Overview

Dataset statistics

Number of variables12
Number of observations8746
Missing cells74
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory922.6 KiB
Average record size in memory108.0 B

Variable types

Numeric12

Dataset

Description한국농어촌공사 새만금방조제 새만금유역 동진대교 수위계측 데이타로 매일/매시 10분 주기로 수위정보를 제공합니다 일자별 데이타중 공란인 것은 수위계 이상으로 결측된 자료입니다
Author한국농어촌공사
URLhttps://www.data.go.kr/data/15104776/fileData.do

Alerts

00분 is highly overall correlated with 10분 and 7 other fieldsHigh correlation
10분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
20분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
30분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
40분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
50분 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간최소 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간최대 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간평균 is highly overall correlated with 00분 and 7 other fieldsHigh correlation
시간 has 364 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-11 23:45:37.683184
Analysis finished2023-12-11 23:45:57.185057
Duration19.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables


Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5188658
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:57.250950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4461534
Coefficient of variation (CV)0.5286431
Kurtosis-1.2048701
Mean6.5188658
Median Absolute Deviation (MAD)3
Skewness-0.0077601736
Sum57014
Variance11.875973
MonotonicityIncreasing
2023-12-12T08:45:57.382053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 744
8.5%
3 744
8.5%
5 744
8.5%
7 744
8.5%
8 744
8.5%
10 744
8.5%
12 744
8.5%
4 720
8.2%
6 720
8.2%
9 720
8.2%
Other values (2) 1378
15.8%
ValueCountFrequency (%)
1 744
8.5%
2 672
7.7%
3 744
8.5%
4 720
8.2%
5 744
8.5%
6 720
8.2%
7 744
8.5%
8 744
8.5%
9 720
8.2%
10 744
8.5%
ValueCountFrequency (%)
12 744
8.5%
11 706
8.1%
10 744
8.5%
9 720
8.2%
8 744
8.5%
7 744
8.5%
6 720
8.2%
5 744
8.5%
4 720
8.2%
3 744
8.5%


Real number (ℝ)

Distinct31
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.741367
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:57.503781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7883504
Coefficient of variation (CV)0.5582965
Kurtosis-1.1911536
Mean15.741367
Median Absolute Deviation (MAD)8
Skewness0.0056569058
Sum137674
Variance77.235103
MonotonicityNot monotonic
2023-12-12T08:45:57.646892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 288
 
3.3%
15 288
 
3.3%
28 288
 
3.3%
27 288
 
3.3%
26 288
 
3.3%
25 288
 
3.3%
24 288
 
3.3%
23 288
 
3.3%
22 288
 
3.3%
21 288
 
3.3%
Other values (21) 5866
67.1%
ValueCountFrequency (%)
1 288
3.3%
2 284
3.2%
3 278
3.2%
4 288
3.3%
5 288
3.3%
6 288
3.3%
7 288
3.3%
8 288
3.3%
9 288
3.3%
10 288
3.3%
ValueCountFrequency (%)
31 168
1.9%
30 264
3.0%
29 264
3.0%
28 288
3.3%
27 288
3.3%
26 288
3.3%
25 288
3.3%
24 288
3.3%
23 288
3.3%
22 288
3.3%

시간
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.50526
Minimum0
Maximum23
Zeros364
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:57.799232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median12
Q317.75
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation6.9215671
Coefficient of variation (CV)0.60160026
Kurtosis-1.2035347
Mean11.50526
Median Absolute Deviation (MAD)6
Skewness-0.0011513851
Sum100625
Variance47.908091
MonotonicityNot monotonic
2023-12-12T08:45:58.193356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12 365
 
4.2%
13 365
 
4.2%
23 365
 
4.2%
22 365
 
4.2%
18 365
 
4.2%
17 365
 
4.2%
16 365
 
4.2%
15 365
 
4.2%
11 365
 
4.2%
14 365
 
4.2%
Other values (14) 5096
58.3%
ValueCountFrequency (%)
0 364
4.2%
1 364
4.2%
2 364
4.2%
3 364
4.2%
4 364
4.2%
5 364
4.2%
6 364
4.2%
7 364
4.2%
8 364
4.2%
9 364
4.2%
ValueCountFrequency (%)
23 365
4.2%
22 365
4.2%
21 364
4.2%
20 364
4.2%
19 364
4.2%
18 365
4.2%
17 365
4.2%
16 365
4.2%
15 365
4.2%
14 365
4.2%

