Overview

Dataset statistics

Number of variables13
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory118.3 B

Variable types

Numeric13

Alerts

순번 is highly overall correlated with 일자High correlation
일자 is highly overall correlated with 순번High correlation
10센티미터 is highly overall correlated with 20센티미터 and 4 other fieldsHigh correlation
20센티미터 is highly overall correlated with 10센티미터 and 4 other fieldsHigh correlation
40센티미터 is highly overall correlated with 20센티미터 and 4 other fieldsHigh correlation
60센티미터 is highly overall correlated with 40센티미터 and 4 other fieldsHigh correlation
80센티미터 is highly overall correlated with 40센티미터 and 5 other fieldsHigh correlation
평균값 is highly overall correlated with 10센티미터 and 5 other fieldsHigh correlation
10센티미터 편차 is highly overall correlated with 10센티미터 and 5 other fieldsHigh correlation
20센티미터 편차 is highly overall correlated with 10센티미터 and 5 other fieldsHigh correlation
40센티미터 편차 is highly overall correlated with 40센티미터 and 5 other fieldsHigh correlation
60센티미터 편차 is highly overall correlated with 60센티미터 and 4 other fieldsHigh correlation
80센티미터 편차 is highly overall correlated with 10센티미터 and 4 other fieldsHigh correlation
순번 has unique valuesUnique
일자 has unique valuesUnique
60센티미터 편차 has 5 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-16 15:31:57.660880
Analysis finished2024-04-16 15:32:13.969650
Duration16.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:14.046299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2024-04-17T00:32:14.192739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

일자
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200233
Minimum20200101
Maximum20200409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:14.308661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200101
5-th percentile20200106
Q120200126
median20200220
Q320200315
95-th percentile20200404
Maximum20200409
Range308
Interquartile range (IQR)189.5

Descriptive statistics

Standard deviation96.431907
Coefficient of variation (CV)4.7738018 × 10-6
Kurtosis-1.1697238
Mean20200233
Median Absolute Deviation (MAD)95
Skewness0.16257304
Sum2.0200233 × 109
Variance9299.1127
MonotonicityStrictly increasing
2024-04-17T00:32:14.439745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200101 1
 
1.0%
20200305 1
 
1.0%
20200315 1
 
1.0%
20200314 1
 
1.0%
20200313 1
 
1.0%
20200312 1
 
1.0%
20200311 1
 
1.0%
20200310 1
 
1.0%
20200309 1
 
1.0%
20200308 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
20200101 1
1.0%
20200102 1
1.0%
20200103 1
1.0%
20200104 1
1.0%
20200105 1
1.0%
20200106 1
1.0%
20200107 1
1.0%
20200108 1
1.0%
20200109 1
1.0%
20200110 1
1.0%
ValueCountFrequency (%)
20200409 1
1.0%
20200408 1
1.0%
20200407 1
1.0%
20200406 1
1.0%
20200405 1
1.0%
20200404 1
1.0%
20200403 1
1.0%
20200402 1
1.0%
20200401 1
1.0%
20200331 1
1.0%

10센티미터
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.073
Minimum25
Maximum33.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:14.570098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile25.595
Q126.675
median27.9
Q329.325
95-th percentile31.01
Maximum33.7
Range8.7
Interquartile range (IQR)2.65

Descriptive statistics

Standard deviation1.7756407
Coefficient of variation (CV)0.063250836
Kurtosis-0.14678434
Mean28.073
Median Absolute Deviation (MAD)1.4
Skewness0.40908148
Sum2807.3
Variance3.1529
MonotonicityNot monotonic
2024-04-17T00:32:14.682161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.8 5
 
