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 5 other fieldsHigh correlation
20센티미터() is highly overall correlated with 10센티미터() and 4 other fieldsHigh correlation
40센티미터() is highly overall correlated with 20센티미터() and 3 other fieldsHigh correlation
60센티미터() is highly overall correlated with 40센티미터() and 2 other fieldsHigh correlation
80센티미터() is highly overall correlated with 40센티미터() and 4 other fieldsHigh correlation
평균값() is highly overall correlated with 10센티미터() and 5 other fieldsHigh correlation
10센티미터 편차() is highly overall correlated with 10센티미터() and 4 other fieldsHigh correlation
20센티미터 편차() is highly overall correlated with 80센티미터() and 2 other fieldsHigh correlation
40센티미터 편차() is highly overall correlated with 10센티미터() and 3 other fieldsHigh correlation
60센티미터 편차() is highly overall correlated with 10센티미터() and 3 other fieldsHigh correlation
80센티미터 편차() is highly overall correlated with 10센티미터() and 4 other fieldsHigh correlation
순번() has unique valuesUnique
일자() has unique valuesUnique
20센티미터 편차() has 3 (3.0%) zerosZeros
60센티미터 편차() has 7 (7.0%) zerosZeros

Reproduction

Analysis started2024-04-16 15:32:42.749205
Analysis finished2024-04-16 15:32:58.459571
Duration15.71 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
2024-04-17T00:32:58.543982image/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
2024-04-17T00:32:58.671993image/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
2024-04-17T00:32:58.802205image/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
2024-04-17T00:32:58.936128image/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 

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.686
Minimum26
Maximum37.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:59.059578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile27.77
Q131.3
median33
Q334.5
95-th percentile35.805
Maximum37.1
Range11.1
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.405004
Coefficient of variation (CV)0.073579026
Kurtosis0.30028074
Mean32.686
Median Absolute Deviation (MAD)1.6
Skewness-0.71464997
Sum3268.6
Variance5.7840444
MonotonicityNot monotonic
2024-04-17T00:32:59.223161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.3 4
 
4.0%
32.3 4
 
4.0%
31.9 4
 
4.0%
35.6 4
 
4.0%
30.8 4
 
4.0%
33.8 3
 
3.0%
32.5 3
 
3.0%
35.1 2
 
2.0%
33.5 2
 
2.0%
30.6 2
 
2.0%
Other values (51) 68
68.0%
ValueCountFrequency (%)
26.0 1
1.0%
26.5 1
1.0%
26.7 1
1.0%
27.2 2
2.0%
27.8 1
1.0%
27.9 1
1.0%
28.7 1
1.0%
28.8 1
1.0%
29.7 2
2.0%
30.1 1
1.0%
ValueCountFrequency (%)
37.1 1
 
1.0%
36.9 1
 
1.0%
36.5 1
 
1.0%
36.2 1
 
1.0%
35.9 1
 
1.0%
35.8 1
 
1.0%
35.6 4
4.0%
35.5 1
 
1.0%
35.3 1
 
1.0%
35.2 1
 
1.0%

20센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.365
Minimum26
Maximum32.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:59.344325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile26.495
Q127.2
median28.15
Q329.3
95-th percentile30.8
Maximum32.6
Range6.6
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation1.4057152
Coefficient of variation (CV)0.049558091
Kurtosis-0.23749361
Mean28.365
Median Absolute Deviation (MAD)1.05
Skewness0.51165084
Sum2836.5
Variance1.9760354
MonotonicityNot monotonic
2024-04-17T00:32:59.461698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
27.7 6
 
6.0%
26.7 5
 
5.0%
29.3 4
 
4.0%
27.4 4
 
4.0%
28.1 4
 
4.0%
26.8 3
 
3.0%
29.6 3
 
3.0%
27.0 3
 
3.0%
27.2 3
 
3.0%
29.2 3
 
3.0%
Other values (36) 62
62.0%
ValueCountFrequency (%)
26.0 1
 
1.0%
26.1 1
 
1.0%
26.3 2
 
2.0%
26.4 1
 
1.0%
26.5 2
 
2.0%
26.6 2
 
2.0%
26.7 5
5.0%
26.8 3
3.0%
26.9 1
 
1.0%
27.0 3
3.0%
ValueCountFrequency (%)
32.6 1
 
1.0%
31.6 1
 
1.0%
31.5 1
 
1.0%
30.8 3
3.0%
30.7 2
2.0%
30.4 2
2.0%
30.3 1
 
1.0%
30.0 2
2.0%
29.9 2
2.0%
29.8 3
3.0%

40센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.944
Minimum22.3
Maximum26.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:59.577328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.3
5-th percentile22.4
Q124.5
median24.9
Q325.6
95-th percentile26.215
Maximum26.8
Range4.5
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.94337884
Coefficient of variation (CV)0.03781987
Kurtosis1.6522909
Mean24.944
Median Absolute Deviation (MAD)0.6
Skewness-0.84446946
Sum2494.4
Variance0.88996364
MonotonicityNot monotonic
2024-04-17T00:32:59.687219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
24.8 9
 