00분
Real number (ℝ)

HIGH CORRELATION 

Distinct265
Distinct (%)3.0%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.0357954
Minimum2.86
Maximum6.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:58.353140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.54
Range3.68
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32740969
Coefficient of variation (CV)0.081126435
Kurtosis6.678281
Mean4.0357954
Median Absolute Deviation (MAD)0.13
Skewness1.540384
Sum35264.78
Variance0.10719711
MonotonicityNot monotonic
2023-12-12T08:45:58.508519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.06 238
 
2.7%
4.08 219
 
2.5%
3.98 214
 
2.4%
4.0 213
 
2.4%
3.95 203
 
2.3%
4.04 203
 
2.3%
3.99 199
 
2.3%
4.02 197
 
2.3%
3.97 187
 
2.1%
3.96 187
 
2.1%
Other values (255) 6678
76.4%
ValueCountFrequency (%)
2.86 1
 
< 0.1%
2.93 1
 
< 0.1%
3.01 1
 
< 0.1%
3.02 1
 
< 0.1%
3.04 2
< 0.1%
3.06 1
 
< 0.1%
3.08 1
 
< 0.1%
3.09 1
 
< 0.1%
3.1 3
< 0.1%
3.12 1
 
< 0.1%
ValueCountFrequency (%)
6.54 1
< 0.1%
6.5 1
< 0.1%
6.47 1
< 0.1%
6.39 1
< 0.1%
6.3 1
< 0.1%
6.24 1
< 0.1%
6.08 1
< 0.1%
6.07 1
< 0.1%
6.03 1
< 0.1%
6.01 1
< 0.1%

10분
Real number (ℝ)

HIGH CORRELATION 

Distinct258
Distinct (%)3.0%
Missing10
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.0362546
Minimum2.89
Maximum6.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:58.675404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.89
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.5725
Maximum6.55
Range3.66
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32728147
Coefficient of variation (CV)0.081085438
Kurtosis6.7204596
Mean4.0362546
Median Absolute Deviation (MAD)0.13
Skewness1.5458056
Sum35260.72
Variance0.10711316
MonotonicityNot monotonic
2023-12-12T08:45:58.803359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.04 236
 
2.7%
4.06 221
 
2.5%
4.08 220
 
2.5%
3.98 214
 
2.4%
3.99 209
 
2.4%
4.0 206
 
2.4%
4.02 198
 
2.3%
3.97 189
 
2.2%
4.05 186
 
2.1%
4.07 185
 
2.1%
Other values (248) 6672
76.3%
ValueCountFrequency (%)
2.89 1
 
< 0.1%
2.92 1
 
< 0.1%
3.01 2
< 0.1%
3.02 1
 
< 0.1%
3.04 1
 
< 0.1%
3.06 1
 
< 0.1%
3.08 4
< 0.1%
3.1 2
< 0.1%
3.11 1
 
< 0.1%
3.15 2
< 0.1%
ValueCountFrequency (%)
6.55 1
< 0.1%
6.5 1
< 0.1%
6.49 1
< 0.1%
6.38 1
< 0.1%
6.36 1
< 0.1%
6.21 1
< 0.1%
6.06 1
< 0.1%
6.05 1
< 0.1%
6.04 1
< 0.1%
6.03 1
< 0.1%

20분
Real number (ℝ)

HIGH CORRELATION 

Distinct269
Distinct (%)3.1%
Missing13
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.0366335
Minimum2.89
Maximum6.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:58.947239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.89
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.53
Range3.64
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32742034
Coefficient of variation (CV)0.08111223
Kurtosis6.6927903
Mean4.0366335
Median Absolute Deviation (MAD)0.13
Skewness1.5409431
Sum35251.92
Variance0.10720408
MonotonicityNot monotonic
2023-12-12T08:45:59.088761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.06 247
 
