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 일자()High correlation
일자() is highly overall correlated with 순번()High correlation
10센티미터() is highly overall correlated with 20센티미터() and 4 other fieldsHigh correlation
20센티미터() is highly overall correlated with 10센티미터() and 6 other fieldsHigh correlation
40센티미터() is highly overall correlated with 10센티미터() and 9 other fieldsHigh correlation
60센티미터() is highly overall correlated with 10센티미터() and 9 other fieldsHigh correlation
80센티미터() is highly overall correlated with 20센티미터() and 8 other fieldsHigh correlation
평균값() is highly overall correlated with 10센티미터() and 9 other fieldsHigh correlation
10센티미터 편차() is highly overall correlated with 40센티미터() and 7 other fieldsHigh correlation
20센티미터 편차() is highly overall correlated with 40센티미터() and 6 other fieldsHigh correlation
40센티미터 편차() is highly overall correlated with 20센티미터() and 8 other fieldsHigh correlation
60센티미터 편차() is highly overall correlated with 10센티미터() and 8 other fieldsHigh correlation
80센티미터 편차() is highly overall correlated with 40센티미터() and 7 other fieldsHigh correlation
순번() has unique valuesUnique
일자() has unique valuesUnique

Reproduction

Analysis started2024-04-16 15:32:20.595404
Analysis finished2024-04-16 15:32:36.316642
Duration15.72 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
2024-04-17T00:32:36.380735image/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
2024-04-17T00:32:36.507248image/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
2024-04-17T00:32:36.640628image/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
2024-04-17T00:32:36.777076image/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 

Distinct49
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.649
Minimum36.9
Maximum44.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:36.906965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.9
5-th percentile37.195
Q138.475
median39.35
Q340.825
95-th percentile42.51
Maximum44.4
Range7.5
Interquartile range (IQR)2.35

Descriptive statistics

Standard deviation1.7166149
Coefficient of variation (CV)0.043295288
Kurtosis0.17589987
Mean39.649
Median Absolute Deviation (MAD)1.3
Skewness0.5548582
Sum3964.9
Variance2.9467667
MonotonicityNot monotonic
2024-04-17T00:32:37.027589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
40.0 5
 
5.0%
39.3 5
 
5.0%
41.1 5
 
5.0%
40.7 4
 
4.0%
40.2 4
 
4.0%
38.9 4
 
4.0%
39.2 4
 
4.0%
41.2 4
 
4.0%
39.0 3
 
3.0%
37.1 3
 
3.0%
Other values (39) 59
59.0%
ValueCountFrequency (%)
36.9 2
2.0%
37.1 3
3.0%
37.2 3
3.0%
37.3 3
3.0%
37.4 1
 
1.0%
37.5 1
 
1.0%
37.6 2
2.0%
37.7 1
 
1.0%
37.8 1
 
1.0%
37.9 1
 
1.0%
ValueCountFrequency (%)
44.4 1
1.0%
44.3 2
2.0%
43.5 1
1.0%
42.7 1
1.0%
42.5 1
1.0%
42.1 1
1.0%
42.0 1
1.0%
41.9 1
1.0%
41.8 1
1.0%
41.7 2
2.0%

20센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.432
Minimum41.7
Maximum50.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:37.155885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41.7
5-th percentile42.095
Q143.075
median44
Q345.625
95-th percentile47.36
Maximum50.8
Range9.1
Interquartile range (IQR)2.55

Descriptive statistics

Standard deviation1.8867363
Coefficient of variation (CV)0.042463456
Kurtosis1.6947485
Mean44.432
Median Absolute Deviation (MAD)1.25
Skewness1.1352412
Sum4443.2
Variance3.5597737
MonotonicityNot monotonic
2024-04-17T00:32:37.275199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43.7 4
 
