Overview

Dataset statistics

Number of variables10
Number of observations180
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory15.2 KiB
Average record size in memory86.7 B

Variable types

DateTime1
Categorical5
Numeric4

Alerts

Dataset has 1 (0.6%) duplicate rowsDuplicates
습지구분명 is highly overall correlated with 소재지위치 and 2 other fieldsHigh correlation
소재지면적(㎡) is highly overall correlated with 습지구분명 and 2 other fieldsHigh correlation
습지면적(㎡) is highly overall correlated with 습지구분명 and 2 other fieldsHigh correlation
소재지위치 is highly overall correlated with 습지구분명 and 2 other fieldsHigh correlation
유입수BOD측정값(㎎/ℓ) is highly overall correlated with 방류수BOD측정값(㎎/ℓ)High correlation
방류수BOD측정값(㎎/ℓ) is highly overall correlated with 유입수BOD측정값(㎎/ℓ)High correlation
유입수T-P측정값(㎎/ℓ) is highly overall correlated with 방류수T-P측정값(㎎/ℓ)High correlation
방류수T-P측정값(㎎/ℓ) is highly overall correlated with 유입수T-P측정값(㎎/ℓ)High correlation
유입수T-P측정값(㎎/ℓ) has 11 (6.1%) zerosZeros
방류수T-P측정값(㎎/ℓ) has 11 (6.1%) zerosZeros

Reproduction

Analysis started2023-12-10 21:24:19.931959
Analysis finished2023-12-10 21:24:21.798835
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일자
Date

Distinct30
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2016-04-06 00:00:00
Maximum2023-02-16 00:00:00
2023-12-11T06:24:21.847059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.935850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

습지구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
청정습지
120 
희망습지
60 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청정습지
2nd row청정습지
3rd row청정습지
4th row청정습지
5th row희망습지

Common Values

ValueCountFrequency (%)
청정습지 120
66.7%
희망습지 60
33.3%

Length

2023-12-11T06:24:22.023925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:22.101662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청정습지 120
66.7%
희망습지 60
33.3%

소재지위치
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
퇴촌면 광동리 광동하수처리장 인근
120 
초월읍 지월리 광주하수처리장 인근
60 

Length

Max length18
Median length18
Mean length18
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row퇴촌면 광동리 광동하수처리장 인근
2nd row퇴촌면 광동리 광동하수처리장 인근
3rd row퇴촌면 광동리 광동하수처리장 인근
4th row퇴촌면 광동리 광동하수처리장 인근
5th row초월읍 지월리 광주하수처리장 인근

Common Values

ValueCountFrequency (%)
퇴촌면 광동리 광동하수처리장 인근 120
66.7%
초월읍 지월리 광주하수처리장 인근 60
33.3%

Length

2023-12-11T06:24:22.203894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:22.296942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인근 180
25.0%
퇴촌면 120
16.7%
광동리 120
16.7%
광동하수처리장 120
16.7%
초월읍 60
 
8.3%
지월리 60
 
8.3%
광주하수처리장 60
 
8.3%

소재지면적(㎡)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
44419
120 
26584
60 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44419
2nd row44419
3rd row44419
4th row44419
5th row26584

Common Values

ValueCountFrequency (%)
44419 120
66.7%
26584 60
33.3%

Length

2023-12-11T06:24:22.379463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:22.457217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44419 120
66.7%
26584 60
33.3%

습지면적(㎡)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
25090
120 
15869
60 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row25090
2nd row25090
3rd row25090
4th row25090
5th row15869

Common Values

ValueCountFrequency (%)
25090 120
66.7%
15869 60
33.3%

Length

2023-12-11T06:24:22.537768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:22.612378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
25090 120
66.7%
15869 60
33.3%

지역구분명
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
A
60 
B
60 
C
30 
D
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowB
3rd rowC
4th rowD
5th rowA

Common Values

ValueCountFrequency (%)
A 60
33.3%
B 60
33.3%
C 30
16.7%
D 30
16.7%

Length

2023-12-11T06:24:22.690148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:22.773834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 60
33.3%
b 60
33.3%
c 30
16.7%
d 30
16.7%

