Overview

Dataset statistics

Number of variables7
Number of observations720
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.7 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 지하수위 정보로 입니다.
Author제주특별자치도개발공사
URLhttps://www.data.go.kr/data/3067778/fileData.do

Alerts

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

Reproduction

Analysis started2024-05-11 10:32:53.977715
Analysis finished2024-05-11 10:33:05.316300
Duration11.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관측소명
Date

UNIQUE 

Distinct720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2024-04-01 00:00:00
Maximum2024-04-30 23:00:00
2024-05-11T10:33:05.543941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:06.080278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1수원 감시정1
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.55215
Minimum268.28
Maximum268.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:06.740070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum268.28
5-th percentile268.31
Q1268.37
median268.55
Q3268.72
95-th percentile268.86
Maximum268.94
Range0.66
Interquartile range (IQR)0.35

Descriptive statistics

Standard deviation0.18788392
Coefficient of variation (CV)0.00069961799
Kurtosis-1.3141124
Mean268.55215
Median Absolute Deviation (MAD)0.17
Skewness0.20144917
Sum193357.55
Variance0.035300366
MonotonicityNot monotonic
2024-05-11T10:33:07.419703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268.34 34
 
4.7%
268.33 34
 
4.7%
268.31 29
 
4.0%
268.4 23
 
3.2%
268.3 22
 
3.1%
268.71 22
 
3.1%
268.66 21
 
2.9%
268.72 20
 
2.8%
268.76 19
 
2.6%
268.75 18
 
2.5%
Other values (57) 478
66.4%
ValueCountFrequency (%)
268.28 3
 
0.4%
268.29 6
 
0.8%
268.3 22
3.1%
268.31 29
4.0%
268.32 17
2.4%
268.33 34
4.7%
268.34 34
4.7%
268.35 14
1.9%
268.36 14
1.9%
268.37 12
 
1.7%
ValueCountFrequency (%)
268.94 2
 
0.3%
268.93 5
0.7%
268.92 5
0.7%
268.91 4
0.6%
268.9 5
0.7%
268.89 4
0.6%
268.88 5
0.7%
268.87 4
0.6%
268.86 3
0.4%
268.85 4
0.6%

1수원 감시정2
Real number (ℝ)

Distinct163
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean282.7644
Minimum281.94
Maximum283.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:08.256716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum281.94
5-th percentile282.09
Q1282.24
median282.53
Q3283.4925
95-th percentile283.67
Maximum283.82
Range1.88
Interquartile range (IQR)1.2525

Descriptive statistics

Standard deviation0.58750829
Coefficient of variation (CV)0.0020777307
Kurtosis-1.4391269
Mean282.7644
Median Absolute Deviation (MAD)0.38
Skewness0.43304194
Sum203590.37
Variance0.34516598
MonotonicityNot monotonic
2024-05-11T10:33:09.096232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
283.59 22
 
3.1%
283.57 22
 
3.1%
282.24 17
 
2.4%
283.58 16
 
2.2%
282.35 15
 
2.1%
282.19 14
 
1.9%
282.12 14
 
1.9%
283.56 13
 
1.8%
283.55 12
 
1.7%
282.13 11
 
1.5%
Other values (153) 564
78.3%
ValueCountFrequency (%)
281.94 1
 
0.1%
281.95 2
 
0.3%
281.96 2
 
0.3%
281.97 1
 
0.1%
281.98 1
 
0.1%
281.99 1
 
0.1%
282.03 1
 
0.1%
282.04 1
 
0.1%
282.05 4
0.6%
282.06 7
1.0%
ValueCountFrequency (%)
283.82 1
 
0.1%
283.78 1
 
0.1%
283.76 1
 
0.1%
283.75 1
 
0.1%
283.73 1
 
0.1%
283.71 5
0.7%
283.7 8
1.1%
283.69 6
0.8%
283.68 6
0.8%
283.67 8
1.1%

1수원 감시정3
Real number (ℝ)

HIGH CORRELATION 

Distinct375
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266.57294
Minimum261.24
Maximum270.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:09.906509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum261.24
5-th percentile262.097
Q1264.77
median266.58
Q3267.3725
95-th percentile270.8
Maximum270.98
Range9.74
Interquartile range (IQR)2.6025

