Overview

Dataset statistics

Number of variables7
Number of observations5478
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory326.5 KiB
Average record size in memory61.0 B

Variable types

Categorical1
DateTime1
Numeric5

Dataset

Description전북특별자치도 진안군 2009년 1월 1일부터 2023년 12월 31일까지 하수처리장 일별 방류수질 정보를 제공합니다.BOD(생화학적 산소요구량), TOC(총유기탄소량), SS(부유물질), T-N(총질소), T-P(총인)에 대한 내용을 담고 있습니다.참고사항1. 20년 12월 말까지는 COD(화학적산소요구량)가 관리지표 였지만 21년 1월부터 TOC(총유기탄소량)으로 전환되어 관리
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15100367/fileData.do

Alerts

시군구명 has constant value ""Constant
날짜 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:38:42.699042
Analysis finished2024-03-14 10:38:50.605780
Duration7.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.9 KiB
전북특별자치도 진안군
5478 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 진안군
2nd row전북특별자치도 진안군
3rd row전북특별자치도 진안군
4th row전북특별자치도 진안군
5th row전북특별자치도 진안군

Common Values

ValueCountFrequency (%)
전북특별자치도 진안군 5478
100.0%

Length

2024-03-14T19:38:50.809254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:38:51.101320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 5478
50.0%
진안군 5478
50.0%

날짜
Date

UNIQUE 

Distinct5478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size42.9 KiB
Minimum2009-01-01 00:00:00
Maximum2023-12-31 00:00:00
2024-03-14T19:38:51.422404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:51.848431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

생물화학적 산소요구량(BOD)
Real number (ℝ)

Distinct199
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3850566
Minimum0
Maximum7.8
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2024-03-14T19:38:52.255705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.51
Q10.8
median1.1
Q31.57
95-th percentile3.4
Maximum7.8
Range7.8
Interquartile range (IQR)0.77

Descriptive statistics

Standard deviation0.95129034
Coefficient of variation (CV)0.68682417
Kurtosis7.6646106
Mean1.3850566
Median Absolute Deviation (MAD)0.3
Skewness2.3578066
Sum7587.34
Variance0.90495332
MonotonicityNot monotonic
2024-03-14T19:38:52.718411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 456
 
8.3%
0.9 428
 
7.8%
1.1 392
 
7.2%
0.8 311
 
5.7%
1.2 260
 
4.7%
1.3 257
 
4.7%
0.7 207
 
3.8%
1.4 187
 
3.4%
1.5 130
 
2.4%
0.6 125
 
2.3%
Other values (189) 2725
49.7%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
0.1 3
 
0.1%
0.2 3
 
0.1%
0.24 2
 
< 0.1%
0.25 1
 
< 0.1%
0.29 1
 
< 0.1%
0.3 30
0.5%
0.31 3
 
0.1%
0.32 3
 
0.1%
0.34 4
 
0.1%
ValueCountFrequency (%)
7.8 1
 
< 0.1%
7.7 1
 
< 0.1%
7.6 2
 
< 0.1%
7.4 2
 
< 0.1%
7.3 1
 
< 0.1%
7.2 4
0.1%
7.1 7
0.1%
6.9 3
0.1%
6.8 1
 
< 0.1%
6.7 1
 
< 0.1%

총유기탄소량(TOC)
Real number (ℝ)

Distinct297
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9784892
Minimum1.3
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2024-03-14T19:38:53.153006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile3
Q14.68
median5.82
Q37.2
95-th percentile9.2
Maximum22.4
Range21.1
Interquartile range (IQR)2.52

Descriptive statistics

Standard deviation1.9436
Coefficient of variation (CV)0.32509886
Kurtosis3.095342
Mean5.9784892
Median Absolute Deviation (MAD)1.26
Skewness0.78875992
Sum32750.164
Variance3.777581
MonotonicityNot monotonic
2024-03-14T19:38:53.566301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.8 111
 
2.0%
5.7 104
 
1.9%
6.3 104
 
1.9%
6.5 102
 
1.9%
6.2 99
 
1.8%
6.4 99
 
1.8%
6.1 96
 
1.8%
5.9 96
 
1.8%
6.6 94
 
1.7%
7.1 93
 
1.7%
Other values (287) 4480
81.8%
ValueCountFrequency (%)
1.3 1
 
< 0.1%
1.5 1
 
< 0.1%
1.6 2
 
< 0.1%
1.7 1
 
< 0.1%
1.8 1
 
< 0.1%
1.9 4
 
0.1%
2.0 10
0.2%
2.04 2
 
< 0.1%
2.06 1
 
< 0.1%
2.1 20
0.4%
ValueCountFrequency (%)
22.4 1
< 0.1%
21.9 1
< 0.1%
19.9 1
< 0.1%
18.6 1
< 0.1%
17.6 1
< 0.1%
15.9 1
< 0.1%
15.5 1
< 0.1%
15.2 1
< 0.1%
15.0 1
< 0.1%
14.6 1
< 0.1%