5.0%
26.2 4
 
4.0%
27.1 4
 
4.0%
28.2 4
 
4.0%
27.7 4
 
4.0%
29.6 3
 
3.0%
28.7 3
 
3.0%
28.9 3
 
3.0%
25.6 3
 
3.0%
27.4 3
 
3.0%
Other values (43) 64
64.0%
ValueCountFrequency (%)
25.0 1
 
1.0%
25.3 2
2.0%
25.4 1
 
1.0%
25.5 1
 
1.0%
25.6 3
3.0%
25.7 1
 
1.0%
25.8 2
2.0%
25.9 3
3.0%
26.0 1
 
1.0%
26.1 1
 
1.0%
ValueCountFrequency (%)
33.7 1
 
1.0%
32.1 1
 
1.0%
31.9 1
 
1.0%
31.4 1
 
1.0%
31.2 1
 
1.0%
31.0 1
 
1.0%
30.4 1
 
1.0%
30.3 1
 
1.0%
30.2 3
3.0%
30.1 1
 
1.0%

20센티미터
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.507
Minimum26.4
Maximum34.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:14.791806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.4
5-th percentile26.9
Q127.975
median29.55
Q330.925
95-th percentile32.23
Maximum34.3
Range7.9
Interquartile range (IQR)2.95

Descriptive statistics

Standard deviation1.795013
Coefficient of variation (CV)0.060833464
Kurtosis-0.66133784
Mean29.507
Median Absolute Deviation (MAD)1.45
Skewness0.25889915
Sum2950.7
Variance3.2220717
MonotonicityNot monotonic
2024-04-17T00:32:14.905829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.2 5
 
5.0%
30.2 4
 
4.0%
28.7 3
 
3.0%
30.4 3
 
3.0%
30.5 3
 
3.0%
27.4 3
 
3.0%
29.9 3
 
3.0%
31.0 3
 
3.0%
29.8 3
 
3.0%
29.5 3
 
3.0%
Other values (42) 67
67.0%
ValueCountFrequency (%)
26.4 1
 
1.0%
26.5 1
 
1.0%
26.7 2
 
2.0%
26.9 2
 
2.0%
27.0 1
 
1.0%
27.2 5
5.0%
27.4 3
3.0%
27.5 3
3.0%
27.6 2
 
2.0%
27.7 2
 
2.0%
ValueCountFrequency (%)
34.3 1
 
1.0%
33.6 1
 
1.0%
32.9 1
 
1.0%
32.8 2
2.0%
32.2 1
 
1.0%
32.1 2
2.0%
31.9 1
 
1.0%
31.8 1
 
1.0%
31.7 2
2.0%
31.5 3
3.0%

40센티미터
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.205
Minimum18.6
Maximum28.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:15.025887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.6
5-th percentile18.8
Q120
median20.7
Q321.825
95-th percentile25.115
Maximum28.5
Range9.9
Interquartile range (IQR)1.825

Descriptive statistics

Standard deviation1.8161106
Coefficient of variation (CV)0.085645393
Kurtosis2.874371
Mean21.205
Median Absolute Deviation (MAD)0.8
Skewness1.5073308
Sum2120.5
Variance3.2982576
MonotonicityNot monotonic
2024-04-17T00:32:15.149030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
20.0 7
 
7.0%
20.6 5
 
5.0%
19.9 5
 
5.0%
20.4 5
 
5.0%
19.7 4
 
4.0%
20.7 4
 
4.0%
19.8 3
 
3.0%
22.1 3
 
3.0%
21.1 3
 
3.0%
18.7 3
 
3.0%
Other values (38) 58
58.0%
ValueCountFrequency (%)
18.6 1
 
1.0%
18.7 3
3.0%
18.8 2
2.0%
19.2 1
 
1.0%
19.3 1
 
1.0%
19.4 1
 
1.0%
19.5 1
 
1.0%
19.6 1
 
1.0%
19.7 4
4.0%
19.8 3
3.0%
ValueCountFrequency (%)
28.5 1
1.0%
26.8 1
1.0%
26.0 1
1.0%
25.7 1
1.0%
25.4 1
1.0%
25.1 1
1.0%
24.4 1
1.0%
24.3 1
1.0%
23.9 1
1.0%
23.7 2
2.0%

