Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells19301
Missing cells (%)19.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory918.0 KiB
Average record size in memory94.0 B

Variable types

DateTime1
Categorical3
Numeric6

Dataset

Description측정일자,물재생센터명칭,처리장구분,계통구분,BOD,TOC(2021년 1월 이전자료는 COD),SS,T-N,TP,COCG
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15562/S/1/datasetView.do

Alerts

BOD is highly overall correlated with TOC(2021년 1월 이전자료는 COD) and 4 other fieldsHigh correlation
TOC(2021년 1월 이전자료는 COD) is highly overall correlated with BOD and 4 other fieldsHigh correlation
SS is highly overall correlated with BOD and 4 other fieldsHigh correlation
T-N is highly overall correlated with BOD and 4 other fieldsHigh correlation
TP is highly overall correlated with BOD and 4 other fieldsHigh correlation
COCG is highly overall correlated with BOD and 5 other fieldsHigh correlation
계통구분 is highly overall correlated with COCGHigh correlation
BOD has 2557 (25.6%) missing valuesMissing
TOC(2021년 1월 이전자료는 COD) has 3240 (32.4%) missing valuesMissing
SS has 2455 (24.6%) missing valuesMissing
T-N has 2594 (25.9%) missing valuesMissing
TP has 2566 (25.7%) missing valuesMissing
COCG has 5889 (58.9%) missing valuesMissing

Reproduction

Analysis started2024-05-10 23:45:34.221115
Analysis finished2024-05-10 23:45:52.467750
Duration18.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일자
Date

Distinct2090
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-04 00:00:00
Maximum2023-10-31 00:00:00
2024-05-10T23:45:52.693390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:53.234982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

물재생센터명칭
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중랑물재생센터
4045 
서남물재생센터
2343 
난지물재생센터
1969 
탄천물재생센터
1643 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row난지물재생센터
2nd row탄천물재생센터
3rd row중랑물재생센터
4th row중랑물재생센터
5th row서남물재생센터

Common Values

ValueCountFrequency (%)
중랑물재생센터 4045
40.5%
서남물재생센터 2343
23.4%
난지물재생센터 1969
19.7%
탄천물재생센터 1643
16.4%

Length

2024-05-10T23:45:53.652742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:45:53.934675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중랑물재생센터 4045
40.5%
서남물재생센터 2343
23.4%
난지물재생센터 1969
19.7%
탄천물재생센터 1643
16.4%

처리장구분
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제2처리장
3400 
제1처리장
3287 
제4처리장
1081 
제3처리장
1021 
처리장 구분없음
822 

Length

Max length8
Median length5
Mean length5.2466
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제2처리장
2nd row제1처리장
3rd row제4처리장
4th row제2처리장
5th row제1처리장

Common Values

ValueCountFrequency (%)
제2처리장 3400
34.0%
제1처리장 3287
32.9%
제4처리장 1081
 
10.8%
제3처리장 1021
 
10.2%
처리장 구분없음 822
 
8.2%
시설현대화 389
 
3.9%

Length

2024-05-10T23:45:54.272835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:45:54.580787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2처리장 3400
31.4%
제1처리장 3287
30.4%
제4처리장 1081
 
10.0%
제3처리장 1021
 
9.4%
처리장 822
 
7.6%
구분없음 822
 
7.6%
시설현대화 389
 
3.6%

계통구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
방류
2339 
2차
2053 
초침유출
2024 
초침유입
2023 
유입수
1561 

Length

Max length4
Median length3
Mean length2.9655
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
방류 2339
23.4%
2차 2053
20.5%
초침유출 2024
20.2%
초침유입 2023
20.2%
유입수 1561
15.6%

Length

2024-05-10T23:45:55.010081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:45:55.379579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방류 2339
23.4%
2차 2053
20.5%
초침유출 2024
20.2%
초침유입 2023
20.2%
유입수 1561
15.6%

BOD
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1960
Distinct (%)26.3%
Missing2557
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean74.41232
Minimum0
Maximum1776
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:45:55.786659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3
Q13.8
median54.2
Q3133.9
95-th percentile203.4
Maximum1776
Range1776
Interquartile range (IQR)130.1

Descriptive statistics

Standard deviation82.753229
Coefficient of variation (CV)1.1120904
Kurtosis26.574996
Mean74.41232
Median Absolute Deviation (MAD)52.1
Skewness2.2858907
Sum553850.9
Variance6848.097
MonotonicityNot monotonic
2024-05-10T23:45:56.248476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8 85
 