4.0%
45.8 4
 
4.0%
43.6 4
 
4.0%
43.9 4
 
4.0%
43.1 3
 
3.0%
42.1 3
 
3.0%
42.7 3
 
3.0%
43.2 3
 
3.0%
45.3 3
 
3.0%
45.9 3
 
3.0%
Other values (43) 66
66.0%
ValueCountFrequency (%)
41.7 1
 
1.0%
41.9 2
2.0%
42.0 2
2.0%
42.1 3
3.0%
42.3 3
3.0%
42.4 2
2.0%
42.5 1
 
1.0%
42.6 3
3.0%
42.7 3
3.0%
42.8 2
2.0%
ValueCountFrequency (%)
50.8 1
1.0%
50.5 1
1.0%
49.9 1
1.0%
49.5 1
1.0%
48.5 1
1.0%
47.3 1
1.0%
47.0 1
1.0%
46.9 1
1.0%
46.7 1
1.0%
46.5 1
1.0%

40센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.771
Minimum32.6
Maximum46.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:37.425865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.6
5-th percentile33.2
Q134.5
median36.85
Q340.9
95-th percentile44.725
Maximum46.2
Range13.6
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation3.7401263
Coefficient of variation (CV)0.099021108
Kurtosis-0.83599874
Mean37.771
Median Absolute Deviation (MAD)2.8
Skewness0.55352341
Sum3777.1
Variance13.988544
MonotonicityNot monotonic
2024-04-17T00:32:37.556675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.9 3
 
3.0%
42.3 3
 
3.0%
33.9 3
 
3.0%
34.6 3
 
3.0%
35.0 3
 
3.0%
33.8 2
 
2.0%
44.7 2
 
2.0%
38.0 2
 
2.0%
36.4 2
 
2.0%
38.4 2
 
2.0%
Other values (61) 75
75.0%
ValueCountFrequency (%)
32.6 1
1.0%
32.8 1
1.0%
32.9 1
1.0%
33.0 1
1.0%
33.2 2
2.0%
33.3 1
1.0%
33.4 2
2.0%
33.5 1
1.0%
33.6 1
1.0%
33.7 2
2.0%
ValueCountFrequency (%)
46.2 1
1.0%
45.5 2
2.0%
45.4 1
1.0%
45.2 1
1.0%
44.7 2
2.0%
44.1 1
1.0%
43.5 1
1.0%
43.3 1
1.0%
43.0 1
1.0%
42.9 1
1.0%

60센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.679
Minimum45
Maximum48.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:37.671447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile45.1
Q145.975
median46.3
Q347.625
95-th percentile48.1
Maximum48.2
Range3.2
Interquartile range (IQR)1.65

Descriptive statistics

Standard deviation0.9771423
Coefficient of variation (CV)0.020933231
Kurtosis-1.3399918
Mean46.679
Median Absolute Deviation (MAD)0.8
Skewness0.14391685
Sum4667.9
Variance0.95480707
MonotonicityNot monotonic
2024-04-17T00:32:37.780969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
46.2 15
15.0%
46.3 11
 
11.0%
47.9 8
 
8.0%
48.1 6
 
6.0%
46.4 6
 
6.0%
47.6 6
 
6.0%
45.5 6
 
6.0%
45.1 5
 
5.0%
45.6 5
 
5.0%
45.7 4
 
4.0%
Other values (15) 28
28.0%
ValueCountFrequency (%)
45.0 1
 
1.0%
45.1 5
 
5.0%
45.4 1
 
1.0%
45.5 6
 
6.0%
45.6 5
 
5.0%
45.7 4
 
4.0%
45.8 2
 
2.0%
45.9 1
 
1.0%
46.0 1
 
1.0%
46.2 15
15.0%
ValueCountFrequency (%)
48.2 4
4.0%
48.1 6
6.0%
48.0 2
 
2.0%
47.9 8
8.0%
47.8 1
 
1.0%
47.7 4
4.0%
47.6 6
6.0%
47.5 3
 
3.0%
47.4 3
 
3.0%
47.3 1
 
1.0%

80센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.583
Minimum29.1
Maximum38.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:37.908201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29.1
5-th percentile29.575
Q130.3
median36.05
Q338.425
95-th percentile38.9
Maximum38.9
Range9.8
Interquartile range (IQR)8.125

