Overview

Dataset statistics

Number of variables11
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory100.6 B

Variable types

Categorical4
DateTime1
Numeric6

Dataset

Description세종시설관리공단 조치원공공하수처리시설 방류수 수질 데이터로 2024년 2월 부터 pH, BOD, TOC, SS, T-N, T-P, 총대장균군 항목을 제공합니다.
Author세종특별자치시시설관리공단
URLhttps://www.data.go.kr/data/15127231/fileData.do

Alerts

장소 has constant value ""Constant
수온 is highly overall correlated with 방류 부유물질(SS)High correlation
방류 부유물질(SS) is highly overall correlated with 수온 and 1 other fieldsHigh correlation
총대장균군 is highly overall correlated with 방류 부유물질(SS)High correlation
총대장균군 is highly imbalanced (72.8%)Imbalance
날짜 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:06:25.595591
Analysis finished2024-04-06 08:06:35.087302
Duration9.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장소
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
조치원공공하수처리시설
29 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
조치원공공하수처리시설 29
100.0%

Length

2024-04-06T17:06:35.216886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:06:35.458990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조치원공공하수처리시설 29
100.0%

날짜
Date

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2024-02-01 00:00:00
Maximum2024-02-29 00:00:00
2024-04-06T17:06:35.623091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:36.025992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

요일
Categorical

Distinct7
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
월요일
5 
화요일
4 
수요일
4 
목요일
4 
금요일
4 
Other values (2)
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row월요일
2nd row화요일
3rd row수요일
4th row목요일
5th row금요일

Common Values

ValueCountFrequency (%)
월요일 5
17.2%
화요일 4
13.8%
수요일 4
13.8%
목요일 4
13.8%
금요일 4
13.8%
토요일 4
13.8%
일요일 4
13.8%

Length

2024-04-06T17:06:36.352431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:06:36.723107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
월요일 5
17.2%
화요일 4
13.8%
수요일 4
13.8%
목요일 4
13.8%
금요일 4
13.8%
토요일 4
13.8%
일요일 4
13.8%

수온
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.92069
Minimum11.4
Maximum14.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:36.968785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.4
5-th percentile11.74
Q112.4
median12.8
Q313.3
95-th percentile14.5
Maximum14.6
Range3.2
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.8372486
Coefficient of variation (CV)0.064799064
Kurtosis-0.011171882
Mean12.92069
Median Absolute Deviation (MAD)0.5
Skewness0.53879487
Sum374.7
Variance0.70098522
MonotonicityNot monotonic
2024-04-06T17:06:37.259906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
12.7 3
 
10.3%
12.5 3
 
10.3%
13.0 3
 
10.3%
12.3 2
 
6.9%
12.1 2
 
6.9%
12.8 2
 
6.9%
13.7 2
 
6.9%
14.5 2
 
6.9%
11.5 1
 
3.4%
11.4 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
11.4 1
 
3.4%
11.5 1
 
3.4%
12.1 2
6.9%
12.2 1
 
3.4%
12.3 2
6.9%
12.4 1
 
3.4%
12.5 3
10.3%
12.7 3
10.3%
12.8 2
6.9%
12.9 1
 
3.4%
ValueCountFrequency (%)
14.6 1
 
3.4%
14.5 2
6.9%
14.4 1
 
3.4%
13.7 2
6.9%
13.4 1
 
3.4%
13.3 1
 
3.4%
13.2 1
 
3.4%
13.0 3
10.3%
12.9 1
 
3.4%
12.8 2
6.9%

수소이온농도
Categorical

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
6.9
15 
7.0
9 
6.8
5 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7.0
2nd row6.9
3rd row6.8
4th row6.9
5th row7.0

Common Values

ValueCountFrequency (%)
6.9 15
51.7%
7.0 9
31.0%
6.8 5
 
17.2%

Length

2024-04-06T17:06:37.526491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:06:37.807801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.9 15
51.7%
7.0 9
31.0%
6.8 5
 
17.2%

방류 생물화학적산소요구량(BOD)
Real number (ℝ)