유입수BOD측정값(㎎/ℓ)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4166667
Minimum0
Maximum12.5
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T06:24:22.889916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q10.7
median1
Q31.6
95-th percentile3.02
Maximum12.5
Range12.5
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation1.6111865
Coefficient of variation (CV)1.1373081
Kurtosis25.491557
Mean1.4166667
Median Absolute Deviation (MAD)0.4
Skewness4.5310476
Sum255
Variance2.5959218
MonotonicityNot monotonic
2023-12-11T06:24:23.197665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.9 17
 
9.4%
0.7 14
 
7.8%
0.6 12
 
6.7%
0.5 12
 
6.7%
0.8 10
 
5.6%
1.4 10
 
5.6%
1.5 9
 
5.0%
1.0 9
 
5.0%
1.2 8
 
4.4%
0.4 8
 
4.4%
Other values (28) 71
39.4%
ValueCountFrequency (%)
0.0 1
 
0.6%
0.1 3
 
1.7%
0.2 3
 
1.7%
0.3 5
 
2.8%
0.4 8
4.4%
0.5 12
6.7%
0.6 12
6.7%
0.7 14
7.8%
0.8 10
5.6%
0.9 17
9.4%
ValueCountFrequency (%)
12.5 1
0.6%
12.2 1
0.6%
8.5 1
0.6%
7.4 1
0.6%
6.0 1
0.6%
5.4 1
0.6%
4.1 1
0.6%
3.9 1
0.6%
3.4 1
0.6%
3.0 1
0.6%

방류수BOD측정값(㎎/ℓ)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1894444
Minimum0
Maximum16.4
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T06:24:23.288388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q10.6
median0.9
Q31.3
95-th percentile2.51
Maximum16.4
Range16.4
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation1.6229326
Coefficient of variation (CV)1.3644459
Kurtosis59.836965
Mean1.1894444
Median Absolute Deviation (MAD)0.3
Skewness7.1589457
Sum214.1
Variance2.6339103
MonotonicityNot monotonic
2023-12-11T06:24:23.384995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.8 19
10.6%
0.6 18
 
10.0%
0.9 17
 
9.4%
1.3 16
 
8.9%
0.7 15
 
8.3%
0.5 13
 
7.2%
1.2 10
 
5.6%
0.4 9
 
5.0%
1.4 8
 
4.4%
1.0 8
 
4.4%
Other values (20) 47
26.1%
ValueCountFrequency (%)
0.0 1
 
0.6%
0.1 4
 
2.2%
0.2 2
 
1.1%
0.3 4
 
2.2%
0.4 9
5.0%
0.5 13
7.2%
0.6 18
10.0%
0.7 15
8.3%
0.8 19
10.6%
0.9 17
9.4%
ValueCountFrequency (%)
16.4 1
0.6%
13.3 1
0.6%
5.0 1
0.6%
4.6 1
0.6%
3.7 2
1.1%
3.1 1
0.6%
2.9 1
0.6%
2.7 1
0.6%
2.5 1
0.6%
2.3 2
1.1%

유입수T-P측정값(㎎/ℓ)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.028177778
Minimum0
Maximum0.577
Zeros11
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T06:24:23.496419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.012
median0.023
Q30.034
95-th percentile0.05805
Maximum0.577
Range0.577
Interquartile range (IQR)0.022

Descriptive statistics

Standard deviation0.04492006
Coefficient of variation (CV)1.5941662
Kurtosis125.85023
Mean0.028177778
Median Absolute Deviation (MAD)0.011
Skewness10.366647
Sum5.072
Variance0.0020178118
MonotonicityNot monotonic
2023-12-11T06:24:23.620742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 11
 
6.1%
0.024 9
 
5.0%
0.029 8
 
4.4%
0.011 7
 
3.9%
0.02 7
 
3.9%
0.016 7
 
3.9%
0.019 6
 
3.3%
0.014 6
 
3.3%
0.01 5
 
2.8%
0.033 5
 
2.8%
Other values (49) 109
60.6%
ValueCountFrequency (%)
0.0 11
6.1%
0.003 1
 
0.6%
0.004 2
 
1.1%
0.005 4
 
2.2%
0.006 3
 
1.7%
0.007 3
 
1.7%
0.008 3
 
1.7%
0.009 2
 
1.1%
0.01 5
2.8%
0.011 7
3.9%
ValueCountFrequency (%)
0.577 1
0.6%
0.121 1
0.6%
0.092 1
0.6%
0.073 1
0.6%
0.07 1
0.6%
0.068 1
0.6%
0.064 1
0.6%
0.06 1
0.6%
0.059 1
0.6%
0.058 1
0.6%