2.8%
4.04 218
 
2.5%
3.99 215
 
2.5%
4.08 210
 
2.4%
4.02 206
 
2.4%
3.97 198
 
2.3%
4.0 198
 
2.3%
3.95 198
 
2.3%
4.07 194
 
2.2%
3.98 191
 
2.2%
Other values (259) 6658
76.1%
ValueCountFrequency (%)
2.89 1
< 0.1%
2.96 1
< 0.1%
2.99 1
< 0.1%
3.0 1
< 0.1%
3.03 1
< 0.1%
3.05 1
< 0.1%
3.07 2
< 0.1%
3.08 2
< 0.1%
3.09 1
< 0.1%
3.1 1
< 0.1%
ValueCountFrequency (%)
6.53 1
< 0.1%
6.5 1
< 0.1%
6.47 1
< 0.1%
6.39 1
< 0.1%
6.35 1
< 0.1%
6.18 1
< 0.1%
6.1 1
< 0.1%
6.07 1
< 0.1%
6.04 1
< 0.1%
6.02 1
< 0.1%

30분
Real number (ℝ)

HIGH CORRELATION 

Distinct267
Distinct (%)3.1%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean4.0366251
Minimum2.88
Maximum6.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:59.208265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.88
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.52
Range3.64
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32731721
Coefficient of variation (CV)0.081086851
Kurtosis6.662216
Mean4.0366251
Median Absolute Deviation (MAD)0.13
Skewness1.5347526
Sum35259.92
Variance0.10713656
MonotonicityNot monotonic
2023-12-12T08:45:59.326174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.06 272
 
3.1%
4.0 217
 
2.5%
3.99 213
 
2.4%
4.08 210
 
2.4%
4.04 206
 
2.4%
3.98 202
 
2.3%
3.97 196
 
2.2%
3.95 196
 
2.2%
4.02 191
 
2.2%
4.05 179
 
2.0%
Other values (257) 6653
76.1%
ValueCountFrequency (%)
2.88 1
 
< 0.1%
2.98 2
< 0.1%
3.0 1
 
< 0.1%
3.02 1
 
< 0.1%
3.06 1
 
< 0.1%
3.07 1
 
< 0.1%
3.08 1
 
< 0.1%
3.09 2
< 0.1%
3.1 1
 
< 0.1%
3.11 3
< 0.1%
ValueCountFrequency (%)
6.52 1
< 0.1%
6.51 1
< 0.1%
6.46 1
< 0.1%
6.4 1
< 0.1%
6.33 1
< 0.1%
6.15 2
< 0.1%
6.07 1
< 0.1%
6.04 1
< 0.1%
6.0 1
< 0.1%
5.98 1
< 0.1%

40분
Real number (ℝ)

HIGH CORRELATION 

Distinct266
Distinct (%)3.0%
Missing15
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean4.0364002
Minimum2.86
Maximum6.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:59.450344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.52
Range3.66
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32716103
Coefficient of variation (CV)0.081052673
Kurtosis6.6685197
Mean4.0364002
Median Absolute Deviation (MAD)0.13
Skewness1.5338356
Sum35241.81
Variance0.10703434
MonotonicityNot monotonic
2023-12-12T08:45:59.574020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.08 236
 
2.7%
4.02 216
 
2.5%
3.98 211
 
2.4%
4.06 211
 
2.4%
4.04 210
 
2.4%
4.0 209
 
2.4%
4.05 208
 
2.4%
3.99 207
 
2.4%
3.97 200
 
2.3%
3.95 184
 
2.1%
Other values (256) 6639
75.9%
ValueCountFrequency (%)
2.86 1
< 0.1%
2.97 1
< 0.1%
2.99 1
< 0.1%
3.0 1
< 0.1%
3.02 1
< 0.1%
3.03 1
< 0.1%
3.08 2
< 0.1%
3.09 1
< 0.1%
3.1 2
< 0.1%
3.11 2
< 0.1%
ValueCountFrequency (%)
6.52 1
< 0.1%
6.5 1
< 0.1%
6.45 1
< 0.1%
6.41 1
< 0.1%
6.3 1
< 0.1%
6.2 1
< 0.1%
6.13 1
< 0.1%
6.07 1
< 0.1%
6.04 1
< 0.1%
6.02 1
< 0.1%