Distinct14
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1862069
Minimum0.5
Maximum1.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:38.077433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.54
Q11
median1.2
Q31.5
95-th percentile1.76
Maximum1.8
Range1.3
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.37294593
Coefficient of variation (CV)0.3144021
Kurtosis-0.6921488
Mean1.1862069
Median Absolute Deviation (MAD)0.3
Skewness-0.10558065
Sum34.4
Variance0.13908867
MonotonicityNot monotonic
2024-04-06T17:06:38.318790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1.2 4
13.8%
1.0 4
13.8%
1.3 3
10.3%
1.8 2
6.9%
1.6 2
6.9%
1.7 2
6.9%
1.5 2
6.9%
0.5 2
6.9%
1.1 2
6.9%
0.9 2
6.9%
Other values (4) 4
13.8%
ValueCountFrequency (%)
0.5 2
6.9%
0.6 1
 
3.4%
0.7 1
 
3.4%
0.8 1
 
3.4%
0.9 2
6.9%
1.0 4
13.8%
1.1 2
6.9%
1.2 4
13.8%
1.3 3
10.3%
1.4 1
 
3.4%
ValueCountFrequency (%)
1.8 2
6.9%
1.7 2
6.9%
1.6 2
6.9%
1.5 2
6.9%
1.4 1
 
3.4%
1.3 3
10.3%
1.2 4
13.8%
1.1 2
6.9%
1.0 4
13.8%
0.9 2
6.9%

방류 총유기탄소량(TOC)
Real number (ℝ)

Distinct18
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6586207
Minimum3.2
Maximum6.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:38.524237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2
5-th percentile3.64
Q14.4
median4.6
Q34.8
95-th percentile5.82
Maximum6.3
Range3.1
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.68217993
Coefficient of variation (CV)0.14643389
Kurtosis0.54607847
Mean4.6586207
Median Absolute Deviation (MAD)0.2
Skewness0.35084749
Sum135.1
Variance0.46536946
MonotonicityNot monotonic
2024-04-06T17:06:38.743964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
4.8 6
20.7%
4.4 5
17.2%
4.1 2
 
6.9%
4.6 2
 
6.9%
5.2 1
 
3.4%
5.7 1
 
3.4%
3.7 1
 
3.4%
4.0 1
 
3.4%
4.2 1
 
3.4%
3.2 1
 
3.4%
Other values (8) 8
27.6%
ValueCountFrequency (%)
3.2 1
 
3.4%
3.6 1
 
3.4%
3.7 1
 
3.4%
4.0 1
 
3.4%
4.1 2
 
6.9%
4.2 1
 
3.4%
4.4 5
17.2%
4.5 1
 
3.4%
4.6 2
 
6.9%
4.7 1
 
3.4%
ValueCountFrequency (%)
6.3 1
 
3.4%
5.9 1
 
3.4%
5.7 1
 
3.4%
5.6 1
 
3.4%
5.4 1
 
3.4%
5.2 1
 
3.4%
4.9 1
 
3.4%
4.8 6
20.7%
4.7 1
 
3.4%
4.6 2
 
6.9%

방류 부유물질(SS)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3724138
Minimum1.5
Maximum3.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:38.955422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile1.68
Q12.1
median2.3
Q32.7
95-th percentile3.12
Maximum3.6
Range2.1
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.46820062
Coefficient of variation (CV)0.19735201
Kurtosis0.57225131
Mean2.3724138
Median Absolute Deviation (MAD)0.3
Skewness0.51225146
Sum68.8
Variance0.21921182
MonotonicityNot monotonic
2024-04-06T17:06:39.156598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2.4 5
17.2%
2.3 4
13.8%
2.0 2
 
6.9%
2.8 2
 
6.9%
2.1 2
 
6.9%
2.7 2
 
6.9%
2.2 2
 
6.9%
1.9 2
 
6.9%
3.6 1
 
3.4%
2.9 1
 
3.4%
Other values (6) 6
20.7%
ValueCountFrequency (%)
1.5 1
 
3.4%
1.6 1
 
3.4%
1.8 1
 
3.4%
1.9 2
 
6.9%
2.0 2
 
6.9%
2.1 2
 
6.9%
2.2 2
 
6.9%
2.3 4
13.8%
2.4 5
17.2%
2.6 1
 
3.4%
ValueCountFrequency (%)
3.6 1
 
3.4%
3.2 1
 
3.4%
3.0 1
 
3.4%
2.9 1
 
3.4%
2.8 2
 
6.9%
2.7 2
 
6.9%
2.6 1
 
3.4%
2.4 5
17.2%
2.3 4
13.8%
2.2 2
 
6.9%

방류 총질소(T-N)
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9062414
Minimum3.549
Maximum6.722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:39.423899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.549
5-th percentile3.6748
Q14.302
median4.745
Q35.648
95-th percentile6.2056
Maximum6.722
Range3.173
Interquartile range (IQR)1.346