9.0%
24.6 7
 
7.0%
24.2 6
 
6.0%
25.6 5
 
5.0%
25.2 5
 
5.0%
25.1 5
 
5.0%
24.9 5
 
5.0%
24.3 5
 
5.0%
22.3 4
 
4.0%
25.7 4
 
4.0%
Other values (19) 45
45.0%
ValueCountFrequency (%)
22.3 4
4.0%
22.4 2
 
2.0%
24.0 1
 
1.0%
24.1 3
3.0%
24.2 6
6.0%
24.3 5
5.0%
24.4 3
3.0%
24.5 3
3.0%
24.6 7
7.0%
24.7 4
4.0%
ValueCountFrequency (%)
26.8 2
2.0%
26.7 1
 
1.0%
26.6 1
 
1.0%
26.5 1
 
1.0%
26.2 1
 
1.0%
26.1 3
3.0%
26.0 4
4.0%
25.9 2
2.0%
25.8 3
3.0%
25.7 4
4.0%

60센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.867
Minimum23.4
Maximum32.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:32:59.801489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.4
5-th percentile23.595
Q128.2
median28.9
Q329.925
95-th percentile31.11
Maximum32.5
Range9.1
Interquartile range (IQR)1.725

Descriptive statistics

Standard deviation1.7371203
Coefficient of variation (CV)0.060176682
Kurtosis3.624379
Mean28.867
Median Absolute Deviation (MAD)0.8
Skewness-1.4482445
Sum2886.7
Variance3.0175869
MonotonicityNot monotonic
2024-04-17T00:32:59.915318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
29.0 6
 
6.0%
28.7 5
 
5.0%
28.0 5
 
5.0%
28.3 5
 
5.0%
27.9 4
 
4.0%
28.6 4
 
4.0%
27.8 4
 
4.0%
28.5 4
 
4.0%
30.8 4
 
4.0%
30.1 3
 
3.0%
Other values (30) 56
56.0%
ValueCountFrequency (%)
23.4 3
3.0%
23.5 2
 
2.0%
23.6 1
 
1.0%
27.7 2
 
2.0%
27.8 4
4.0%
27.9 4
4.0%
28.0 5
5.0%
28.1 3
3.0%
28.2 3
3.0%
28.3 5
5.0%
ValueCountFrequency (%)
32.5 1
 
1.0%
32.0 1
 
1.0%
31.6 1
 
1.0%
31.4 1
 
1.0%
31.3 1
 
1.0%
31.1 1
 
1.0%
31.0 1
 
1.0%
30.9 1
 
1.0%
30.8 4
4.0%
30.6 1
 
1.0%

80센티미터()
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.645
Minimum27.1
Maximum36.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:33:00.061243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.1
5-th percentile27.3
Q131.9
median32.7
Q333.725
95-th percentile35.015
Maximum36.1
Range9
Interquartile range (IQR)1.825

Descriptive statistics

Standard deviation1.8098147
Coefficient of variation (CV)0.055439262
Kurtosis2.8790926
Mean32.645
Median Absolute Deviation (MAD)0.9
Skewness-1.3014003
Sum3264.5
Variance3.2754293
MonotonicityNot monotonic
2024-04-17T00:33:00.189787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
31.9 6
 
6.0%
32.1 6
 
6.0%
32.2 5
 
5.0%
33.7 5
 
5.0%
32.9 4
 
4.0%
31.7 4
 
4.0%
32.3 4
 
4.0%
32.7 4
 
4.0%
33.1 4
 
4.0%
31.5 4
 
4.0%
Other values (33) 54
54.0%
ValueCountFrequency (%)
27.1 1
 
1.0%
27.2 3
3.0%
27.3 2
2.0%
29.7 1
 
1.0%
31.3 1
 
1.0%
31.4 1
 
1.0%
31.5 4
4.0%
31.6 2
2.0%
31.7 4
4.0%
31.8 3
3.0%
ValueCountFrequency (%)
36.1 1
1.0%
36.0 1
1.0%
35.4 2
2.0%
35.3 1
1.0%
35.0 2
2.0%
34.9 1
1.0%
34.8 1
1.0%
34.7 2
2.0%
34.5 2
2.0%
34.4 1
1.0%