Descriptive statistics

Standard deviation4.0251496
Coefficient of variation (CV)0.11639099
Kurtosis-1.9054269
Mean34.583
Median Absolute Deviation (MAD)2.85
Skewness-0.10808954
Sum3458.3
Variance16.201829
MonotonicityNot monotonic
2024-04-17T00:32:38.012426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
38.9 15
15.0%
30.3 12
12.0%
38.2 10
 
10.0%
30.1 8
 
8.0%
38.4 7
 
7.0%
38.7 6
 
6.0%
29.1 5
 
5.0%
30.5 4
 
4.0%
30.2 4
 
4.0%
38.3 3
 
3.0%
Other values (23) 26
26.0%
ValueCountFrequency (%)
29.1 5
5.0%
29.6 1
 
1.0%
30.1 8
8.0%
30.2 4
 
4.0%
30.3 12
12.0%
30.4 2
 
2.0%
30.5 4
 
4.0%
30.6 1
 
1.0%
30.7 1
 
1.0%
30.9 2
 
2.0%
ValueCountFrequency (%)
38.9 15
15.0%
38.8 2
 
2.0%
38.7 6
 
6.0%
38.6 1
 
1.0%
38.5 1
 
1.0%
38.4 7
7.0%
38.3 3
 
3.0%
38.2 10
10.0%
38.1 1
 
1.0%
37.8 1
 
1.0%

평균값()
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.626
Minimum37.2
Maximum45.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:38.128292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.2
5-th percentile37.8
Q138.675
median40.35
Q342.6
95-th percentile44.205
Maximum45.3
Range8.1
Interquartile range (IQR)3.925

Descriptive statistics

Standard deviation2.2215937
Coefficient of variation (CV)0.054684039
Kurtosis-1.0990153
Mean40.626
Median Absolute Deviation (MAD)1.95
Skewness0.32621385
Sum4062.6
Variance4.9354788
MonotonicityNot monotonic
2024-04-17T00:32:38.258132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.0 4
 
4.0%
41.8 4
 
4.0%
37.8 4
 
4.0%
43.1 3
 
3.0%
39.0 3
 
3.0%
39.3 3
 
3.0%
43.2 3
 
3.0%
38.6 3
 
3.0%
38.3 3
 
3.0%
41.3 3
 
3.0%
Other values (49) 67
67.0%
ValueCountFrequency (%)
37.2 1
 
1.0%
37.4 1
 
1.0%
37.6 2
2.0%
37.8 4
4.0%
37.9 1
 
1.0%
38.0 4
4.0%
38.1 2
2.0%
38.2 1
 
1.0%
38.3 3
3.0%
38.4 2
2.0%
ValueCountFrequency (%)
45.3 2
2.0%
45.2 1
1.0%
45.1 1
1.0%
44.3 1
1.0%
44.2 1
1.0%
44.1 1
1.0%
44.0 1
1.0%
43.7 1
1.0%
43.5 2
2.0%
43.3 1
1.0%

10센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.977
Minimum-3.2
Maximum3.3
Zeros1
Zeros (%)1.0%
Negative67
Negative (%)67.0%
Memory size1.0 KiB
2024-04-17T00:32:38.376301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.2
5-th percentile-3.005
Q1-2.3
median-1.15
Q30.225
95-th percentile1.405
Maximum3.3
Range6.5
Interquartile range (IQR)2.525

Descriptive statistics

Standard deviation1.5002932
Coefficient of variation (CV)-1.5356123
Kurtosis-0.70664014
Mean-0.977
Median Absolute Deviation (MAD)1.25
Skewness0.417923
Sum-97.7
Variance2.2508798
MonotonicityNot monotonic
2024-04-17T00:32:38.724901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
-2.1 6
 