60센티미터
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.13
Minimum22.5
Maximum29.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:15.266169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.5
5-th percentile22.5
Q124.1
median24.8
Q325.8
95-th percentile28.13
Maximum29.8
Range7.3
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation1.5298709
Coefficient of variation (CV)0.06087827
Kurtosis0.95051872
Mean25.13
Median Absolute Deviation (MAD)0.8
Skewness0.91068059
Sum2513
Variance2.3405051
MonotonicityNot monotonic
2024-04-17T00:32:15.387525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
24.0 9
 
9.0%
24.6 7
 
7.0%
22.5 6
 
6.0%
24.1 6
 
6.0%
24.2 4
 
4.0%
25.8 4
 
4.0%
25.4 4
 
4.0%
25.1 4
 
4.0%
24.8 4
 
4.0%
25.3 3
 
3.0%
Other values (35) 49
49.0%
ValueCountFrequency (%)
22.5 6
6.0%
23.4 1
 
1.0%
23.5 1
 
1.0%
23.6 1
 
1.0%
23.7 1
 
1.0%
23.8 2
 
2.0%
23.9 1
 
1.0%
24.0 9
9.0%
24.1 6
6.0%
24.2 4
4.0%
ValueCountFrequency (%)
29.8 1
1.0%
29.3 1
1.0%
29.2 1
1.0%
28.7 2
2.0%
28.1 1
1.0%
28.0 1
1.0%
27.8 1
1.0%
27.5 2
2.0%
27.2 1
1.0%
27.0 2
2.0%

80센티미터
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.636
Minimum19.5
Maximum23.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:15.500545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19.5
5-th percentile19.6
Q121.2
median21.6
Q322
95-th percentile23.005
Maximum23.7
Range4.2
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.81470327
Coefficient of variation (CV)0.037654986
Kurtosis1.2987106
Mean21.636
Median Absolute Deviation (MAD)0.4
Skewness-0.34190037
Sum2163.6
Variance0.66374141
MonotonicityNot monotonic
2024-04-17T00:32:15.626346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
21.1 10
 
10.0%
21.7 9
 
9.0%
21.5 7
 
7.0%
21.6 7
 
7.0%
21.2 6
 
6.0%
21.9 6
 
6.0%
22.0 6
 
6.0%
21.4 5
 
5.0%
21.3 4
 
4.0%
19.6 3
 
3.0%
Other values (19) 37
37.0%
ValueCountFrequency (%)
19.5 3
 
3.0%
19.6 3
 
3.0%
20.8 2
 
2.0%
20.9 2
 
2.0%
21.0 3
 
3.0%
21.1 10
10.0%
21.2 6
6.0%
21.3 4
 
4.0%
21.4 5
5.0%
21.5 7
7.0%
ValueCountFrequency (%)
23.7 1
1.0%
23.5 1
1.0%
23.2 1
1.0%
23.1 2
2.0%
23.0 1
1.0%
22.9 2
2.0%
22.8 2
2.0%
22.7 2
2.0%
22.6 1
1.0%
22.5 1
1.0%

평균값
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.112
Minimum22.9
Maximum29.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:15.740753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.9
5-th percentile23.1
Q124.175
median25.1
Q325.8
95-th percentile27.51
Maximum29.5
Range6.6
Interquartile range (IQR)1.625

Descriptive statistics

Standard deviation1.3247664
Coefficient of variation (CV)0.052754317
Kurtosis0.73319861
Mean25.112
Median Absolute Deviation (MAD)0.8
Skewness0.71524485
Sum2511.2
Variance1.7550061
MonotonicityNot monotonic
2024-04-17T00:32:15.858195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
25.3 7
 
7.0%
25.2 5
 
5.0%
24.0 5
 
5.0%
25.0 5
 
5.0%
25.4 4
 
4.0%
24.8 4
 
4.0%
25.5 4
 
4.0%
25.8 4
 
4.0%
25.1 3
 
3.0%
24.2 3
 
3.0%
Other values (33) 56
56.0%
ValueCountFrequency (%)
22.9 1
 
1.0%
23.0 2
 
2.0%
23.1 3
3.0%
23.3 2
 
2.0%
23.4 2
 
2.0%
23.5 2
 
2.0%
23.6 3
3.0%
23.7 1
 
1.0%
23.8 3
3.0%
24.0 5
5.0%
ValueCountFrequency (%)
29.5 1
1.0%
28.4 2
2.0%
28.3 1
1.0%
27.7 1
1.0%
27.5 2
2.0%
27.2 1
1.0%
27.1 1
1.0%
26.9 1
1.0%
26.7 1
1.0%
26.5 2
2.0%