평균값()
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.499
Minimum26
Maximum32.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T00:33:00.332453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile26.5
Q128.775
median29.6
Q330.325
95-th percentile31.5
Maximum32.6
Range6.6
Interquartile range (IQR)1.55

Descriptive statistics

Standard deviation1.3298056
Coefficient of variation (CV)0.045079683
Kurtosis0.66704572
Mean29.499
Median Absolute Deviation (MAD)0.8
Skewness-0.49021452
Sum2949.9
Variance1.7683828
MonotonicityNot monotonic
2024-04-17T00:33:00.461592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
29.6 8
 
8.0%
29.2 5
 
5.0%
29.4 5
 
5.0%
29.8 5
 
5.0%
29.3 4
 
4.0%
28.6 4
 
4.0%
30.1 4
 
4.0%
30.6 3
 
3.0%
30.3 3
 
3.0%
29.0 3
 
3.0%
Other values (34) 56
56.0%
ValueCountFrequency (%)
26.0 1
1.0%
26.1 1
1.0%
26.2 1
1.0%
26.3 1
1.0%
26.5 2
2.0%
27.3 1
1.0%
27.5 1
1.0%
27.6 1
1.0%
27.8 2
2.0%
28.0 1
1.0%
ValueCountFrequency (%)
32.6 1
 
1.0%
32.4 1
 
1.0%
32.3 1
 
1.0%
31.5 3
3.0%
31.3 1
 
1.0%
31.2 1
 
1.0%
31.1 1
 
1.0%
31.0 1
 
1.0%
30.9 3
3.0%
30.8 3
3.0%

10센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.187
Minimum-1.3
Maximum6.4
Zeros0
Zeros (%)0.0%
Negative7
Negative (%)7.0%
Memory size1.0 KiB
2024-04-17T00:33:00.607841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.3
5-th percentile-0.22
Q12.3
median3.05
Q34.425
95-th percentile5.62
Maximum6.4
Range7.7
Interquartile range (IQR)2.125

Descriptive statistics

Standard deviation1.7203274
Coefficient of variation (CV)0.53979522
Kurtosis0.083923624
Mean3.187
Median Absolute Deviation (MAD)1
Skewness-0.43863604
Sum318.7
Variance2.9595263
MonotonicityNot monotonic
2024-04-17T00:33:00.734005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2.7 7
 
7.0%
2.8 5
 
5.0%
6.0 4
 
4.0%
3.3 4
 
4.0%
5.4 4
 
4.0%
2.3 3
 
3.0%
2.1 3
 
3.0%
4.7 3
 
3.0%
4.3 3
 
3.0%
5.6 3
 
3.0%
Other values (37) 61
61.0%
ValueCountFrequency (%)
-1.3 1
1.0%
-1.0 1
1.0%
-0.9 1
1.0%
-0.6 2
2.0%
-0.2 2
2.0%
0.4 2
2.0%
1.0 1
1.0%
1.1 1
1.0%
1.4 1
1.0%
1.6 2
2.0%
ValueCountFrequency (%)
6.4 1
 
1.0%
6.0 4
4.0%
5.6 3
3.0%
5.5 1
 
1.0%
5.4 4
4.0%
5.3 2
2.0%
5.1 2
2.0%
5.0 3
3.0%
4.8 1
 
1.0%
4.7 3
3.0%

20센티미터 편차()
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.134
Minimum-2.1
Maximum1.5
Zeros3
Zeros (%)3.0%
Negative87
Negative (%)87.0%
Memory size1.0 KiB
2024-04-17T00:33:00.840672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.1
5-th percentile-1.9
Q1-1.7
median-1.45
Q3-0.7
95-th percentile0.3
Maximum1.5
Range3.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.75105582
Coefficient of variation (CV)-0.66230672
Kurtosis0.62104813
Mean-1.134
Median Absolute Deviation (MAD)0.35
Skewness1.1233144
Sum-113.4
Variance0.56408485
MonotonicityNot monotonic
2024-04-17T00:33:00.935337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
-1.7 15
15.0%
-1.6 13
13.0%
-1.9 8
 