6.0%
-2.6 4
 
4.0%
-2.4 4
 
4.0%
0.2 4
 
4.0%
-2.5 4
 
4.0%
0.3 4
 
4.0%
0.4 3
 
3.0%
-2.3 3
 
3.0%
-1.4 3
 
3.0%
-1.6 3
 
3.0%
Other values (39) 62
62.0%
ValueCountFrequency (%)
-3.2 2
2.0%
-3.1 3
3.0%
-3.0 2
2.0%
-2.9 2
2.0%
-2.8 1
 
1.0%
-2.7 1
 
1.0%
-2.6 4
4.0%
-2.5 4
4.0%
-2.4 4
4.0%
-2.3 3
3.0%
ValueCountFrequency (%)
3.3 1
1.0%
2.4 1
1.0%
1.7 1
1.0%
1.6 1
1.0%
1.5 1
1.0%
1.4 2
2.0%
1.2 2
2.0%
1.1 1
1.0%
1.0 1
1.0%
0.9 2
2.0%

20센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.806
Minimum2.4
Maximum6.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:38.838618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4
5-th percentile2.5
Q12.8
median4
Q34.525
95-th percentile5.5
Maximum6.2
Range3.8
Interquartile range (IQR)1.725

Descriptive statistics

Standard deviation1.0345369
Coefficient of variation (CV)0.27181738
Kurtosis-1.1069326
Mean3.806
Median Absolute Deviation (MAD)1
Skewness0.27938733
Sum380.6
Variance1.0702667
MonotonicityNot monotonic
2024-04-17T00:32:38.949288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2.6 12
 
12.0%
2.5 6
 
6.0%
4.4 6
 
6.0%
4.1 5
 
5.0%
4.0 5
 
5.0%
4.3 5
 
5.0%
3.1 5
 
5.0%
2.7 4
 
4.0%
3.0 4
 
4.0%
2.8 4
 
4.0%
Other values (24) 44
44.0%
ValueCountFrequency (%)
2.4 2
 
2.0%
2.5 6
6.0%
2.6 12
12.0%
2.7 4
 
4.0%
2.8 4
 
4.0%
2.9 3
 
3.0%
3.0 4
 
4.0%
3.1 5
5.0%
3.2 1
 
1.0%
3.3 1
 
1.0%
ValueCountFrequency (%)
6.2 1
 
1.0%
5.9 1
 
1.0%
5.7 2
2.0%
5.5 3
3.0%
5.4 1
 
1.0%
5.3 3
3.0%
5.2 1
 
1.0%
5.1 1
 
1.0%
5.0 3
3.0%
4.9 2
2.0%

40센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.855
Minimum-5.9
Maximum1.2
Zeros0
Zeros (%)0.0%
Negative92
Negative (%)92.0%
Memory size1.0 KiB
2024-04-17T00:32:39.076680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.9
5-th percentile-5
Q1-4.2
median-3.2
Q3-1.65
95-th percentile0.305
Maximum1.2
Range7.1
Interquartile range (IQR)2.55

Descriptive statistics

Standard deviation1.6625631
Coefficient of variation (CV)-0.58233385
Kurtosis-0.37504319
Mean-2.855
Median Absolute Deviation (MAD)1
Skewness0.60071593
Sum-285.5
Variance2.7641162
MonotonicityNot monotonic
2024-04-17T00:32:39.201053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
-4.2 7
 