10센티미터 편차
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.961
Minimum1.5
Maximum5.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:15.973274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile1.6
Q12.1
median2.6
Q33.8
95-th percentile4.805
Maximum5.4
Range3.9
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation1.0448426
Coefficient of variation (CV)0.35286814
Kurtosis-0.90875786
Mean2.961
Median Absolute Deviation (MAD)0.75
Skewness0.49408215
Sum296.1
Variance1.091696
MonotonicityNot monotonic
2024-04-17T00:32:16.082966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2.1 8
 
8.0%
1.6 6
 
6.0%
2.4 6
 
6.0%
1.9 5
 
5.0%
2.6 5
 
5.0%
2.3 5
 
5.0%
2.0 5
 
5.0%
4.1 4
 
4.0%
3.8 4
 
4.0%
4.3 4
 
4.0%
Other values (23) 48
48.0%
ValueCountFrequency (%)
1.5 1
 
1.0%
1.6 6
6.0%
1.7 3
 
3.0%
1.8 3
 
3.0%
1.9 5
5.0%
2.0 5
5.0%
2.1 8
8.0%
2.2 2
 
2.0%
2.3 5
5.0%
2.4 6
6.0%
ValueCountFrequency (%)
5.4 2
2.0%
5.0 1
 
1.0%
4.9 2
2.0%
4.8 2
2.0%
4.6 1
 
1.0%
4.4 2
2.0%
4.3 4
4.0%
4.2 2
2.0%
4.1 4
4.0%
4.0 3
3.0%

20센티미터 편차
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.395
Minimum3.1
Maximum6.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:16.245369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile3.295
Q13.675
median4.2
Q35.125
95-th percentile5.905
Maximum6.3
Range3.2
Interquartile range (IQR)1.45

Descriptive statistics

Standard deviation0.88150182
Coefficient of variation (CV)0.20056924
Kurtosis-1.0540809
Mean4.395
Median Absolute Deviation (MAD)0.7
Skewness0.44018819
Sum439.5
Variance0.77704545
MonotonicityNot monotonic
2024-04-17T00:32:16.356958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
3.4 7
 
7.0%
3.8 7
 
7.0%
3.7 7
 
7.0%
3.6 6
 
6.0%
5.5 5
 
5.0%
4.0 5
 
5.0%
4.7 5
 
5.0%
5.7 4
 
4.0%
3.2 4
 
4.0%
3.5 4
 
4.0%
Other values (19) 46
46.0%
ValueCountFrequency (%)
3.1 1
 
1.0%
3.2 4
4.0%
3.3 3
3.0%
3.4 7
7.0%
3.5 4
4.0%
3.6 6
6.0%
3.7 7
7.0%
3.8 7
7.0%
3.9 1
 
1.0%
4.0 5
5.0%
ValueCountFrequency (%)
6.3 1
 
1.0%
6.1 1
 
1.0%
6.0 3
3.0%
5.9 3
3.0%
5.8 1
 
1.0%
5.7 4
4.0%
5.5 5
5.0%
5.3 3
3.0%
5.2 4
4.0%
5.1 3
3.0%

40센티미터 편차
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.907
Minimum-5.3
Maximum-1
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2024-04-17T00:32:16.470942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.3
5-th percentile-5
Q1-4.5
median-3.8
Q3-3.5
95-th percentile-2.595
Maximum-1
Range4.3
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.77788304
Coefficient of variation (CV)-0.19909983
Kurtosis1.5282269
Mean-3.907
Median Absolute Deviation (MAD)0.5
Skewness0.78640816
Sum-390.7
Variance0.60510202
MonotonicityNot monotonic
2024-04-17T00:32:16.570314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
-3.7 11
 