8.0%
-1.8 6
 
6.0%
-1.3 6
 
6.0%
-1.5 6
 
6.0%
-1.1 4
 
4.0%
-1.0 4
 
4.0%
-0.6 4
 
4.0%
0.2 3
 
3.0%
Other values (15) 31
31.0%
ValueCountFrequency (%)
-2.1 2
 
2.0%
-1.9 8
8.0%
-1.8 6
 
6.0%
-1.7 15
15.0%
-1.6 13
13.0%
-1.5 6
 
6.0%
-1.4 2
 
2.0%
-1.3 6
 
6.0%
-1.2 3
 
3.0%
-1.1 4
 
4.0%
ValueCountFrequency (%)
1.5 1
 
1.0%
0.6 1
 
1.0%
0.5 2
2.0%
0.3 2
2.0%
0.2 3
3.0%
0.1 1
 
1.0%
0.0 3
3.0%
-0.1 3
3.0%
-0.3 3
3.0%
-0.5 1
 
1.0%

40센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.555
Minimum-5.8
Maximum-2.7
Zeros0
Zeros (%)0.0%
Negative100
Negative (%)100.0%
Memory size1.0 KiB
2024-04-17T00:33:01.381551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.8
5-th percentile-5.5
Q1-5
median-4.7
Q3-4.2
95-th percentile-3.2
Maximum-2.7
Range3.1
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.67335659
Coefficient of variation (CV)-0.14782801
Kurtosis0.22537238
Mean-4.555
Median Absolute Deviation (MAD)0.4
Skewness0.67939027
Sum-455.5
Variance0.45340909
MonotonicityNot monotonic
2024-04-17T00:33:01.507065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
-4.9 10
 
10.0%
-4.7 9
 
9.0%
-4.4 7
 
7.0%
-5.0 7
 
7.0%
-4.2 6
 
6.0%
-4.5 5
 
5.0%
-5.3 5
 
5.0%
-4.8 5
 
5.0%
-4.6 4
 
4.0%
-4.3 4
 
4.0%
Other values (18) 38
38.0%
ValueCountFrequency (%)
-5.8 1
 
1.0%
-5.7 2
 
2.0%
-5.6 1
 
1.0%
-5.5 2
 
2.0%
-5.4 4
 
4.0%
-5.3 5
5.0%
-5.2 3
 
3.0%
-5.1 3
 
3.0%
-5.0 7
7.0%
-4.9 10
10.0%
ValueCountFrequency (%)
-2.7 1
 
1.0%
-2.8 1
 
1.0%
-3.0 2
2.0%
-3.2 2
2.0%
-3.3 2
2.0%
-3.5 2
2.0%
-3.7 2
2.0%
-3.8 3
3.0%
-3.9 3
3.0%
-4.0 1
 
1.0%

60센티미터 편차()
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.632
Minimum-3.1
Maximum0.7
Zeros7
Zeros (%)7.0%
Negative81
Negative (%)81.0%
Memory size1.0 KiB
2024-04-17T00:33:01.628396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.1
5-th percentile-2.605
Q1-1.225
median-0.2
Q3-0.1
95-th percentile0.5
Maximum0.7
Range3.8
Interquartile range (IQR)1.125

Descriptive statistics

Standard deviation0.90552513
Coefficient of variation (CV)-1.4327929
Kurtosis0.14212651
Mean-0.632
Median Absolute Deviation (MAD)0.2
Skewness-1.0594335
Sum-63.2
Variance0.81997576
MonotonicityNot monotonic
2024-04-17T00:33:01.758048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
-0.1 22
22.0%
-0.2 13
13.0%
0.0 7
 
