Overview

Dataset statistics

Number of variables7
Number of observations744
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.2 KiB
Average record size in memory62.2 B

Variable types

DateTime1
Numeric6

Dataset

Description제주특별자치도개발공사가 운영하는 제주삼다수 제1,2취수원의 감시정 6개를 통해 관리 및 수집하는 제주지역 수소 이온 농도 정보로 입니다.
Author제주특별자치도개발공사
URLhttps://www.data.go.kr/data/15103550/fileData.do

Alerts

1수원 감시정1 is highly overall correlated with 1수원 감시정3High correlation
1수원 감시정2 is highly overall correlated with 1수원 감시정3 and 1 other fieldsHigh correlation
1수원 감시정3 is highly overall correlated with 1수원 감시정1 and 1 other fieldsHigh correlation
2수원 감시정1 is highly overall correlated with 1수원 감시정2High correlation
일시 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:11:50.689401
Analysis finished2024-04-21 02:11:56.795045
Duration6.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일시
Date

UNIQUE 

Distinct744
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2024-03-01 00:00:00
Maximum2024-03-31 23:00:00
2024-04-21T11:11:56.865403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:56.998396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1수원 감시정1
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4337231
Minimum7.15
Maximum7.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:57.122814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.15
5-th percentile7.2215
Q17.4275
median7.47
Q37.48
95-th percentile7.51
Maximum7.53
Range0.38
Interquartile range (IQR)0.0525

Descriptive statistics

Standard deviation0.083574154
Coefficient of variation (CV)0.01124257
Kurtosis2.4855963
Mean7.4337231
Median Absolute Deviation (MAD)0.01
Skewness-1.8240822
Sum5530.69
Variance0.0069846392
MonotonicityNot monotonic
2024-04-21T11:11:57.259405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7.47 190
25.5%
7.46 114
15.3%
7.48 82
11.0%
7.49 54
 
7.3%
7.5 43
 
5.8%
7.51 30
 
4.0%
7.45 16
 
2.2%
7.36 12
 
1.6%
7.35 10
 
1.3%
7.41 10
 
1.3%
Other values (29) 183
24.6%
ValueCountFrequency (%)
7.15 5
0.7%
7.16 5
0.7%
7.17 4
0.5%
7.18 5
0.7%
7.19 5
0.7%
7.2 5
0.7%
7.21 5
0.7%
7.22 4
0.5%
7.23 5
0.7%
7.24 5
0.7%
ValueCountFrequency (%)
7.53 2
 
0.3%
7.52 8
 
1.1%
7.51 30
 
4.0%
7.5 43
 
5.8%
7.49 54
 
7.3%
7.48 82
11.0%
7.47 190
25.5%
7.46 114
15.3%
7.45 16
 
2.2%
7.44 9
 
1.2%

1수원 감시정2
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6605376
Minimum7.27
Maximum7.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:57.431025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.27
5-th percentile7.35
Q17.67
median7.7
Q37.74
95-th percentile7.78
Maximum7.81
Range0.54
Interquartile range (IQR)0.07

Descriptive statistics

Standard deviation0.12714901
Coefficient of variation (CV)0.016597922
Kurtosis1.5235491
Mean7.6605376
Median Absolute Deviation (MAD)0.035
Skewness-1.587336
Sum5699.44
Variance0.016166871
MonotonicityNot monotonic
2024-04-21T11:11:57.597392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.68 87
 
11.7%
7.69 78
 
10.5%
7.73 64
 
8.6%
7.72 52
 
7.0%
7.7 42
 
5.6%
7.74 41
 
5.5%
7.71 38
 
5.1%
7.77 36
 
4.8%
7.76 32
 
4.3%
7.78 31
 
4.2%
Other values (45) 243
32.7%
ValueCountFrequency (%)
7.27 3
0.4%
7.28 5
0.7%
7.29 4
0.5%
7.3 5
0.7%
7.31 4
0.5%
7.32 5
0.7%
7.33 4
0.5%
7.34 5
0.7%
7.35 4
0.5%
7.36 5
0.7%
ValueCountFrequency (%)
7.81 3
 
0.4%
7.8 10
 
1.3%
7.79 10
 
1.3%
7.78 31
4.2%
7.77 36
4.8%
7.76 32
4.3%
7.75 29
3.9%
7.74 41
5.5%
7.73 64
8.6%
7.72 52
7.0%