11.0%
-3.8 11
 
11.0%
-4.5 6
 
6.0%
-3.3 6
 
6.0%
-4.8 6
 
6.0%
-3.2 5
 
5.0%
-4.2 4
 
4.0%
-4.3 4
 
4.0%
-3.9 4
 
4.0%
-4.1 4
 
4.0%
Other values (19) 39
39.0%
ValueCountFrequency (%)
-5.3 2
 
2.0%
-5.2 2
 
2.0%
-5.0 3
3.0%
-4.9 2
 
2.0%
-4.8 6
6.0%
-4.7 4
4.0%
-4.6 3
3.0%
-4.5 6
6.0%
-4.4 2
 
2.0%
-4.3 4
4.0%
ValueCountFrequency (%)
-1.0 1
 
1.0%
-1.6 1
 
1.0%
-2.1 1
 
1.0%
-2.4 1
 
1.0%
-2.5 1
 
1.0%
-2.6 2
 
2.0%
-2.8 1
 
1.0%
-2.9 2
 
2.0%
-3.2 5
5.0%
-3.3 6
6.0%

60센티미터 편차
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.018
Minimum-1.6
Maximum1.2
Zeros5
Zeros (%)5.0%
Negative42
Negative (%)42.0%
Memory size1.0 KiB
2024-04-17T00:32:16.664095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.6
5-th percentile-1.2
Q1-0.7
median0.2
Q30.7
95-th percentile0.9
Maximum1.2
Range2.8
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation0.74146729
Coefficient of variation (CV)41.192627
Kurtosis-1.2220211
Mean0.018
Median Absolute Deviation (MAD)0.6
Skewness-0.34937971
Sum1.8
Variance0.54977374
MonotonicityNot monotonic
2024-04-17T00:32:16.763925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.8 13
 
13.0%
0.5 7
 
7.0%
-1.0 6
 
6.0%
0.9 6
 
6.0%
-0.7 6
 
6.0%
0.0 5
 
5.0%
0.7 5
 
5.0%
0.4 5
 
5.0%
0.3 4
 
4.0%
0.6 4
 
4.0%
Other values (17) 39
39.0%
ValueCountFrequency (%)
-1.6 1
 
1.0%
-1.3 3
3.0%
-1.2 2
 
2.0%
-1.1 3
3.0%
-1.0 6
6.0%
-0.9 3
3.0%
-0.8 2
 
2.0%
-0.7 6
6.0%
-0.6 4
4.0%
-0.5 3
3.0%
ValueCountFrequency (%)
1.2 1
 
1.0%
1.1 1
 
1.0%
1.0 2
 
2.0%
0.9 6
6.0%
0.8 13
13.0%
0.7 5
 
5.0%
0.6 4
 
4.0%
0.5 7
7.0%
0.4 5
 
5.0%
0.3 4
 
4.0%

80센티미터 편차
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.476
Minimum-7.3
Maximum-2.1
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2024-04-17T00:32:17.185479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.3
5-th percentile-4.72
Q1-4
median-3.5
Q3-2.775
95-th percentile-2.295
Maximum-2.1
Range5.2
Interquartile range (IQR)1.225

Descriptive statistics

Standard deviation0.90063053
Coefficient of variation (CV)-0.25909969
Kurtosis2.4254161
Mean-3.476
Median Absolute Deviation (MAD)0.65
Skewness-0.9718216
Sum-347.6
Variance0.81113535
MonotonicityNot monotonic
2024-04-17T00:32:17.300713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
-3.6 9
 