7.0%
-0.3 6
 
6.0%
-0.4 4
 
4.0%
-1.8 4
 
4.0%
0.5 3
 
3.0%
-1.5 3
 
3.0%
0.1 3
 
3.0%
-2.0 3
 
3.0%
Other values (23) 32
32.0%
ValueCountFrequency (%)
-3.1 1
 
1.0%
-2.9 1
 
1.0%
-2.8 1
 
1.0%
-2.7 2
2.0%
-2.6 1
 
1.0%
-2.3 2
2.0%
-2.1 1
 
1.0%
-2.0 3
3.0%
-1.9 1
 
1.0%
-1.8 4
4.0%
ValueCountFrequency (%)
0.7 1
 
1.0%
0.6 2
 
2.0%
0.5 3
 
3.0%
0.4 1
 
1.0%
0.3 1
 
1.0%
0.2 1
 
1.0%
0.1 3
 
3.0%
0.0 7
 
7.0%
-0.1 22
22.0%
-0.2 13
13.0%

80센티미터 편차()
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.146
Minimum-1.4
Maximum4.5
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.0%
Memory size1.0 KiB
2024-04-17T00:33:01.886955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.4
5-th percentile1.095
Q12.4
median3.7
Q34
95-th percentile4.3
Maximum4.5
Range5.9
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.1329251
Coefficient of variation (CV)0.36011604
Kurtosis1.4370269
Mean3.146
Median Absolute Deviation (MAD)0.4
Skewness-1.2488477
Sum314.6
Variance1.2835192
MonotonicityNot monotonic
2024-04-17T00:33:02.002501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3.9 14
 
14.0%
4.0 12
 
12.0%
4.1 6
 
6.0%
3.7 6
 
6.0%
3.8 4
 
4.0%
3.5 4
 
4.0%
4.2 4
 
4.0%
3.0 3
 
3.0%
2.4 3
 
3.0%
4.3 3
 
3.0%
Other values (25) 41
41.0%
ValueCountFrequency (%)
-1.4 1
1.0%
0.6 1
1.0%
0.8 1
1.0%
1.0 2
2.0%
1.1 2
2.0%
1.2 2
2.0%
1.3 1
1.0%
1.5 2
2.0%
1.7 2
2.0%
1.8 2
2.0%
ValueCountFrequency (%)
4.5 1
 
1.0%
4.4 2
 
2.0%
4.3 3
 
3.0%
4.2 4
 
4.0%
4.1 6
6.0%
4.0 12
12.0%
3.9 14
14.0%
3.8 4
 
4.0%
3.7 6
6.0%
3.6 2
 
2.0%

Interactions

2024-04-17T00:32:57.035292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.079365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.152797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.212080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.584881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.580661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.641447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.578739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.611024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.044728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.247488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.479218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.560995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.116610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.154317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.228700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.287933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.656145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.653912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.722518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.654383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.691828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.177086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.333776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.557496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.678516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.208710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.236634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.304145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.368017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.729801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.745456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.793272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.736248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.783199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.263099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.425451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.639859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.762390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.296761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.328819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.373682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.439608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.797443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.815888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.854387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.808261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.853314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.351820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.512181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.713997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.838408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.379119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.415875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.467292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.873734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.868669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.905067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.923141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.879419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.242551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.431528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.603313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.790386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.922310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.452303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.485898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.572232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.945298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.932819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.009137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.985097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.952957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.324327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.517934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.708291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.863416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.011243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.543680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.558606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.639064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.024948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.004266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.075445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.052451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.034514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.427769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.616661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.791115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.941710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.087636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.652489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.658758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.705075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.106178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.079837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.144634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.117676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.112145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.516157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.689672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.862686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.022870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.179134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.749966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.762718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.784011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.191427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.176025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.224532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.188585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.199303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.602044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.772899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.956296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.105989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.288085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.835991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.847068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.861344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.273401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.265104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.307184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.273894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.276453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.691145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.868171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.043430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.191412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.418044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.921552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:43.933600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.935230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.352749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.344092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.384743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.353082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.376974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.783835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:52.961144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.158604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.286412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.516266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:57.995071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.007221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.015315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.430664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.421668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.466745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.429188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.451693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.874334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.055100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.293687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.371516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.603237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:58.079364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:44.084782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:45.117244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:46.509159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:47.501040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:48.560055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:49.509575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:50.537050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:51.962212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:53.167905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:54.399966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:55.453422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:32:56.684647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T00:33:02.114620image/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()1.0000.9480.6200.5610.7140.7950.7710.7840.7360.7350.6800.8240.620
일자()0.9481.0000.4610.2490.4590.5400.6050.5460.5790.5920.5940.5160.228
10센티미터()0.6200.4611.0000.8900.5990.6980.6130.8790.9330.6000.9230.8760.551
20센티미터()0.5610.2490.8901.0000.7450.7740.7870.8860.7960.7830.7680.7670.750
40센티미터()0.7140.4590.5990.7451.0000.8150.8900.8340.5900.6800.5440.7050.787
60센티미터()0.7950.5400.6980.7740.8151.0000.8550.9070.6540.6780.6940.7450.603
80센티미터()0.7710.6050.6130.7870.8900.8551.0000.8170.6940.8190.6220.7510.891
평균값()0.7840.5460.8790.8860.8340.9070.8171.0000.8590.6510.8670.8630.556
10센티미터 편차()0.7360.5790.9330.7960.5900.6540.6940.8591.0000.6600.9190.9140.684
20센티미터 편차()0.7350.5920.6000.7830.6800.6780.8190.6510.6601.0000.5120.8100.835
40센티미터 편차()0.6800.5940.9230.7680.5440.6940.6220.8670.9190.5121.0000.8170.408
60센티미터 편차()0.8240.5160.8760.7670.7050.7450.7510.8630.9140.8100.8171.0000.828
80센티미터 편차()0.6200.2280.5510.7500.7870.6030.8910.5560.6840.8350.4080.8281.000
2024-04-17T00:33:02.259350image/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()1.0001.000-0.1940.0590.3230.0710.025-0.009-0.4020.1310.3200.2930.152
일자()1.0001.000-0.1940.0590.3230.0710.025-0.009-0.4020.1310.3200.2930.152
10센티미터()-0.194-0.1941.0000.8710.4540.2500.1270.8020.8210.266-0.809-0.655-0.619
20센티미터()0.0590.0590.8711.0000.7420.4610.2890.9060.5220.297-0.673-0.401-0.455
40센티미터()0.3230.3230.4540.7421.0000.7950.5900.8260.0020.024-0.2790.100-0.037
60센티미터()0.0710.0710.2500.4610.7951.0000.9240.742-0.207-0.474-0.4010.3590.329
80센티미터()0.0250.0250.1270.2890.5900.9241.0000.610-0.299-0.656-0.4580.4250.512
평균값()-0.009-0.0090.8020.9060.8260.7420.6101.0000.383-0.055-0.742-0.208-0.205
10센티미터 편차()-0.402-0.4020.8210.5220.002-0.207-0.2990.3831.0000.465-0.562-0.910-0.845
20센티미터 편차()0.1310.1310.2660.2970.024-0.474-0.656-0.0550.4651.0000.175-0.521-0.710
40센티미터 편차()0.3200.320-0.809-0.673-0.279-0.401-0.458-0.742-0.5620.1751.0000.3660.201
60센티미터 편차()0.2930.293-0.655-0.4010.1000.3590.425-0.208-0.910-0.5210.3661.0000.875
80센티미터 편차()0.1520.152-0.619-0.455-0.0370.3290.512-0.205-0.845-0.7100.2010.8751.000