7.0%
-3.2 7
 
7.0%
-3.1 6
 
6.0%
-4.9 5
 
5.0%
-5.0 5
 
5.0%
-2.9 5
 
5.0%
-1.5 4
 
4.0%
-3.3 4
 
4.0%
-3.5 4
 
4.0%
-0.9 3
 
3.0%
Other values (35) 50
50.0%
ValueCountFrequency (%)
-5.9 1
 
1.0%
-5.7 1
 
1.0%
-5.0 5
5.0%
-4.9 5
5.0%
-4.8 2
 
2.0%
-4.7 1
 
1.0%
-4.6 1
 
1.0%
-4.5 2
 
2.0%
-4.3 2
 
2.0%
-4.2 7
7.0%
ValueCountFrequency (%)
1.2 1
1.0%
0.9 2
2.0%
0.6 1
1.0%
0.4 1
1.0%
0.3 1
1.0%
0.2 1
1.0%
0.1 1
1.0%
-0.2 1
1.0%
-0.3 1
1.0%
-0.4 1
1.0%

60센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.053
Minimum2.2
Maximum8.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:39.345133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3.78
Q15.1
median6.1
Q37.225
95-th percentile7.905
Maximum8.6
Range6.4
Interquartile range (IQR)2.125

Descriptive statistics

Standard deviation1.4127454
Coefficient of variation (CV)0.2333959
Kurtosis-0.095440491
Mean6.053
Median Absolute Deviation (MAD)1.1
Skewness-0.51682424
Sum605.3
Variance1.9958495
MonotonicityNot monotonic
2024-04-17T00:32:39.524635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
7.7 5
 
5.0%
5.7 5
 
5.0%
4.5 5
 
5.0%
5.6 5
 
5.0%
7.1 4
 
4.0%
6.8 4
 
4.0%
5.3 4
 
4.0%
4.9 4
 
4.0%
7.0 3
 
3.0%
5.4 3
 
3.0%
Other values (36) 58
58.0%
ValueCountFrequency (%)
2.2 2
 
2.0%
2.7 1
 
1.0%
2.8 1
 
1.0%
3.4 1
 
1.0%
3.8 1
 
1.0%
4.0 1
 
1.0%
4.1 1
 
1.0%
4.4 2
 
2.0%
4.5 5
5.0%
4.6 1
 
1.0%
ValueCountFrequency (%)
8.6 1
 
1.0%
8.4 1
 
1.0%
8.2 1
 
1.0%
8.1 1
 
1.0%
8.0 1
 
1.0%
7.9 2
 
2.0%
7.8 1
 
1.0%
7.7 5
5.0%
7.6 3
3.0%
7.5 3
3.0%

80센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.043
Minimum-9.8
Maximum-2.1
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2024-04-17T00:32:39.649587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.8
5-th percentile-9.01
Q1-8.1
median-6.35
Q3-3.9
95-th percentile-2.4
Maximum-2.1
Range7.7
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation2.2602072
Coefficient of variation (CV)-0.37402071
Kurtosis-1.4653099
Mean-6.043
Median Absolute Deviation (MAD)2
Skewness0.12669582
Sum-604.3
Variance5.1085364
MonotonicityNot monotonic
2024-04-17T00:32:39.779677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-8.1 5
 