9.0%
-2.3 6
 
6.0%
-4.3 6
 
6.0%
-3.8 6
 
6.0%
-3.5 5
 
5.0%
-3.0 4
 
4.0%
-3.4 4
 
4.0%
-4.2 4
 
4.0%
-3.2 4
 
4.0%
-2.7 4
 
4.0%
Other values (22) 48
48.0%
ValueCountFrequency (%)
-7.3 1
 
1.0%
-6.0 1
 
1.0%
-5.4 1
 
1.0%
-5.3 1
 
1.0%
-5.1 1
 
1.0%
-4.7 1
 
1.0%
-4.6 1
 
1.0%
-4.5 3
3.0%
-4.4 2
 
2.0%
-4.3 6
6.0%
ValueCountFrequency (%)
-2.1 2
 
2.0%
-2.2 3
3.0%
-2.3 6
6.0%
-2.4 4
4.0%
-2.5 3
3.0%
-2.6 3
3.0%
-2.7 4
4.0%
-2.8 3
3.0%
-2.9 2
 
2.0%
-3.0 4
4.0%

Interactions

2024-04-17T00:32:12.483624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.356665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.529387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.678892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.946684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.050044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.947460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.041274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.964841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.344072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.395170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.486006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.391140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.567859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.502118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.616962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.767044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.024165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.117025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.031366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.109551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.037786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.431042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.475160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.553958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.467820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.894099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.586103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.691738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.850549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.110056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.190260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.126878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.181774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.116154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.522458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.557808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.625297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.544942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.952613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.671091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.772470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.924441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.178458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.254510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.208711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.255252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.191484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.598973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.642597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.684208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.627726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.034208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.755966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.851976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.280717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.263451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.329490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.288551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.340539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.269048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.678648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.733949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.754818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.731837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.104918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.833409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.926362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.348658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.335139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.395672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.362751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.416858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.647493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.745331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.843542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.814032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.804754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.185053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.913620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.009402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.429579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.445775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.470182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.453953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.496400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.747533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.821664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.937452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.888729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.892584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.254995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:31:59.985773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.081374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.491759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.532646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.531615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.534989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.555847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.824268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.893360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.017744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.963481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.006913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.332309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.069959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.166831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.563488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.621349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.599134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.652682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.624163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.911048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.972405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.114013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.039530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.104466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.416282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.166535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.258645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.647109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.714993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.674843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.742557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.691735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:07.999803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.072913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.195783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.119315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.187459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.490731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.249225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.366611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.720780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.794411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.746971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.819505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.758447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.093224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.152250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.271851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.190790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.267564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.571029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.326412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.471226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.792290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.873646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.808081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.892593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.825434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.178872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.225619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.342025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.259993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.340707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:13.649282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:00.433347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:01.571154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:02.865304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:03.968188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:04.876086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:05.968094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:06.895162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:08.252857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:09.309842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:10.414888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:11.324718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:12.412567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T00:32:17.387874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번일자10센티미터20센티미터40센티미터60센티미터80센티미터평균값10센티미터 편차20센티미터 편차40센티미터 편차60센티미터 편차80센티미터 편차
순번1.0000.9480.5600.6550.8300.8890.7970.7080.7380.5300.7860.7000.467
일자0.9481.0000.3060.4960.6760.7800.6910.6620.5130.0000.5300.4730.566
10센티미터0.5600.3061.0000.9510.8550.6720.5190.8830.7970.7270.8420.6770.911
20센티미터0.6550.4960.9511.0000.8210.7550.5290.8660.6120.7510.7740.5960.909
40센티미터0.8300.6760.8550.8211.0000.9720.8940.9710.3920.3930.9500.6680.758
60센티미터0.8890.7800.6720.7550.9721.0000.9040.9270.4840.5320.8820.7150.592
80센티미터0.7970.6910.5190.5290.8940.9041.0000.7500.4120.4370.8100.6810.528
평균값0.7080.6620.8830.8660.9710.9270.7501.0000.4350.4760.8950.6750.786
10센티미터 편차0.7380.5130.7970.6120.3920.4840.4120.4351.0000.8240.8520.9100.651
20센티미터 편차0.5300.0000.7270.7510.3930.5320.4370.4760.8241.0000.6430.8480.704
40센티미터 편차0.7860.5300.8420.7740.9500.8820.8100.8950.8520.6431.0000.8990.730
60센티미터 편차0.7000.4730.6770.5960.6680.7150.6810.6750.9100.8480.8991.0000.758
80센티미터 편차0.4670.5660.9110.9090.7580.5920.5280.7860.6510.7040.7300.7581.000
2024-04-17T00:32:17.516652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번일자10센티미터20센티미터40센티미터60센티미터80센티미터평균값10센티미터 편차20센티미터 편차40센티미터 편차60센티미터 편차80센티미터 편차
순번1.0001.000-0.155-0.206-0.241-0.210-0.181-0.1990.043-0.115-0.148-0.0220.258
일자1.0001.000-0.155-0.206-0.241-0.210-0.181-0.1990.043-0.115-0.148-0.0220.258
10센티미터-0.155-0.1551.0000.9510.4890.3640.2270.8150.6540.769-0.316-0.487-0.939
20센티미터-0.206-0.2060.9511.0000.6280.4940.3320.8890.4990.747-0.166-0.366-0.950
40센티미터-0.241-0.2410.4890.6281.0000.9780.8790.885-0.2490.0230.5800.401-0.475
60센티미터-0.210-0.2100.3640.4940.9781.0000.9380.806-0.376-0.1400.6770.538-0.336
80센티미터-0.181-0.1810.2270.3320.8790.9381.0000.676-0.502-0.3100.6790.661-0.164
평균값-0.199-0.1990.8150.8890.8850.8060.6761.0000.1460.3980.2130.032-0.778
10센티미터 편차0.0430.0430.6540.499-0.249-0.376-0.5020.1461.0000.874-0.838-0.937-0.611
20센티미터 편차-0.115-0.1150.7690.7470.023-0.140-0.3100.3980.8741.000-0.700-0.841-0.805
40센티미터 편차-0.148-0.148-0.316-0.1660.5800.6770.6790.213-0.838-0.7001.0000.8990.257
60센티미터 편차-0.022-0.022-0.487-0.3660.4010.5380.6610.032-0.937-0.8410.8991.0000.467
80센티미터 편차0.2580.258-0.939-0.950-0.475-0.336-0.164-0.778-0.611-0.8050.2570.4671.000