방류수T-P측정값(㎎/ℓ)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.021944444
Minimum0
Maximum0.44
Zeros11
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T06:24:23.749005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.009
median0.017
Q30.027
95-th percentile0.04615
Maximum0.44
Range0.44
Interquartile range (IQR)0.018

Descriptive statistics

Standard deviation0.034128204
Coefficient of variation (CV)1.5552093
Kurtosis127.10311
Mean0.021944444
Median Absolute Deviation (MAD)0.009
Skewness10.405125
Sum3.95
Variance0.0011647343
MonotonicityNot monotonic
2023-12-11T06:24:23.880785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 11
 
6.1%
0.009 9
 
5.0%
0.007 8
 
4.4%
0.012 8
 
4.4%
0.015 7
 
3.9%
0.02 7
 
3.9%
0.011 7
 
3.9%
0.017 7
 
3.9%
0.026 7
 
3.9%
0.013 6
 
3.3%
Other values (38) 103
57.2%
ValueCountFrequency (%)
0.0 11
6.1%
0.001 1
 
0.6%
0.003 6
3.3%
0.004 2
 
1.1%
0.005 3
 
1.7%
0.006 2
 
1.1%
0.007 8
4.4%
0.008 4
 
2.2%
0.009 9
5.0%
0.01 3
 
1.7%
ValueCountFrequency (%)
0.44 1
0.6%
0.063 1
0.6%
0.061 1
0.6%
0.058 2
1.1%
0.056 1
0.6%
0.051 1
0.6%
0.05 1
0.6%
0.049 1
0.6%
0.046 1
0.6%
0.045 2
1.1%

Interactions

2023-12-11T06:24:21.288495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.323034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.665674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.980834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.365843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.407337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.741264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.060038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.461763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.502506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.817818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.137002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.549688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.596791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:20.903254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:21.216835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:24:23.969981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일자습지구분명소재지위치소재지면적(㎡)습지면적(㎡)지역구분명유입수BOD측정값(㎎/ℓ)방류수BOD측정값(㎎/ℓ)유입수T-P측정값(㎎/ℓ)방류수T-P측정값(㎎/ℓ)
측정일자1.0000.0000.0000.0000.0000.0000.5440.3370.4330.410
습지구분명0.0001.0001.0001.0001.0000.6890.2150.0850.0000.041
소재지위치0.0001.0001.0001.0001.0000.6890.2150.0850.0000.041
소재지면적(㎡)0.0001.0001.0001.0001.0000.6890.2150.0850.0000.041
습지면적(㎡)0.0001.0001.0001.0001.0000.6890.2150.0850.0000.041
지역구분명0.0000.6890.6890.6890.6891.0000.1560.0000.0580.121
유입수BOD측정값(㎎/ℓ)0.5440.2150.2150.2150.2150.1561.0000.8330.2510.000
방류수BOD측정값(㎎/ℓ)0.3370.0850.0850.0850.0850.0000.8331.0000.0000.000
유입수T-P측정값(㎎/ℓ)0.4330.0000.0000.0000.0000.0580.2510.0001.0000.764
방류수T-P측정값(㎎/ℓ)0.4100.0410.0410.0410.0410.1210.0000.0000.7641.000
2023-12-11T06:24:24.075274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
습지구분명지역구분명소재지면적(㎡)습지면적(㎡)소재지위치
습지구분명1.0000.4840.9870.9870.987
지역구분명0.4841.0000.4840.4840.484
소재지면적(㎡)0.9870.4841.0000.9870.987
습지면적(㎡)0.9870.4840.9871.0000.987
소재지위치0.9870.4840.9870.9871.000
2023-12-11T06:24:24.155743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입수BOD측정값(㎎/ℓ)방류수BOD측정값(㎎/ℓ)유입수T-P측정값(㎎/ℓ)방류수T-P측정값(㎎/ℓ)습지구분명소재지위치소재지면적(㎡)습지면적(㎡)지역구분명
유입수BOD측정값(㎎/ℓ)1.0000.5680.4480.2510.1890.1890.1890.1890.058
방류수BOD측정값(㎎/ℓ)0.5681.0000.3400.3080.0590.0590.0590.0590.000
유입수T-P측정값(㎎/ℓ)0.4480.3401.0000.7760.0000.0000.0000.0000.021
방류수T-P측정값(㎎/ℓ)0.2510.3080.7761.0000.0680.0680.0680.0680.113
습지구분명0.1890.0590.0000.0681.0000.9870.9870.9870.484
소재지위치0.1890.0590.0000.0680.9871.0000.9870.9870.484
소재지면적(㎡)0.1890.0590.0000.0680.9870.9871.0000.9870.484
습지면적(㎡)0.1890.0590.0000.0680.9870.9870.9871.0000.484
지역구분명0.0580.0000.0210.1130.4840.4840.4840.4841.000