1수원 감시정3
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6166129
Minimum7.52
Maximum7.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:57.715491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.52
5-th percentile7.55
Q17.61
median7.63
Q37.63
95-th percentile7.65
Maximum7.67
Range0.15
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.030409155
Coefficient of variation (CV)0.0039924774
Kurtosis0.91330374
Mean7.6166129
Median Absolute Deviation (MAD)0.01
Skewness-1.1827883
Sum5666.76
Variance0.00092471671
MonotonicityNot monotonic
2024-04-21T11:11:57.816534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
7.63 191
25.7%
7.62 136
18.3%
7.64 101
13.6%
7.61 58
 
7.8%
7.65 54
 
7.3%
7.57 34
 
4.6%
7.6 30
 
4.0%
7.59 29
 
3.9%
7.55 25
 
3.4%
7.66 25
 
3.4%
Other values (6) 61
 
8.2%
ValueCountFrequency (%)
7.52 5
 
0.7%
7.53 8
 
1.1%
7.54 15
 
2.0%
7.55 25
3.4%
7.56 14
 
1.9%
7.57 34
4.6%
7.58 14
 
1.9%
7.59 29
3.9%
7.6 30
4.0%
7.61 58
7.8%
ValueCountFrequency (%)
7.67 5
 
0.7%
7.66 25
 
3.4%
7.65 54
 
7.3%
7.64 101
13.6%
7.63 191
25.7%
7.62 136
18.3%
7.61 58
 
7.8%
7.6 30
 
4.0%
7.59 29
 
3.9%
7.58 14
 
1.9%

2수원 감시정1
Real number (ℝ)

HIGH CORRELATION 

Distinct114
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.040336
Minimum7.19
Maximum8.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:57.963504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.19
5-th percentile7.43
Q17.7
median8.21
Q38.36
95-th percentile8.39
Maximum8.67
Range1.48
Interquartile range (IQR)0.66

Descriptive statistics

Standard deviation0.35346395
Coefficient of variation (CV)0.043961341
Kurtosis-1.2212751
Mean8.040336
Median Absolute Deviation (MAD)0.17
Skewness-0.56425402
Sum5982.01
Variance0.12493676
MonotonicityNot monotonic
2024-04-21T11:11:58.101892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.38 57
 
7.7%
8.37 53
 
7.1%
8.39 50
 
6.7%
8.36 34
 
4.6%
8.35 30
 
4.0%
8.34 19
 
2.6%
8.3 13
 
1.7%
8.4 13
 
1.7%
8.33 13
 
1.7%
8.32 12
 
1.6%
Other values (104) 450
60.5%
ValueCountFrequency (%)
7.19 1
 
0.1%
7.24 1
 
0.1%
7.28 1
 
0.1%
7.29 1
 
0.1%
7.31 2
0.3%
7.32 1
 
0.1%
7.33 4
0.5%
7.34 4
0.5%
7.35 4
0.5%
7.36 3
0.4%
ValueCountFrequency (%)
8.67 1
 
0.1%
8.4 13
 
1.7%
8.39 50
6.7%
8.38 57
7.7%
8.37 53
7.1%
8.36 34
4.6%
8.35 30
4.0%
8.34 19
 
2.6%
8.33 13
 
1.7%
8.32 12
 
1.6%

2수원 감시정2
Real number (ℝ)

Distinct26
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3424731
Minimum8.19
Maximum8.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:58.232704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.19
5-th percentile8.23
Q18.2975
median8.35
Q38.4
95-th percentile8.42
Maximum8.44
Range0.25
Interquartile range (IQR)0.1025

Descriptive statistics

Standard deviation0.06093539
Coefficient of variation (CV)0.0073042357
Kurtosis-0.95466101
Mean8.3424731
Median Absolute Deviation (MAD)0.05
Skewness-0.39457398
Sum6206.8
Variance0.0037131218
MonotonicityNot monotonic
2024-04-21T11:11:58.348742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
8.41 76
 
10.2%
8.42 56
 
7.5%
8.4 54
 
7.3%
8.29 43
 
5.8%
8.38 39
 
5.2%
8.39 39
 
5.2%
8.34 39
 
5.2%
8.36 37
 
5.0%
8.31 36
 
4.8%
8.32 35
 
4.7%
Other values (16) 290
39.0%
ValueCountFrequency (%)
8.19 1
 
0.1%
8.2 2
 
0.3%
8.21 3
 
0.4%
8.22 15
2.0%
8.23 24
3.2%
8.24 16
2.2%
8.25 24
3.2%
8.26 19
2.6%
8.27 16
2.2%
8.28 23
3.1%
ValueCountFrequency (%)
8.44 2
 