Missing values

2024-04-17T00:32:58.202803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T00:32:58.385640image/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()
012020010132.526.722.423.627.326.56.00.2-4.1-2.90.8
122020010231.926.622.423.527.326.35.60.3-3.9-2.81.0
232020010331.526.422.323.527.226.25.30.2-3.9-2.71.0
342020010431.426.322.323.427.226.15.30.2-3.8-2.71.1
452020010531.026.122.323.427.226.05.00.1-3.7-2.61.2
562020010632.926.822.323.427.126.56.40.3-4.2-3.10.6
672020010737.132.626.729.229.731.16.01.5-4.4-1.9-1.4
782020010836.231.526.832.536.132.63.6-1.1-5.8-0.13.5
892020010934.629.926.131.435.431.53.1-1.6-5.4-0.13.9
9102020011033.629.125.730.835.030.82.8-1.7-5.10.04.2
순번()일자()10센티미터()20센티미터()40센티미터()60센티미터()80센티미터()평균값()10센티미터 편차()20센티미터 편차()40센티미터 편차()60센티미터 편차()80센티미터 편차()
90912020033133.129.225.728.932.129.83.3-0.6-4.1-0.92.3
91922020040132.328.925.629.032.229.62.7-0.7-4.0-0.62.6
92932020040231.428.425.529.032.329.32.1-0.9-3.8-0.33.0
93942020040330.628.125.328.932.329.01.6-0.9-3.7-0.13.3
94952020040429.727.725.228.732.228.71.0-1.0-3.50.03.5
95962020040528.827.425.128.632.228.40.4-1.0-3.30.23.8
96972020040627.927.024.928.532.128.1-0.2-1.1-3.20.44.0
97982020040727.226.724.828.331.927.8-0.6-1.1-3.00.54.1
98992020040826.526.524.728.131.827.5-1.0-1.0-2.80.64.3
991002020040926.026.024.628.031.727.3-1.3-1.3-2.70.74.4