부유물질(SS)
Real number (ℝ)

Distinct68
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2854691
Minimum0.2
Maximum8.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2024-03-14T19:38:53.976707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.6
Q11.2
median2
Q33.2
95-th percentile4.6
Maximum8.8
Range8.6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3529823
Coefficient of variation (CV)0.59199325
Kurtosis0.20603013
Mean2.2854691
Median Absolute Deviation (MAD)1
Skewness0.68769302
Sum12519.8
Variance1.8305611
MonotonicityNot monotonic
2024-03-14T19:38:54.316344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 426
 
7.8%
1.2 403
 
7.4%
1.0 347
 
6.3%
2.8 323
 
5.9%
2.0 320
 
5.8%
2.4 308
 
5.6%
3.2 302
 
5.5%
1.6 274
 
5.0%
0.6 253
 
4.6%
4.0 242
 
4.4%
Other values (58) 2280
41.6%
ValueCountFrequency (%)
0.2 24
 
0.4%
0.3 5
 
0.1%
0.4 167
 
3.0%
0.5 37
 
0.7%
0.6 253
4.6%
0.7 26
 
0.5%
0.8 426
7.8%
0.9 33
 
0.6%
1.0 347
6.3%
1.1 22
 
0.4%
ValueCountFrequency (%)
8.8 2
 
< 0.1%
8.4 3
0.1%
8.1 1
 
< 0.1%
8.0 1
 
< 0.1%
7.8 1
 
< 0.1%
7.6 4
0.1%
7.2 3
0.1%
6.8 7
0.1%
6.6 3
0.1%
6.5 3
0.1%

총질소(T-N)
Real number (ℝ)

Distinct2085
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6481009
Minimum0.21
Maximum18.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2024-03-14T19:38:54.609003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.21
5-th percentile1.6602
Q12.784
median3.9445
Q35.9025
95-th percentile9.97975
Maximum18.36
Range18.15
Interquartile range (IQR)3.1185

Descriptive statistics

Standard deviation2.5938504
Coefficient of variation (CV)0.5580452
Kurtosis1.4389287
Mean4.6481009
Median Absolute Deviation (MAD)1.3835
Skewness1.2326493
Sum25462.297
Variance6.72806
MonotonicityNot monotonic
2024-03-14T19:38:54.887028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.64 102
 
1.9%
3.84 78
 
1.4%
3.36 77
 
1.4%
3.0 73
 
1.3%
3.12 71
 
1.3%
2.88 69
 
1.3%
2.16 58
 
1.1%
2.4 57
 
1.0%
3.6 55
 
1.0%
3.96 54
 
1.0%
Other values (2075) 4784
87.3%
ValueCountFrequency (%)
0.21 1
< 0.1%
0.45 1
< 0.1%
0.523 1
< 0.1%
0.547 1
< 0.1%
0.564 1
< 0.1%
0.576 1
< 0.1%
0.6 1
< 0.1%
0.643 1
< 0.1%
0.684 1
< 0.1%
0.69 1
< 0.1%
ValueCountFrequency (%)
18.36 1
< 0.1%
16.272 1
< 0.1%
15.198 1
< 0.1%
15.138 1
< 0.1%
15.012 1
< 0.1%
14.904 1
< 0.1%
14.832 1
< 0.1%
14.814 1
< 0.1%
14.76 2
< 0.1%
14.754 1
< 0.1%

총인(T-P)
Real number (ℝ)

Distinct760
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17771358
Minimum0.005
Maximum1.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2024-03-14T19:38:55.146982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.005
5-th percentile0.025
Q10.056
median0.087
Q30.162
95-th percentile0.712
Maximum1.28
Range1.275
Interquartile range (IQR)0.106

Descriptive statistics

Standard deviation0.21690711
Coefficient of variation (CV)1.2205432
Kurtosis3.2920582
Mean0.17771358
Median Absolute Deviation (MAD)0.039
Skewness2.0254812
Sum973.515
Variance0.047048693
MonotonicityNot monotonic
2024-03-14T19:38:55.564712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.062 102
 