0.3%
8.43 18
 
2.4%
8.42 56
7.5%
8.41 76
10.2%
8.4 54
7.3%
8.39 39
5.2%
8.38 39
5.2%
8.37 32
4.3%
8.36 37
5.0%
8.35 34
4.6%

2수원 감시정3
Real number (ℝ)

Distinct31
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8236962
Minimum7.69
Maximum7.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:11:58.467488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.69
5-th percentile7.73
Q17.78
median7.82
Q37.86
95-th percentile7.93
Maximum7.99
Range0.3
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.059127066
Coefficient of variation (CV)0.0075574337
Kurtosis-0.15303909
Mean7.8236962
Median Absolute Deviation (MAD)0.04
Skewness0.36186896
Sum5820.83
Variance0.0034960099
MonotonicityNot monotonic
2024-04-21T11:11:58.600845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7.81 59
 
7.9%
7.8 57
 
7.7%
7.84 52
 
7.0%
7.82 50
 
6.7%
7.79 48
 
6.5%
7.83 47
 
6.3%
7.78 45
 
6.0%
7.85 39
 
5.2%
7.77 33
 
4.4%
7.91 30
 
4.0%
Other values (21) 284
38.2%
ValueCountFrequency (%)
7.69 1
 
0.1%
7.7 6
 
0.8%
7.71 9
 
1.2%
7.72 10
 
1.3%
7.73 20
2.7%
7.74 17
 
2.3%
7.75 25
3.4%
7.76 27
3.6%
7.77 33
4.4%
7.78 45
6.0%
ValueCountFrequency (%)
7.99 2
 
0.3%
7.98 4
 
0.5%
7.97 7
 
0.9%
7.96 6
 
0.8%
7.95 5
 
0.7%
7.94 9
 
1.2%
7.93 8
 
1.1%
7.92 13
1.7%
7.91 30
4.0%
7.9 16
2.2%

Interactions

2024-04-21T11:11:55.782700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.305898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.089233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.700086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.371930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.079876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.902873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.465444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.201555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.850816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.489044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.248228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.993170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.684541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.290408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.949261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.584165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.346996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:56.100426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.786752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.384451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.051417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.684567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.447183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:56.203928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.897688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.488958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.147782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.789333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.567937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:56.316142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:52.992265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:53.597253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.243444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:54.896780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:55.675027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:11:58.707871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
1수원 감시정11.0000.9530.8270.6370.4500.562
1수원 감시정20.9531.0000.8720.7840.4360.681
1수원 감시정30.8270.8721.0000.5690.3500.451
2수원 감시정10.6370.7840.5691.0000.3400.320
2수원 감시정20.4500.4360.3500.3401.0000.168
2수원 감시정30.5620.6810.4510.3200.1681.000
2024-04-21T11:11:58.822312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
1수원 감시정11.0000.4670.580-0.1080.206-0.039
1수원 감시정20.4671.0000.683-0.6390.1330.044
1수원 감시정30.5800.6831.000-0.3050.251-0.073
2수원 감시정1-0.108-0.639-0.3051.0000.055-0.221
2수원 감시정20.2060.1330.2510.0551.000-0.053
2수원 감시정3-0.0390.044-0.073-0.221-0.0531.000

Missing values

2024-04-21T11:11:56.636208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:11:56.743071image/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

일시1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
02024-03-01 00:007.157.277.558.198.257.8
12024-03-01 01:007.157.277.68.198.267.77
22024-03-01 02:007.157.277.68.28.277.8
32024-03-01 03:007.157.287.598.28.287.77
42024-03-01 04:007.157.287.568.218.297.78
52024-03-01 05:007.167.287.578.218.37.79
62024-03-01 06:007.167.287.578.228.317.82
72024-03-01 07:007.167.287.578.228.327.8
82024-03-01 08:007.167.297.578.238.337.77
92024-03-01 09:007.167.297.578.28.317.8
일시1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
7342024-03-31 14:007.357.787.617.558.317.9
7352024-03-31 15:007.347.787.627.578.417.86
7362024-03-31 16:007.357.787.667.58.397.88
7372024-03-31 17:007.337.87.637.388.377.85
7382024-03-31 18:007.347.797.627.598.387.89
7392024-03-31 19:007.347.797.627.678.357.83
7402024-03-31 20:007.337.797.617.688.357.88
7412024-03-31 21:007.337.87.627.678.347.87
7422024-03-31 22:007.357.87.657.78.427.93
7432024-03-31 23:007.347.87.637.438.367.85