0.9%
2.2 78
 
0.8%
1.9 72
 
0.7%
2.0 71
 
0.7%
1.7 71
 
0.7%
2.3 69
 
0.7%
1.6 68
 
0.7%
2.4 68
 
0.7%
1.2 68
 
0.7%
1.5 66
 
0.7%
Other values (1950) 6727
67.3%
(Missing) 2557
 
25.6%
ValueCountFrequency (%)
0.0 12
 
0.1%
0.2 3
 
< 0.1%
0.3 8
 
0.1%
0.4 10
 
0.1%
0.43 1
 
< 0.1%
0.5 10
 
0.1%
0.57 1
 
< 0.1%
0.6 24
0.2%
0.7 23
0.2%
0.8 38
0.4%
ValueCountFrequency (%)
1776.0 1
< 0.1%
799.5 1
< 0.1%
708.0 1
< 0.1%
627.0 1
< 0.1%
611.5 1
< 0.1%
609.0 1
< 0.1%
554.7 1
< 0.1%
525.0 1
< 0.1%
510.2 1
< 0.1%
507.3 1
< 0.1%

TOC(2021년 1월 이전자료는 COD)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1120
Distinct (%)16.6%
Missing3240
Missing (%)32.4%
Infinite0
Infinite (%)0.0%
Mean38.186358
Minimum0
Maximum414
Zeros28
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:45:56.904322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.2
Q17.1
median28.2
Q366.6
95-th percentile91.605
Maximum414
Range414
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation34.607283
Coefficient of variation (CV)0.90627345
Kurtosis2.8659855
Mean38.186358
Median Absolute Deviation (MAD)23.1
Skewness0.96460701
Sum258139.78
Variance1197.664
MonotonicityNot monotonic
2024-05-10T23:45:57.563481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 81
 
0.8%
6.5 69
 
0.7%
7.0 69
 
0.7%
7.8 67
 
0.7%
8.0 67
 
0.7%
6.0 61
 
0.6%
6.6 58
 
0.6%
7.5 58
 
0.6%
7.4 57
 
0.6%
6.9 55
 
0.5%
Other values (1110) 6118
61.2%
(Missing) 3240
32.4%
ValueCountFrequency (%)
0.0 28
0.3%
1.0 2
 
< 0.1%
1.3 1
 
< 0.1%
1.5 3
 
< 0.1%
1.6 2
 
< 0.1%
1.7 2
 
< 0.1%
1.8 4
 
< 0.1%
2.0 3
 
< 0.1%
2.1 4
 
< 0.1%
2.2 8
 
0.1%
ValueCountFrequency (%)
414.0 1
< 0.1%
327.0 1
< 0.1%
281.8 1
< 0.1%
255.7 1
< 0.1%
229.3 1
< 0.1%
208.5 1
< 0.1%
199.7 1
< 0.1%
199.0 1
< 0.1%
187.3 1
< 0.1%
185.7 1
< 0.1%

SS
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct960
Distinct (%)12.7%
Missing2455
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean56.5763
Minimum0
Maximum840
Zeros16
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:45:58.030545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.706
Q13.5
median30
Q3100
95-th percentile166
Maximum840
Range840
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation68.145779
Coefficient of variation (CV)1.2044934
Kurtosis11.723238
Mean56.5763
Median Absolute Deviation (MAD)28
Skewness2.2743651
Sum426868.18
Variance4643.8471
MonotonicityNot monotonic
2024-05-10T23:45:58.538541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 229
 
2.3%
4.0 202
 
2.0%
3.5 175
 
1.8%
2.0 155
 
1.6%
2.8 138
 
1.4%
5.0 123
 
1.2%
3.2 118
 
1.2%
2.5 118
 
1.2%
4.5 113
 
1.1%
3.8 99
 
1.0%
Other values (950) 6075
60.8%
(Missing) 2455
24.6%
ValueCountFrequency (%)
0.0 16
 
0.2%
0.4 7
 
0.1%
0.5 9
 
0.1%
0.6 5
 
0.1%
0.7 9
 
0.1%
0.8 25
 
0.2%
0.9 2
 
< 0.1%
1.0 68
0.7%
1.1 3
 
< 0.1%
1.2 49
0.5%
ValueCountFrequency (%)
840.0 1
< 0.1%
708.0 1
< 0.1%
670.0 1
< 0.1%
650.0 2
< 0.1%
620.0 1
< 0.1%
590.0 1
< 0.1%
573.3 1
< 0.1%
570.0 1
< 0.1%
556.0 1
< 0.1%
550.0 1
< 0.1%

T-N
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6406
Distinct (%)86.5%
Missing2594
Missing (%)25.9%
Infinite0
Infinite (%)0.0%
Mean23.534432
Minimum3.037
Maximum135.534
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:45:58.948563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.037
5-th percentile8.65825
Q112.619
median20.114
Q333.72775
95-th percentile43.3925
Maximum135.534
Range132.497
Interquartile range (IQR)21.10875

Descriptive statistics

Standard deviation12.413686
Coefficient of variation (CV)0.5274691
Kurtosis0.75504479
Mean23.534432
Median Absolute Deviation (MAD)9.766
Skewness0.64061652
Sum174296
Variance154.09959
MonotonicityNot monotonic
2024-05-10T23:45:59.521609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.082 5
 