5.0%
-3.9 5
 
5.0%
-8.9 4
 
4.0%
-8.3 4
 
4.0%
-7.8 4
 
4.0%
-3.4 4
 
4.0%
-9.2 3
 
3.0%
-4.8 3
 
3.0%
-3.5 3
 
3.0%
-2.4 3
 
3.0%
Other values (43) 62
62.0%
ValueCountFrequency (%)
-9.8 1
 
1.0%
-9.3 1
 
1.0%
-9.2 3
3.0%
-9.0 2
2.0%
-8.9 4
4.0%
-8.8 1
 
1.0%
-8.7 2
2.0%
-8.5 3
3.0%
-8.4 1
 
1.0%
-8.3 4
4.0%
ValueCountFrequency (%)
-2.1 1
 
1.0%
-2.2 1
 
1.0%
-2.3 1
 
1.0%
-2.4 3
3.0%
-2.8 1
 
1.0%
-2.9 2
2.0%
-3.0 1
 
1.0%
-3.2 1
 
1.0%
-3.3 1
 
1.0%
-3.4 4
4.0%

Interactions

2024-04-17T00:32:34.822129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:20.903751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.042739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.230557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.305389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.538078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.666787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.751756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.736737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.125503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.157375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.220924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.444038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.891163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:20.967350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.145656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.308421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.371985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.627479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.775880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.818208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.816351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.196583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.233135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.294264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.515074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.992052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.047430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.232904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.387934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.447763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.717894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.864091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.893090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.936828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.275339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.313239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.372457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.596416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.076731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.131935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.318777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.478335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.519685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.820538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.934678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.969207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.018804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.353247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.399052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.467940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.681926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.172800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.199700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.390153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.554602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.583990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.890267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.007184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.035508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.090998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.426318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.471030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.558666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.753348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.317931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.288923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.520292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.635921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.938556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.975421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.085347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.107486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.173981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.528072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.553292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.637486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.831820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.417434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.378446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.637546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.718112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.010474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.069270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.165716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.185176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.252181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.606069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.630922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.708557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.917449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.524770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.467987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.725955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.797514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.080835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.150972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.241864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.261591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.325423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.673590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.706214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.775609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.008296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.629840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.571470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.813191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.882863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.158279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.235929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.342453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.342991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.406384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.756905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.793003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.853761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.098172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.714729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.681111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.891528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.964060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.232049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.342895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.419664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.441254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.489776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.828353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.890106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.002959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.186610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.802016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.772846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:22.977168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.046397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.306298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.424472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.501381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.529311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.579095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.910488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.974069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.180362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.285628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.889644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.860505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.069378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.128852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.384397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.509066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.582734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.601713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:29.949190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.995210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.057900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.273329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.388239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:35.980869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:21.950104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:23.145639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:24.212041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:25.456223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:26.581935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:27.663294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:28.666653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:30.038292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:31.075532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:32.134861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:33.351361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:34.471949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T00:32:39.877635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번()일자()10센티미터()20센티미터()40센티미터()60센티미터()80센티미터()평균값()10센티미터 편차()20센티미터 편차()40센티미터 편차()60센티미터 편차()80센티미터 편차()
순번()1.0000.9480.5800.5460.7610.8740.6400.7030.7550.6830.8160.7480.651
일자()0.9481.0000.5670.5460.6680.7170.5030.6240.6080.5370.7120.7400.570
10센티미터()0.5800.5671.0000.9190.7290.7440.4770.8940.8240.6380.7460.8520.783
20센티미터()0.5460.5460.9191.0000.8690.6840.1480.9250.6190.7230.8010.9500.886
40센티미터()0.7610.6680.7290.8691.0000.8480.6930.9320.7260.7550.9070.9090.896
60센티미터()0.8740.7170.7440.6840.8481.0000.7690.8320.8060.7480.7940.7190.774
80센티미터()0.6400.5030.4770.1480.6930.7691.0000.7070.6370.6870.5720.5830.671
평균값()0.7030.6240.8940.9250.9320.8320.7071.0000.7290.7800.8490.9420.919
10센티미터 편차()0.7550.6080.8240.6190.7260.8060.6370.7291.0000.9080.8430.7450.840
20센티미터 편차()0.6830.5370.6380.7230.7550.7480.6870.7800.9081.0000.7410.7990.902
40센티미터 편차()0.8160.7120.7460.8010.9070.7940.5720.8490.8430.7411.0000.8310.852
60센티미터 편차()0.7480.7400.8520.9500.9090.7190.5830.9420.7450.7990.8311.0000.919
80센티미터 편차()0.6510.5700.7830.8860.8960.7740.6710.9190.8400.9020.8520.9191.000
2024-04-17T00:32:40.011028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번()일자()10센티미터()20센티미터()40센티미터()60센티미터()80센티미터()평균값()10센티미터 편차()20센티미터 편차()40센티미터 편차()60센티미터 편차()80센티미터 편차()
순번()1.0001.0000.231-0.004-0.2520.2170.038-0.0780.3890.124-0.4340.258-0.186
일자()1.0001.0000.231-0.004-0.2520.2170.038-0.0780.3890.124-0.4340.258-0.186
10센티미터()0.2310.2311.0000.9130.5900.6540.4550.7460.0190.0380.383-0.705-0.014
20센티미터()-0.004-0.0040.9131.0000.8150.7830.6370.906-0.312-0.1950.640-0.8750.233
40센티미터()-0.252-0.2520.5900.8151.0000.8150.8630.958-0.735-0.5990.918-0.9380.625
60센티미터()0.2170.2170.6540.7830.8151.0000.8660.885-0.598-0.6050.653-0.7310.562
80센티미터()0.0380.0380.4550.6370.8630.8661.0000.863-0.765-0.7840.717-0.7900.802
평균값()-0.078-0.0780.7460.9060.9580.8850.8631.000-0.628-0.5300.794-0.9510.573
10센티미터 편차()0.3890.3890.019-0.312-0.735-0.598-0.765-0.6281.0000.883-0.7340.600-0.873
20센티미터 편차()0.1240.1240.038-0.195-0.599-0.605-0.784-0.5300.8831.000-0.5420.471-0.914
40센티미터 편차()-0.434-0.4340.3830.6400.9180.6530.7170.794-0.734-0.5421.000-0.7860.502
60센티미터 편차()0.2580.258-0.705-0.875-0.938-0.731-0.790-0.9510.6000.471-0.7861.000-0.563
80센티미터 편차()-0.186-0.186-0.0140.2330.6250.5620.8020.573-0.873-0.9140.502-0.5631.000