50분
Real number (ℝ)

HIGH CORRELATION 

Distinct266
Distinct (%)3.0%
Missing17
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean4.0361828
Minimum2.86
Maximum6.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:59.705272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.58
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.52
Range3.66
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32751988
Coefficient of variation (CV)0.081145948
Kurtosis6.6582888
Mean4.0361828
Median Absolute Deviation (MAD)0.13
Skewness1.534105
Sum35231.84
Variance0.10726927
MonotonicityNot monotonic
2023-12-12T08:45:59.837944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.02 230
 
2.6%
4.06 223
 
2.5%
3.98 220
 
2.5%
4.08 219
 
2.5%
3.99 217
 
2.5%
4.0 212
 
2.4%
3.97 211
 
2.4%
4.04 207
 
2.4%
4.05 190
 
2.2%
3.94 181
 
2.1%
Other values (256) 6619
75.7%
ValueCountFrequency (%)
2.86 1
< 0.1%
2.95 1
< 0.1%
3.02 1
< 0.1%
3.03 1
< 0.1%
3.04 1
< 0.1%
3.06 2
< 0.1%
3.07 1
< 0.1%
3.08 1
< 0.1%
3.1 2
< 0.1%
3.11 1
< 0.1%
ValueCountFrequency (%)
6.52 1
< 0.1%
6.5 1
< 0.1%
6.45 1
< 0.1%
6.42 1
< 0.1%
6.28 1
< 0.1%
6.26 1
< 0.1%
6.11 1
< 0.1%
6.06 1
< 0.1%
6.04 1
< 0.1%
6.02 1
< 0.1%

시간최소
Real number (ℝ)

HIGH CORRELATION 

Distinct261
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0064166
Minimum2.86
Maximum6.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:45:59.962712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.53
Q13.85
median3.99
Q34.11
95-th percentile4.55
Maximum6.5
Range3.64
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.33077163
Coefficient of variation (CV)0.082560466
Kurtosis6.1731042
Mean4.0064166
Median Absolute Deviation (MAD)0.13
Skewness1.4281186
Sum35040.12
Variance0.10940987
MonotonicityNot monotonic
2023-12-12T08:46:00.104966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.94 222
 
2.5%
3.97 219
 
2.5%
3.98 211
 
2.4%
3.99 209
 
2.4%
4.02 209
 
2.4%
4.06 208
 
2.4%
4.04 205
 
2.3%
4.08 202
 
2.3%
3.95 198
 
2.3%
4.0 194
 
2.2%
Other values (251) 6669
76.3%
ValueCountFrequency (%)
2.86 2
< 0.1%
2.95 1
 
< 0.1%
2.99 1
 
< 0.1%
3.02 2
< 0.1%
3.03 1
 
< 0.1%
3.06 3
< 0.1%
3.08 3
< 0.1%
3.1 1
 
< 0.1%
3.11 2
< 0.1%
3.13 3
< 0.1%
ValueCountFrequency (%)
6.5 1
< 0.1%
6.47 1
< 0.1%
6.42 1
< 0.1%
6.3 1
< 0.1%
6.28 1
< 0.1%
6.11 1
< 0.1%
6.04 1
< 0.1%
6.03 1
< 0.1%
5.96 1
< 0.1%
5.93 2
< 0.1%

시간최대
Real number (ℝ)

HIGH CORRELATION 

Distinct265
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0660142
Minimum2.93
Maximum6.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:46:00.248083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.93
5-th percentile3.63
Q13.91
median4.04
Q34.16
95-th percentile4.61
Maximum6.55
Range3.62
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.32295435
Coefficient of variation (CV)0.079427749
Kurtosis7.2336011
Mean4.0660142
Median Absolute Deviation (MAD)0.13
Skewness1.6671119
Sum35561.36
Variance0.10429951
MonotonicityNot monotonic
2023-12-12T08:46:00.375481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.06 254
 