Descriptive statistics

Standard deviation0.85205821
Coefficient of variation (CV)0.17366822
Kurtosis-0.67792221
Mean4.9062414
Median Absolute Deviation (MAD)0.652
Skewness0.18136478
Sum142.281
Variance0.72600319
MonotonicityNot monotonic
2024-04-06T17:06:39.696508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
5.648 2
 
6.9%
3.634 1
 
3.4%
4.14 1
 
3.4%
4.724 1
 
3.4%
5.397 1
 
3.4%
4.392 1
 
3.4%
4.745 1
 
3.4%
5.325 1
 
3.4%
4.302 1
 
3.4%
4.756 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
3.549 1
3.4%
3.634 1
3.4%
3.736 1
3.4%
3.744 1
3.4%
3.789 1
3.4%
4.086 1
3.4%
4.14 1
3.4%
4.302 1
3.4%
4.392 1
3.4%
4.617 1
3.4%
ValueCountFrequency (%)
6.722 1
3.4%
6.428 1
3.4%
5.872 1
3.4%
5.808 1
3.4%
5.77 1
3.4%
5.733 1
3.4%
5.648 2
6.9%
5.397 1
3.4%
5.325 1
3.4%
5.311 1
3.4%

방류 총인(T-P)
Real number (ℝ)

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049344828
Minimum0.004
Maximum0.169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-06T17:06:39.959054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.004
5-th percentile0.0138
Q10.024
median0.043
Q30.061
95-th percentile0.1082
Maximum0.169
Range0.165
Interquartile range (IQR)0.037

Descriptive statistics

Standard deviation0.034717509
Coefficient of variation (CV)0.70356936
Kurtosis4.0223921
Mean0.049344828
Median Absolute Deviation (MAD)0.019
Skewness1.71438
Sum1.431
Variance0.0012053054
MonotonicityNot monotonic
2024-04-06T17:06:40.229351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.043 2
 
6.9%
0.044 2
 
6.9%
0.023 1
 
3.4%
0.053 1
 
3.4%
0.109 1
 
3.4%
0.085 1
 
3.4%
0.063 1
 
3.4%
0.013 1
 
3.4%
0.041 1
 
3.4%
0.107 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
0.004 1
3.4%
0.013 1
3.4%
0.015 1
3.4%
0.016 1
3.4%
0.02 1
3.4%
0.022 1
3.4%
0.023 1
3.4%
0.024 1
3.4%
0.029 1
3.4%
0.032 1
3.4%
ValueCountFrequency (%)
0.169 1
3.4%
0.109 1
3.4%
0.107 1
3.4%
0.085 1
3.4%
0.072 1
3.4%
0.071 1
3.4%
0.063 1
3.4%
0.061 1
3.4%
0.058 1
3.4%
0.053 1
3.4%

총대장균군
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
27 
11
 
1
1
 
1

Length

Max length2
Median length1
Mean length1.0344828
Min length1

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row11

Common Values

ValueCountFrequency (%)
0 27
93.1%
11 1
 
3.4%
1 1
 
3.4%

Length

2024-04-06T17:06:40.512892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:06:40.708457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
93.1%
11 1
 