Descriptive statistics

Standard deviation2.6829584
Coefficient of variation (CV)0.010064631
Kurtosis-0.71574753
Mean266.57294
Median Absolute Deviation (MAD)1.5
Skewness0.1250613
Sum191932.52
Variance7.1982659
MonotonicityNot monotonic
2024-05-11T10:33:10.679505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
270.72 12
 
1.7%
270.76 8
 
1.1%
270.61 8
 
1.1%
266.62 6
 
0.8%
270.66 6
 
0.8%
267.07 6
 
0.8%
267.3 6
 
0.8%
270.85 5
 
0.7%
270.74 5
 
0.7%
266.36 5
 
0.7%
Other values (365) 653
90.7%
ValueCountFrequency (%)
261.24 1
0.1%
261.25 2
0.3%
261.26 1
0.1%
261.33 1
0.1%
261.34 1
0.1%
261.36 1
0.1%
261.38 1
0.1%
261.41 1
0.1%
261.42 1
0.1%
261.44 2
0.3%
ValueCountFrequency (%)
270.98 3
0.4%
270.94 1
 
0.1%
270.93 2
 
0.3%
270.92 1
 
0.1%
270.9 1
 
0.1%
270.89 2
 
0.3%
270.88 2
 
0.3%
270.87 2
 
0.3%
270.86 4
0.6%
270.85 5
0.7%

2수원 감시정1
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean325.79281
Minimum325.56
Maximum325.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:11.121574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325.56
5-th percentile325.65
Q1325.74
median325.8
Q3325.85
95-th percentile325.91
Maximum325.98
Range0.42
Interquartile range (IQR)0.11

Descriptive statistics

Standard deviation0.078773039
Coefficient of variation (CV)0.00024178876
Kurtosis-0.19048174
Mean325.79281
Median Absolute Deviation (MAD)0.06
Skewness-0.35128925
Sum234570.82
Variance0.0062051916
MonotonicityNot monotonic
2024-05-11T10:33:11.627782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
325.77 46
 
6.4%
325.87 41
 
5.7%
325.86 39
 
5.4%
325.85 37
 
5.1%
325.76 35
 
4.9%
325.84 34
 
4.7%
325.8 33
 
4.6%
325.79 32
 
4.4%
325.81 29
 
4.0%
325.74 28
 
3.9%
Other values (32) 366
50.8%
ValueCountFrequency (%)
325.56 1
 
0.1%
325.57 2
 
0.3%
325.58 5
0.7%
325.59 3
 
0.4%
325.6 1
 
0.1%
325.61 2
 
0.3%
325.62 5
0.7%
325.63 2
 
0.3%
325.64 8
1.1%
325.65 12
1.7%
ValueCountFrequency (%)
325.98 2
 
0.3%
325.96 4
 
0.6%
325.95 4
 
0.6%
325.94 6
 
0.8%
325.93 7
 
1.0%
325.92 4
 
0.6%
325.91 14
1.9%
325.9 13
1.8%
325.89 21
2.9%
325.88 24
3.3%

2수원 감시정2
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean332.07531
Minimum324.48
Maximum334.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:12.183416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum324.48
5-th percentile324.63
Q1333.48
median333.76
Q3333.8925
95-th percentile334.01
Maximum334.02
Range9.54
Interquartile range (IQR)0.4125

Descriptive statistics

Standard deviation3.4981371
Coefficient of variation (CV)0.010534168
Kurtosis0.59332331
Mean332.07531
Median Absolute Deviation (MAD)0.23
Skewness-1.5934235
Sum239094.22
Variance12.236963
MonotonicityNot monotonic
2024-05-11T10:33:12.742885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
334.01 43
 
6.0%
333.48 38
 
5.3%
333.99 36
 
5.0%
333.79 33
 
4.6%
334.0 32
 
4.4%
333.8 27
 
3.8%
333.78 27
 
3.8%
334.02 22
 
3.1%
333.81 21
 
2.9%
333.49 18
 
2.5%
Other values (105) 423
58.8%
ValueCountFrequency (%)
324.48 1
 
0.1%
324.49 2
0.3%
324.5 3
0.4%
324.51 2
0.3%
324.52 3
0.4%
324.53 2
0.3%
324.54 2
0.3%
324.55 3
0.4%
324.56 2
0.3%
324.57 3
0.4%
ValueCountFrequency (%)
334.02 22
3.1%
334.01 43
6.0%
334.0 32
4.4%
333.99 36
5.0%
333.98 11
 