2.9%
4.08 244
 
2.8%
4.0 233
 
2.7%
3.99 230
 
2.6%
3.98 206
 
2.4%
4.02 205
 
2.3%
4.1 191
 
2.2%
4.07 188
 
2.1%
4.09 186
 
2.1%
4.05 180
 
2.1%
Other values (255) 6629
75.8%
ValueCountFrequency (%)
2.93 1
 
< 0.1%
3.04 3
< 0.1%
3.07 1
 
< 0.1%
3.09 1
 
< 0.1%
3.1 3
< 0.1%
3.12 2
< 0.1%
3.13 2
< 0.1%
3.15 1
 
< 0.1%
3.17 3
< 0.1%
3.18 1
 
< 0.1%
ValueCountFrequency (%)
6.55 1
< 0.1%
6.52 1
< 0.1%
6.5 1
< 0.1%
6.45 1
< 0.1%
6.39 1
< 0.1%
6.26 1
< 0.1%
6.24 1
< 0.1%
6.08 1
< 0.1%
6.07 2
< 0.1%
6.02 1
< 0.1%

시간평균
Real number (ℝ)

HIGH CORRELATION 

Distinct262
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0370478
Minimum2.89
Maximum6.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.0 KiB
2023-12-12T08:46:00.500622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.89
5-th percentile3.59
Q13.88
median4.01
Q34.14
95-th percentile4.58
Maximum6.53
Range3.64
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.32550085
Coefficient of variation (CV)0.080628436
Kurtosis6.8239289
Mean4.0370478
Median Absolute Deviation (MAD)0.13
Skewness1.571511
Sum35308.02
Variance0.1059508
MonotonicityNot monotonic
2023-12-12T08:46:00.627103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.99 230
 
2.6%
4.06 229
 
2.6%
4.04 226
 
2.6%
4.05 217
 
2.5%
4.07 205
 
2.3%
3.97 204
 
2.3%
4.0 204
 
2.3%
4.08 202
 
2.3%
3.98 196
 
2.2%
3.96 187
 
2.1%
Other values (252) 6646
76.0%
ValueCountFrequency (%)
2.89 1
 
< 0.1%
2.97 1
 
< 0.1%
2.99 1
 
< 0.1%
3.01 1
 
< 0.1%
3.03 1
 
< 0.1%
3.06 1
 
< 0.1%
3.07 1
 
< 0.1%
3.08 1
 
< 0.1%
3.09 3
< 0.1%
3.1 1
 
< 0.1%
ValueCountFrequency (%)
6.53 1
< 0.1%
6.5 1
< 0.1%
6.47 1
< 0.1%
6.39 1
< 0.1%
6.34 1
< 0.1%
6.17 1
< 0.1%
6.12 1
< 0.1%
6.06 1
< 0.1%
6.05 1
< 0.1%
6.0 1
< 0.1%