0.1%
13.3 4
 
< 0.1%
32.67 4
 
< 0.1%
13.5 4
 
< 0.1%
33.051 4
 
< 0.1%
32.347 4
 
< 0.1%
31.86 4
 
< 0.1%
10.049 4
 
< 0.1%
38.079 4
 
< 0.1%
34.233 4
 
< 0.1%
Other values (6396) 7365
73.7%
(Missing) 2594
 
25.9%
ValueCountFrequency (%)
3.037 1
< 0.1%
3.194 1
< 0.1%
3.473 1
< 0.1%
3.522 1
< 0.1%
3.602 1
< 0.1%
3.713 1
< 0.1%
3.893 1
< 0.1%
4.145 1
< 0.1%
4.529 1
< 0.1%
4.534 1
< 0.1%
ValueCountFrequency (%)
135.534 1
< 0.1%
123.247 1
< 0.1%
87.394 1
< 0.1%
84.837 1
< 0.1%
81.923 1
< 0.1%
80.394 1
< 0.1%
71.749 1
< 0.1%
71.616 1
< 0.1%
70.979 1
< 0.1%
69.919 1
< 0.1%

TP
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2714
Distinct (%)36.5%
Missing2566
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean1.9394904
Minimum0
Maximum27.163
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:46:00.154374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.08965
Q10.18
median1.276
Q33.439
95-th percentile4.61735
Maximum27.163
Range27.163
Interquartile range (IQR)3.259

Descriptive statistics

Standard deviation2.0283908
Coefficient of variation (CV)1.045837
Kurtosis10.856053
Mean1.9394904
Median Absolute Deviation (MAD)1.1915
Skewness1.85363
Sum14418.172
Variance4.1143693
MonotonicityNot monotonic
2024-05-10T23:46:00.749671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.201 30
 
0.3%
0.117 28
 
0.3%
0.13 27
 
0.3%
0.1 27
 
0.3%
0.2 26
 
0.3%
0.185 26
 
0.3%
0.188 26
 
0.3%
0.199 25
 
0.2%
0.12 24
 
0.2%
0.14 24
 
0.2%
Other values (2704) 7171
71.7%
(Missing) 2566
 
25.7%
ValueCountFrequency (%)
0.0 2
< 0.1%
0.014 1
 
< 0.1%
0.015 1
 
< 0.1%
0.02 1
 
< 0.1%
0.023 1
 
< 0.1%
0.024 1
 
< 0.1%
0.025 1
 
< 0.1%
0.031 2
< 0.1%
0.032 1
 
< 0.1%
0.033 3
< 0.1%
ValueCountFrequency (%)
27.163 1
< 0.1%
23.716 1
< 0.1%
20.063 1
< 0.1%
19.218 1
< 0.1%
17.661 1
< 0.1%
16.852 1
< 0.1%
16.61 1
< 0.1%
15.857 1
< 0.1%
15.704 2
< 0.1%
15.557 1
< 0.1%

COCG
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct757
Distinct (%)18.4%
Missing5889
Missing (%)58.9%
Infinite0
Infinite (%)0.0%
Mean63136.901
Minimum0
Maximum530000
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:46:01.315217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile34
Q1260
median1200
Q3114000
95-th percentile278000
Maximum530000
Range530000
Interquartile range (IQR)113740

Descriptive statistics

Standard deviation97249.862
Coefficient of variation (CV)1.5403015
Kurtosis2.1622406
Mean63136.901
Median Absolute Deviation (MAD)1189
Skewness1.6287318
Sum2.595558 × 108
Variance9.4575357 × 109
MonotonicityNot monotonic
2024-05-10T23:46:01.928761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3300 37
 
0.4%
210 36
 
0.4%
220 36
 
0.4%
50 35
 
0.4%
320 32
 
0.3%
200 31
 
0.3%
400 31
 
0.3%
240 30
 
0.3%
230 30
 
0.3%
1 30
 
0.3%
Other values (747) 3783
37.8%
(Missing) 5889
58.9%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 30
0.3%
2 22
0.2%
3 18
0.2%
4 21
0.2%
5 14
0.1%
6 9
 