1.5%
333.97 9
 
1.2%
333.96 3
 
0.4%
333.95 5
 
0.7%
333.94 4
 
0.6%
333.93 3
 
0.4%

2수원 감시정3
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean321.91203
Minimum321.7
Maximum322.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-05-11T10:33:13.368628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum321.7
5-th percentile321.72
Q1321.8
median321.9
Q3322.04
95-th percentile322.13
Maximum322.18
Range0.48
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.13517227
Coefficient of variation (CV)0.00041990438
Kurtosis-1.299415
Mean321.91203
Median Absolute Deviation (MAD)0.13
Skewness0.17933896
Sum231776.66
Variance0.018271543
MonotonicityNot monotonic
2024-05-11T10:33:14.034411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
321.81 39
 
5.4%
321.75 38
 
5.3%
322.05 37
 
5.1%
322.11 35
 
4.9%
322.03 34
 
4.7%
321.82 32
 
4.4%
321.98 27
 
3.8%
321.74 27
 
3.8%
321.92 24
 
3.3%
322.04 24
 
3.3%
Other values (38) 403
56.0%
ValueCountFrequency (%)
321.7 2
 
0.3%
321.71 21
2.9%
321.72 14
 
1.9%
321.73 15
 
2.1%
321.74 27
3.8%
321.75 38
5.3%
321.76 18
2.5%
321.77 16
2.2%
321.78 13
 
1.8%
321.79 14
 
1.9%
ValueCountFrequency (%)
322.18 2
 
0.3%
322.17 3
 
0.4%
322.16 4
 
0.6%
322.15 8
 
1.1%
322.14 10
 
1.4%
322.13 10
 
1.4%
322.12 16
2.2%
322.11 35
4.9%
322.1 3
 
0.4%
322.09 3
 
0.4%

Interactions

2024-05-11T10:33:02.948370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:54.551674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:56.431785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:58.233728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:59.840058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:01.463502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:03.216756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:54.909339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:56.731373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:58.520795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:00.125520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:01.739446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:03.598027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:55.262134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:57.020398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:58.805638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:00.418151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:01.974201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:03.869690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:55.525306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:57.352664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:59.060879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:00.677137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:02.165564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:04.237137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:55.866597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:57.626507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:59.324067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:00.934055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:02.432985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:04.453922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:56.139992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:57.906857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:32:59.575464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:01.192336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:33:02.683074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:33:14.450649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
1수원 감시정11.0000.7100.7690.7510.6410.901
1수원 감시정20.7101.0000.6290.6340.6280.758
1수원 감시정30.7690.6291.0000.6990.5860.856
2수원 감시정10.7510.6340.6991.0000.6150.712
2수원 감시정20.6410.6280.5860.6151.0000.653
2수원 감시정30.9010.7580.8560.7120.6531.000
2024-05-11T10:33:14.816000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
1수원 감시정11.000-0.2080.9130.730-0.1100.600
1수원 감시정2-0.2081.000-0.267-0.250-0.071-0.226
1수원 감시정30.913-0.2671.0000.799-0.2100.480
2수원 감시정10.730-0.2500.7991.000-0.2050.399
2수원 감시정2-0.110-0.071-0.210-0.2051.0000.565
2수원 감시정30.600-0.2260.4800.3990.5651.000

Missing values

2024-05-11T10:33:04.788036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:33:05.167393image/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

관측소명1수원 감시정11수원 감시정21수원 감시정32수원 감시정12수원 감시정22수원 감시정3
02024-04-01 00:00268.34283.76261.24325.74333.42321.74
12024-04-01 01:00268.35283.78261.26325.76333.42321.76
22024-04-01 02:00268.33282.83261.25325.77333.42321.75
32024-04-01 03:00268.32282.58261.25325.68333.42321.77
42024-04-01 04:00268.34283.71261.33325.73333.42321.75
52024-04-01 05:00268.34283.75261.36325.75333.43321.78
62024-04-01 06:00268.33283.28261.38325.77333.42321.76
72024-04-01 07:00268.31282.57261.34325.71333.43321.77
82024-04-01 08:00268.33283.47261.44325.76333.42321.74
92024-04-01 09:00268.3282.34261.41325.78333.43321.74
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