.00.00.0043-268-62502018-03-232018-09-2113448.0염소 자외선 오존 기타금강외천천금강하류500톤 이상(Ⅱ지역)대청댐하류Ⅱ0.0481192.00.0민간(대행)(주)두현이엔씨,(주)홍익기술단761.52018-12-03~2022-12-3160
7충청북도청주시청주시문의충청북도 청원군 대청호반로 8751000010000566.80566.80.0495.30495.30.0161.41.30.00.0132.11.846.666.274.920.02110063699.290.7장기포기법<NA>0.00.00.00.0043-711-12331986-10-311986-11-012502.0자외선금강무심천미호천500톤 이상(Ⅱ지역)미호천Ⅲ3.5618823.04.9민간(대행)(주)건양기술공사건축사무소,(주)동명기술공단종합건축사사무소979.02018-01-01~2022-12-3180
8충청북도청주시청주시미원충청북도 청주시 상당구 미원면 성대1길 21370000700786.800.0786.8744.900.0744.9155.11.20.00.0150.21.633.773.613.580.0611798999.2121.1PSBRPSBR0.00.00.00.0043-293-02082004-12-132004-12-146315.0자외선한강미원천남한강상류500톤 이상(Ⅲ지역)남한강상류Ⅰa5.7260140.03.6민간(대행)(주)영진엔지니어링,환경시설관리(주)310.02018-01-01~2022-12-3120
9충청북도청주시청주시품곡충청북도 청원군 덕유남계로 234-2750005000370.80370.80.0322.40322.40.075.01.80.00.066.61.330.9611.683.030.04750634697.627.1산화구<NA>0.00.00.00.0043-711-12331999-12-312000-01-015170.0염소금강등동천대청댐500톤 이상(Ⅰ지역)대청댐Ⅰa0.0177400.00.0민간(대행)(주)건양기술공사건축사무소,(주)동명기술공단종합건축사사무소233.02018-01-01~2022-12-3120
시도구군행정구역명시설명소재지시설용량(500세제곱미터-일 이상-미만)시설용량 물리적(세제곱미터-일)시설용량 생물학적(세제곱미터-일)시설용량 고도(세제곱미터-일)유입하수량(500세제곱미터-일 이상-미만)유입하수량 물리적(세제곱미터-일)유입하수량 생물학적(세제곱미터-일)유입하수량 고도(세제곱미터-일)방류량(500세제곱미터-일 이상-미만)방류량 물리적(세제곱미터-일)방류량 생물학적(세제곱미터-일)방류량 고도(세제곱미터-일)유입 생화학적 산소요구량(BOD)방류 생물학적 산소 요구량(BOD)유입 화학적 산소 요구량(COD)방류 화학적 산소 요구량(COD)유입 부유물질량(SS)방류 부유물질량(SS)유입 총질소(T-N)방류 총질소(T-N)유입 총인(T-P)방류 총인(T-P)유입총대장균군수방류총대장균군수처리효율(퍼센트)처리부하량(킬로그램 당 생화학적 산소유구량(BOD-D))처리방법적용신기술분뇨 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)축산 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)침출수 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)기타 연계처리량(세제곱미터-일 500세제곱미터-일 이상-미만)전화번호준공일가동개시일사업비(백만원)방류수소독방법수계지류세부단위구역지역구분중권역역 번호재생에너지이용률(퍼센트)연간 총 전력사용량(kWh-년)하수처리량당CO2배출량(kgCO2-세제곱미터)운영주체(자체-공기업-민간대행)위탁업체명위탁비용(백만원-년)위탁계약기간직원총수(명)안전사고건수
343충청북도단양군단양군가산충청북도 단양군 단성면 가산리 89130003046.300.046.346.300.046.3151.43.00.00.0177.12.834.915.073.690.7217633311498.06.9IC-SBR<NA>0.00.00.00.0043-421-86132016-10-112016-12-121077.0염소 자외선 오존 기타한강단양천남한강상류50톤 미만충주댐Ⅰa0.012437.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
344충청북도단양군단양군보발2리가곡면 보발2리 296-230003032.200.032.232.200.032.2122.73.10.00.080.42.726.537.222.870.814386712497.53.9FNR<NA>0.00.00.00.0043-421-86142009-12-092009-12-09230.0염소 자외선 오존 기타한강하일천남한강상류50톤 미만충주댐Ⅰa0.029044.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
345충청북도단양군단양군사인암리대강면 사인암리 9-1730003019.800.019.819.800.019.8109.73.30.00.066.73.317.416.891.650.761825035697.02.1BSTS-II<NA>0.00.00.00.0043-421-86132009-12-092009-12-09264.0염소 자외선 오존 기타한강단양천남한강상류50톤 미만충주댐Ⅰa0.017704.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
346충청북도단양군단양군상시충청북도 단양군 매포읍 상시리 30330003022.400.022.422.400.022.4138.43.50.00.0122.12.844.356.844.680.6911841718097.53.0IC-SBR<NA>0.00.00.00.0043-421-86132015-12-232016-01-221220.0염소 자외선 오존 기타한강매포천남한강상류50톤 미만충주댐Ⅰa0.018906.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
347충청북도단양군단양군양당리단성면 양당리 71-430003021.600.021.621.600.021.6120.93.30.00.0101.73.820.766.492.170.792808316797.32.5KM-SBR<NA>0.00.00.00.0043-421-86132009-12-092009-12-09367.0염소 자외선 오존 기타한강단양천남한강상류50톤 미만충주댐Ⅰa0.013029.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
348충청북도단양군단양군연곡1단양군 어상천면 연곡1리 77730003011.100.011.111.100.011.1158.92.80.00.0168.82.938.266.896.471.23760837398.21.7KM-SBR<NA>0.00.00.00.0<NA>2018-12-172019-01-181031.0염소 자외선 오존 기타한강어곡천남한강상류50톤 미만충주댐Ⅰa0.012392.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
349충청북도단양군단양군노동충청북도 단양군 단양읍 노동리 258-220002042.300.042.342.300.042.3137.73.30.00.0123.32.521.335.562.270.558058328397.65.7IC-SBR<NA>0.00.00.00.0<NA>2018-12-172019-01-181618.0염소 자외선 오존 기타한강노동천남한강상류50톤 미만충주댐Ⅰa0.07799.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
350충청북도단양군단양군하리 영춘영춘면 하리 122-142000201.000.01.01.000.01.0119.02.70.00.063.82.415.956.642.191.0347254397.70.1KM-SBR<NA>0.00.00.00.0043-421-86132009-12-092009-12-09155.0염소 오존 기타한강하일천남한강상류50톤 미만충주댐Ⅰa0.04340.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
351충청북도단양군단양군삼곡리매포읍 삼곡리 56-71000102.700.02.72.700.02.7144.24.10.00.0110.03.736.2315.543.110.994876715997.20.4A2EBC<NA>0.00.00.00.0043-421-86132009-12-092009-12-09124.0염소 자외선 오존 기타한강매포천남한강상류50톤 미만충주댐Ⅰa0.010025.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100
352충청북도단양군단양군어의곡1리가곡면 어의곡1리 267-610001010.800.010.810.800.010.8137.33.20.00.097.13.327.88.573.061.126964624597.71.4BSTS-II<NA>0.00.00.00.0043-421-86132009-12-092009-12-09120.0염소 자외선 오존 기타한강하일천남한강상류50톤 미만충주댐Ⅰa0.04160.00.0민간(대행)(주)에코비트워터,의림환경에너텍(주0.02015-08-07~2021-12-3100