1.9%
0.082 84
 
1.5%
0.086 76
 
1.4%
0.077 72
 
1.3%
0.101 72
 
1.3%
0.072 70
 
1.3%
0.067 67
 
1.2%
0.096 63
 
1.2%
0.091 63
 
1.2%
0.052 60
 
1.1%
Other values (750) 4749
86.7%
ValueCountFrequency (%)
0.005 1
 
< 0.1%
0.007 1
 
< 0.1%
0.009 3
 
0.1%
0.01 4
 
0.1%
0.011 10
0.2%
0.012 19
0.3%
0.014 16
0.3%
0.015 13
0.2%
0.016 18
0.3%
0.017 5
 
0.1%
ValueCountFrequency (%)
1.28 1
< 0.1%
1.275 1
< 0.1%
1.2125 1
< 0.1%
1.205 1
< 0.1%
1.17 1
< 0.1%
1.16 1
< 0.1%
1.1375 1
< 0.1%
1.13 2
< 0.1%
1.107 1
< 0.1%
1.098 1
< 0.1%

Interactions

2024-03-14T19:38:48.391886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:43.056072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:44.433385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:45.720144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:47.017633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:48.676525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:43.344918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:44.706176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:45.995908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:47.309306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:48.929399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:43.606700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:44.947558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:46.240231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:47.568392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:49.389073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:43.871161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:45.194745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:46.486943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:47.835413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:49.667284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:44.156219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:45.459882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:46.754786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:38:48.113787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:38:55.805274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생물화학적 산소요구량(BOD)총유기탄소량(TOC)부유물질(SS)총질소(T-N)총인(T-P)
생물화학적 산소요구량(BOD)1.0000.3470.4780.2260.318
총유기탄소량(TOC)0.3471.0000.4280.3810.325
부유물질(SS)0.4780.4281.0000.3920.411
총질소(T-N)0.2260.3810.3921.0000.259
총인(T-P)0.3180.3250.4110.2591.000
2024-03-14T19:38:55.995295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생물화학적 산소요구량(BOD)총유기탄소량(TOC)부유물질(SS)총질소(T-N)총인(T-P)
생물화학적 산소요구량(BOD)1.0000.3150.3960.050-0.072
총유기탄소량(TOC)0.3151.0000.4190.2640.056
부유물질(SS)0.3960.4191.0000.3370.052
총질소(T-N)0.0500.2640.3371.0000.024
총인(T-P)-0.0720.0560.0520.0241.000

Missing values

2024-03-14T19:38:50.043126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:38:50.439541image/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

시군구명날짜생물화학적 산소요구량(BOD)총유기탄소량(TOC)부유물질(SS)총질소(T-N)총인(T-P)
0전북특별자치도 진안군2009-01-010.64.51.42.7840.484
1전북특별자치도 진안군2009-01-020.44.31.63.1680.508
2전북특별자치도 진안군2009-01-030.44.21.22.7840.394
3전북특별자치도 진안군2009-01-040.54.41.42.880.44
4전북특별자치도 진안군2009-01-050.64.51.63.1680.502
5전북특별자치도 진안군2009-01-060.54.41.42.880.488
6전북특별자치도 진안군2009-01-070.44.51.02.7840.58
7전북특별자치도 진안군2009-01-080.74.81.23.2640.494
8전북특별자치도 진안군2009-01-090.64.91.43.4560.662
9전북특별자치도 진안군2009-01-100.75.02.03.840.594
시군구명날짜생물화학적 산소요구량(BOD)총유기탄소량(TOC)부유물질(SS)총질소(T-N)총인(T-P)
5468전북특별자치도 진안군2023-12-221.32.50.83.4680.064
5469전북특별자치도 진안군2023-12-231.63.01.22.0520.116
5470전북특별자치도 진안군2023-12-240.72.91.21.530.067
5471전북특별자치도 진안군2023-12-252.92.93.22.220.14
5472전북특별자치도 진안군2023-12-263.72.94.02.1720.106
5473전북특별자치도 진안군2023-12-274.02.43.91.1880.198
5474전북특별자치도 진안군2023-12-282.64.31.22.760.116
5475전북특별자치도 진안군2023-12-294.13.43.23.0480.157
5476전북특별자치도 진안군2023-12-301.95.01.97.1760.096
5477전북특별자치도 진안군2023-12-312.55.32.07.2060.104