Missing values

2024-04-17T00:32:13.755342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T00:32:13.908870image/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

순번일자10센티미터20센티미터40센티미터60센티미터80센티미터평균값10센티미터 편차20센티미터 편차40센티미터 편차60센티미터 편차80센티미터 편차
012020010127.728.718.822.519.623.54.25.2-4.7-1.0-3.9
122020010227.128.318.822.519.623.33.85.0-4.5-0.8-3.7
232020010326.728.018.722.519.623.13.64.9-4.4-0.6-3.5
342020010426.627.718.722.519.523.03.64.7-4.3-0.5-3.5
452020010526.227.518.722.519.522.93.34.6-4.2-0.4-3.4
562020010627.327.618.622.519.523.14.24.5-4.5-0.6-3.6
672020010733.734.325.727.021.028.35.46.0-2.6-1.3-7.3
782020010832.133.628.529.823.529.52.64.1-1.00.3-6.0
892020010930.032.226.829.323.728.41.63.8-1.60.9-4.7
9102020011029.031.325.428.723.227.51.53.8-2.11.2-4.3
순번일자10센티미터20센티미터40센티미터60센티미터80센티미터평균값10센티미터 편차20센티미터 편차40센티미터 편차60센티미터 편차80센티미터 편차
90912020033128.129.520.024.121.224.63.54.9-4.6-0.5-3.4
91922020040127.729.119.924.021.124.43.34.7-4.5-0.4-3.3
92932020040227.328.619.824.021.124.23.14.4-4.4-0.2-3.1
93942020040326.928.219.723.921.124.02.94.2-4.3-0.1-2.9
94952020040426.527.819.723.821.023.82.74.0-4.10.0-2.8
95962020040526.227.519.623.821.023.62.63.9-4.00.2-2.6
96972020040625.827.219.523.720.923.42.43.8-3.90.3-2.5
97982020040725.626.919.423.620.923.32.33.6-3.90.3-2.4
98992020040825.326.719.323.520.823.12.23.6-3.80.4-2.3
991002020040925.026.419.223.420.823.02.03.4-3.80.4-2.2