Interactions

2023-12-12T08:45:55.321574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.023631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.128062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.137717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.291418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.556876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.121568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.479715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.760882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.872892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.391339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.713983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.438504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.120055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.217641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.210337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.392579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.651573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.211040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.590368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.844957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.961072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.483227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.814147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.544667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.228919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.302574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.293509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.498106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.071577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.299522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.691100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.935899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.056584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.582737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.935897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.643064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.318555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.380302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.367880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.585591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.163769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.382941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.803891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.018050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.143014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.684795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.040297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.766997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.407655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.460311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.463879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.677186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.268415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.477858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.900924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.113045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.239465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.805574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.204107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.895440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.498646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.542215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.603446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.782055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.379154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.584269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.018401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.196105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.340385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.899241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.324955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.004533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.596693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.623747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.690514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.896131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.491109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.693406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.131973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.286575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.446883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.000935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.463056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.140883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.691010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.703102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.789399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.992123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.601342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.816389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.261806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.377370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.542903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.096774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.616933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.264158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.783906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.786893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.884295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.115863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.720014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.964167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.362013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.486139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.657839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.197405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.759126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.401792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.883420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.866295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.001818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.254385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.824916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.086049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.462520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.592639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.814791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.298314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:54.899310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.514681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:41.960277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.953177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.087182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.352734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:46.919090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.183933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.575462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.688647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:51.936901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.415044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.045428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:56.632208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:42.043019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:43.050845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:44.198434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:45.453355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.030453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.315233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:49.669042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:50.782621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:52.294966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:53.562778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:55.184386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:46:00.775471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0000.0000.5910.5850.5910.5920.5980.5940.5920.5890.593
0.0001.0000.0000.3990.4060.4180.4090.4040.4080.4060.4150.421
시간0.0000.0001.0000.2000.1980.1930.1850.1820.1850.2040.1860.193
00분0.5910.3990.2001.0000.9970.9970.9940.9900.9850.9960.9890.996
10분0.5850.4060.1980.9971.0000.9990.9960.9910.9860.9950.9950.999
20분0.5910.4180.1930.9970.9991.0000.9990.9950.9910.9970.9951.000
30분0.5920.4090.1850.9940.9960.9991.0000.9980.9950.9980.9930.999
40분0.5980.4040.1820.9900.9910.9950.9981.0000.9990.9970.9930.996
50분0.5940.4080.1850.9850.9860.9910.9950.9991.0000.9960.9920.993
시간최소0.5920.4060.2040.9960.9950.9970.9980.9970.9961.0000.9860.997
시간최대0.5890.4150.1860.9890.9950.9950.9930.9930.9920.9861.0000.996
시간평균0.5930.4210.1930.9960.9991.0000.9990.9960.9930.9970.9961.000
2023-12-12T08:46:00.894308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간00분10분20분30분40분50분시간최소시간최대시간평균
1.0000.0150.0010.0300.0300.0290.0280.0270.0290.0350.0230.028
0.0151.000-0.001-0.086-0.085-0.086-0.087-0.088-0.087-0.086-0.087-0.086
시간0.001-0.0011.0000.0990.0970.0930.0900.0860.0810.0950.0840.092
00분0.030-0.0860.0991.0000.9940.9810.9650.9490.9290.9790.9580.980
10분0.030-0.0850.0970.9941.0000.9940.9830.9670.9480.9840.9710.992
20분0.029-0.0860.0930.9810.9941.0000.9940.9820.9650.9840.9790.997
30분0.028-0.0870.0900.9650.9830.9941.0000.9940.9800.9790.9830.997
40분0.027-0.0880.0860.9490.9670.9820.9941.0000.9930.9720.9830.990
50분0.029-0.0870.0810.9290.9480.9650.9800.9931.0000.9600.9770.977
시간최소0.035-0.0860.0950.9790.9840.9840.9790.9720.9601.0000.9490.987
시간최대0.023-0.0870.0840.9580.9710.9790.9830.9830.9770.9491.0000.984
시간평균0.028-0.0860.0920.9800.9920.9970.9970.9900.9770.9870.9841.000

Missing values

2023-12-12T08:45:56.773708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:45:56.949216image/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.
2023-12-12T08:45:57.089989image/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

시간00분10분20분30분40분50분시간최소시간최대시간평균
01103.883.823.773.743.723.73.73.883.77
11113.693.673.663.653.643.73.643.73.67
21123.783.873.933.984.074.153.784.153.96
31134.194.164.14.023.984.013.984.194.08
41144.054.14.14.114.154.154.054.154.11
51154.124.084.064.054.044.024.024.124.06
61164.024.024.024.014.014.014.014.024.02
71174.014.014.014.024.044.064.014.064.03
81184.064.084.094.094.094.084.064.094.08
91194.084.074.064.054.054.044.044.084.06
시간00분10분20분30분40분50분시간최소시간최대시간평균
87361231144.14.114.114.114.14.114.14.114.11
87371231154.114.124.124.134.134.134.114.134.12
87381231164.134.124.124.134.124.124.124.134.12
87391231174.14.124.124.14.084.084.084.124.1
87401231184.084.064.064.064.074.084.064.084.07
87411231194.084.084.084.084.084.084.084.084.08
87421231204.074.074.084.084.064.044.044.084.07
87431231214.044.044.054.044.044.054.044.054.04
87441231224.044.044.024.024.034.044.024.044.03
87451231234.044.044.044.054.054.054.044.054.05