Missing values

2023-12-11T06:24:21.642581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:24:21.753110image/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

측정일자습지구분명소재지위치소재지면적(㎡)습지면적(㎡)지역구분명유입수BOD측정값(㎎/ℓ)방류수BOD측정값(㎎/ℓ)유입수T-P측정값(㎎/ℓ)방류수T-P측정값(㎎/ℓ)
02016-04-06청정습지퇴촌면 광동리 광동하수처리장 인근4441925090A2.22.30.0590.046
12016-04-06청정습지퇴촌면 광동리 광동하수처리장 인근4441925090B1.51.30.0240.022
22016-04-06청정습지퇴촌면 광동리 광동하수처리장 인근4441925090C0.91.30.0410.01
32016-04-06청정습지퇴촌면 광동리 광동하수처리장 인근4441925090D1.91.70.0260.03
42016-04-06희망습지초월읍 지월리 광주하수처리장 인근2658415869A0.91.00.0290.029
52016-04-06희망습지초월읍 지월리 광주하수처리장 인근2658415869B1.01.00.030.029
62016-05-13청정습지퇴촌면 광동리 광동하수처리장 인근4441925090A2.11.50.0920.061
72016-05-13청정습지퇴촌면 광동리 광동하수처리장 인근4441925090B0.60.80.0420.039
82016-05-13청정습지퇴촌면 광동리 광동하수처리장 인근4441925090C1.00.40.060.02
92016-05-13청정습지퇴촌면 광동리 광동하수처리장 인근4441925090D0.80.90.0390.039
측정일자습지구분명소재지위치소재지면적(㎡)습지면적(㎡)지역구분명유입수BOD측정값(㎎/ℓ)방류수BOD측정값(㎎/ℓ)유입수T-P측정값(㎎/ℓ)방류수T-P측정값(㎎/ℓ)
1702022-05-20청정습지퇴촌면 광동리 광동하수처리장 인근4441925090C1.10.70.0110.0
1712022-05-20청정습지퇴촌면 광동리 광동하수처리장 인근4441925090D1.51.20.0220.024
1722022-05-20희망습지초월읍 지월리 광주하수처리장 인근2658415869A1.71.50.0430.033
1732022-05-20희망습지초월읍 지월리 광주하수처리장 인근2658415869B1.51.60.040.039
1742023-02-16청정습지퇴촌면 광동리 광동하수처리장 인근4441925090A1.24.60.030.009
1752023-02-16청정습지퇴촌면 광동리 광동하수처리장 인근4441925090B0.91.30.0140.013
1762023-02-16청정습지퇴촌면 광동리 광동하수처리장 인근4441925090C0.20.80.00.005
1772023-02-16청정습지퇴촌면 광동리 광동하수처리장 인근4441925090D1.21.00.0120.013
1782023-02-16희망습지초월읍 지월리 광주하수처리장 인근2658415869A2.31.10.0430.033
1792023-02-16희망습지초월읍 지월리 광주하수처리장 인근2658415869B2.01.30.020.018

Duplicate rows

Most frequently occurring

측정일자습지구분명소재지위치소재지면적(㎡)습지면적(㎡)지역구분명유입수BOD측정값(㎎/ℓ)방류수BOD측정값(㎎/ℓ)유입수T-P측정값(㎎/ℓ)방류수T-P측정값(㎎/ℓ)# duplicates
02021-09-27청정습지퇴촌면 광동리 광동하수처리장 인근4441925090A1.40.60.0290.0152