0.1%
7 5
 
0.1%
8 11
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
530000 2
 
< 0.1%
500000 1
 
< 0.1%
490000 1
 
< 0.1%
470000 1
 
< 0.1%
460000 1
 
< 0.1%
450000 4
< 0.1%
440000 3
 
< 0.1%
430000 9
0.1%
420000 6
0.1%
410000 3
 
< 0.1%

Interactions

2024-05-10T23:45:48.285836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:36.983960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:39.209947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:41.460552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:44.007977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:45.964965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:48.653536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:37.339904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:39.524945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:41.938481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:44.406649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:46.368838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:49.067192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:37.617310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:39.801340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:42.418799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:44.758366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:46.670726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:49.562891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:37.948321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:40.183486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:42.783984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:45.027462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:46.938813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:49.855557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:38.262318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:40.631700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:43.256069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:45.336719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:47.406805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:50.371523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:38.823819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:41.048808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:43.618204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:45.651159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:45:47.836576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:46:02.239899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물재생센터명칭처리장구분계통구분BODTOC(2021년 1월 이전자료는 COD)SST-NTPCOCG
물재생센터명칭1.0000.5920.0860.1150.1150.2210.3310.1200.490
처리장구분0.5921.0000.3240.1460.1760.1510.1650.1440.398
계통구분0.0860.3241.0000.2690.6650.7360.6210.7790.750
BOD0.1150.1460.2691.0000.6470.6260.4080.8000.393
TOC(2021년 1월 이전자료는 COD)0.1150.1760.6650.6471.0000.7360.8200.9270.819
SS0.2210.1510.7360.6260.7361.0000.5960.8790.549
T-N0.3310.1650.6210.4080.8200.5961.0000.7080.634
TP0.1200.1440.7790.8000.9270.8790.7081.0000.592
COCG0.4900.3980.7500.3930.8190.5490.6340.5921.000
2024-05-10T23:46:02.644296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물재생센터명칭계통구분처리장구분
물재생센터명칭1.0000.0700.423
계통구분0.0701.0000.226
처리장구분0.4230.2261.000
2024-05-10T23:46:03.177845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BODTOC(2021년 1월 이전자료는 COD)SST-NTPCOCG물재생센터명칭처리장구분계통구분
BOD1.0000.8940.9020.8590.8720.7960.0740.0540.186
TOC(2021년 1월 이전자료는 COD)0.8941.0000.8700.8380.8520.7590.0740.0880.463
SS0.9020.8701.0000.8150.8560.7910.1330.0800.389
T-N0.8590.8380.8151.0000.8360.7010.1530.0920.444
TP0.8720.8520.8560.8361.0000.7410.0720.0760.435
COCG0.7960.7590.7910.7010.7411.0000.3140.2220.558
물재생센터명칭0.0740.0740.1330.1530.0720.3141.0000.4230.070
처리장구분0.0540.0880.0800.0920.0760.2220.4231.0000.226
계통구분0.1860.4630.3890.4440.4350.5580.0700.2261.000

Missing values

2024-05-10T23:45:50.922285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:45:51.703447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-10T23:45:52.188316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

측정일자물재생센터명칭처리장구분계통구분BODTOC(2021년 1월 이전자료는 COD)SST-NTPCOCG
809212019/03/07난지물재생센터제2처리장초침유출103.6743.6735.3339.2773.892<NA>
572392020/06/21탄천물재생센터제1처리장초침유출<NA><NA><NA><NA><NA><NA>
244862022/02/19중랑물재생센터제4처리장초침유출<NA><NA><NA><NA><NA><NA>
830552019/01/22중랑물재생센터제2처리장초침유출107.352.546.0<NA><NA><NA>
716572019/09/10서남물재생센터제1처리장초침유출123.160.2104.029.072.86<NA>
540172020/08/19서남물재생센터시설현대화초침유입<NA><NA><NA><NA><NA><NA>
799572019/03/26탄천물재생센터제1처리장2차8.111.85.317.310.288<NA>
641742020/02/06탄천물재생센터제1처리장방류8.612.04.515.230.114140
454602021/01/19중랑물재생센터제2처리장2차11.09.318.512.6190.54750
769592019/05/27난지물재생센터제2처리장2차2.476.533.6314.3580.179<NA>
측정일자물재생센터명칭처리장구분계통구분BODTOC(2021년 1월 이전자료는 COD)SST-NTPCOCG
154702022/08/08탄천물재생센터제2처리장방류4.28.04.011.8540.22432
528822020/09/08중랑물재생센터제1처리장방류0.43.42.411.0890.181
639582020/02/11난지물재생센터제2처리장2차1.77.22.813.4350.11<NA>
221142022/04/05중랑물재생센터제2처리장방류1.14.52.015.6250.17154
119202022/10/14탄천물재생센터제2처리장2차3.3<NA>6.211.2970.312<NA>
439472021/02/16탄천물재생센터제1처리장초침유입181.0<NA>105.049.3454.182<NA>
277602021/12/19탄천물재생센터제1처리장방류3.310.13.916.0170.197180
629822020/03/01서남물재생센터제1처리장초침유입<NA><NA><NA><NA><NA><NA>
19152023/07/28중랑물재생센터제1처리장초침유출73.6<NA>73.026.2221.523<NA>
606682020/04/15중랑물재생센터제3처리장방류7.87.24.213.640.1491270