Missing values

2024-04-17T00:32:36.108204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T00:32:36.257457image/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

순번()일자()10센티미터()20센티미터()40센티미터()60센티미터()80센티미터()평균값()10센티미터 편차()20센티미터 편차()40센티미터 편차()60센티미터 편차()80센티미터 편차()
012020010138.443.733.845.129.138.00.45.7-4.27.1-8.9
122020010238.043.133.645.129.137.80.25.3-4.27.3-8.7
232020010337.742.633.445.129.137.60.15.0-4.27.5-8.5
342020010437.542.333.245.129.137.40.14.9-4.27.7-8.3
452020010537.242.032.945.029.137.20.04.8-4.37.8-8.1
562020010638.942.833.845.129.638.00.94.8-4.27.1-8.4
672020010744.350.545.547.438.245.2-0.95.30.32.2-7.0
782020010844.350.845.547.538.245.3-1.05.50.22.2-7.1
892020010941.248.545.447.638.244.2-3.04.31.23.4-6.0
9102020011039.946.243.547.638.243.1-3.23.10.44.5-4.9
순번()일자()10센티미터()20센티미터()40센티미터()60센티미터()80센티미터()평균값()10센티미터 편차()20센티미터 편차()40센티미터 편차()60센티미터 편차()80센티미터 편차()
90912020033140.844.734.546.330.339.31.55.4-4.87.0-9.0
91922020040140.644.534.446.430.339.21.45.3-4.87.2-8.9
92932020040240.044.034.146.430.339.01.05.0-4.97.4-8.7
93942020040339.743.733.946.430.338.80.94.9-4.97.6-8.5
94952020040439.443.433.746.330.338.60.84.8-4.97.7-8.3
95962020040539.043.033.446.330.338.40.64.6-5.07.9-8.1
96972020040638.542.633.246.230.238.10.44.5-4.98.1-7.9
97982020040738.242.433.046.230.238.00.24.4-5.08.2-7.8
98992020040837.942.132.846.230.137.80.14.3-5.08.4-7.7
991002020040937.341.732.646.230.137.6-0.34.1-5.08.6-7.5