3.4%
1 1
 
3.4%

Interactions

2024-04-06T17:06:32.289476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:26.446945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.520407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.056578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.121920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:31.152674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:32.535660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:26.622286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.735186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.231238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.306841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:31.396164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:32.739137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:26.847479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.987214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.392579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.502494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:31.564997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:33.124764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.010496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:28.170198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.562904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.680686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:31.724988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:33.549412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.171579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:28.319937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.765307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.824855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:31.895084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:34.078943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:27.335260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:28.882946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:29.947317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:30.970461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:06:32.057669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:06:40.833091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜요일수온수소이온농도방류 생물화학적산소요구량(BOD)방류 총유기탄소량(TOC)방류 부유물질(SS)방류 총질소(T-N)방류 총인(T-P)총대장균군
날짜1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
요일1.0001.0000.0000.0000.3880.2090.2900.0000.1390.000
수온1.0000.0001.0000.0000.0000.0000.5100.0000.0380.000
수소이온농도1.0000.0000.0001.0000.0000.3800.4000.0000.3370.000
방류 생물화학적산소요구량(BOD)1.0000.3880.0000.0001.0000.5450.0000.0000.2930.000
방류 총유기탄소량(TOC)1.0000.2090.0000.3800.5451.0000.0000.2880.0000.000
방류 부유물질(SS)1.0000.2900.5100.4000.0000.0001.0000.3890.4650.810
방류 총질소(T-N)1.0000.0000.0000.0000.0000.2880.3891.0000.0000.598
방류 총인(T-P)1.0000.1390.0380.3370.2930.0000.4650.0001.0000.470
총대장균군1.0000.0000.0000.0000.0000.0000.8100.5980.4701.000
2024-04-06T17:06:41.573556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총대장균군요일수소이온농도
총대장균군1.0000.0000.000
요일0.0001.0000.000
수소이온농도0.0000.0001.000
2024-04-06T17:06:41.847943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수온방류 생물화학적산소요구량(BOD)방류 총유기탄소량(TOC)방류 부유물질(SS)방류 총질소(T-N)방류 총인(T-P)요일수소이온농도총대장균군
수온1.0000.2500.3270.558-0.285-0.1280.0000.0000.000
방류 생물화학적산소요구량(BOD)0.2501.0000.2460.028-0.085-0.0800.1550.0000.000
방류 총유기탄소량(TOC)0.3270.2461.0000.1600.0270.2940.0000.1830.000
방류 부유물질(SS)0.5580.0280.1601.000-0.2100.1030.0770.1980.599
방류 총질소(T-N)-0.285-0.0850.027-0.2101.0000.0980.0000.0000.267
방류 총인(T-P)-0.128-0.0800.2940.1030.0981.0000.0000.2040.319
요일0.0000.1550.0000.0770.0000.0001.0000.0000.000
수소이온농도0.0000.0000.1830.1980.0000.2040.0001.0000.000
총대장균군0.0000.0000.0000.5990.2670.3190.0000.0001.000

Missing values

2024-04-06T17:06:34.493423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:06:34.966415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

장소날짜요일수온수소이온농도방류 생물화학적산소요구량(BOD)방류 총유기탄소량(TOC)방류 부유물질(SS)방류 총질소(T-N)방류 총인(T-P)총대장균군
0조치원공공하수처리시설2024-02-01월요일13.77.01.84.13.63.6340.0230
1조치원공공하수처리시설2024-02-02화요일13.76.91.24.82.73.5490.0220
2조치원공공하수처리시설2024-02-03수요일14.66.81.84.92.03.7360.0320
3조치원공공하수처리시설2024-02-04목요일14.56.91.45.62.85.3110.020
4조치원공공하수처리시설2024-02-05금요일14.47.01.35.43.25.770.06111
5조치원공공하수처리시설2024-02-06토요일14.57.01.04.72.14.6440.0290
6조치원공공하수처리시설2024-02-07일요일13.36.91.64.62.45.130.0470
7조치원공공하수처리시설2024-02-08월요일13.06.91.74.82.64.0860.0711
8조치원공공하수처리시설2024-02-09화요일11.47.01.54.41.84.7190.0580
9조치원공공하수처리시설2024-02-10수요일11.56.91.34.42.03.7440.0430
장소날짜요일수온수소이온농도방류 생물화학적산소요구량(BOD)방류 총유기탄소량(TOC)방류 부유물질(SS)방류 총질소(T-N)방류 총인(T-P)총대장균군
19조치원공공하수처리시설2024-02-20토요일12.56.91.05.22.95.2850.0440
20조치원공공하수처리시설2024-02-21일요일12.86.81.03.62.34.7560.0440
21조치원공공하수처리시설2024-02-22월요일12.36.90.63.22.24.3020.0340
22조치원공공하수처리시설2024-02-23화요일12.16.90.74.41.55.3250.1070
23조치원공공하수처리시설2024-02-24수요일12.46.90.94.22.85.6480.0410
24조치원공공하수처리시설2024-02-25목요일12.36.81.14.02.24.7450.0430
25조치원공공하수처리시설2024-02-26금요일13.06.81.23.72.35.6480.0130
26조치원공공하수처리시설2024-02-27토요일13.27.00.94.43.04.3920.0630
27조치원공공하수처리시설2024-02-28일요일13.47.01.24.82.45.3970.0850
28조치원공공하수처리시설2024-02-29월요일13.07.01.05.72.44.7240.1090