Overview

Dataset statistics

Number of variables6
Number of observations429
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 KiB
Average record size in memory54.3 B

Variable types

Numeric6

Alerts

SPOT_LO is highly overall correlated with SPOT_AL and 1 other fieldsHigh correlation
SPOT_AL is highly overall correlated with SPOT_LOHigh correlation
GRDNT_RT is highly overall correlated with GRDNT_VALHigh correlation
GRDNT_VAL is highly overall correlated with GRDNT_RTHigh correlation
SLANT_DRC is highly overall correlated with SPOT_LOHigh correlation
SPOT_LO has unique valuesUnique
SPOT_LA has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:38:26.957242
Analysis finished2024-03-13 12:38:33.621875
Duration6.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SPOT_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct429
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57806
Minimum126.57417
Maximum126.57812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:33.762749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.57417
5-th percentile126.57805
Q1126.57807
median126.57808
Q3126.57809
95-th percentile126.57811
Maximum126.57812
Range0.0039469643
Interquartile range (IQR)2.4499638 × 10-5

Descriptive statistics

Standard deviation0.00026686662
Coefficient of variation (CV)2.1083166 × 10-6
Kurtosis210.07508
Mean126.57806
Median Absolute Deviation (MAD)1.3235366 × 10-5
Skewness-14.496196
Sum54301.988
Variance7.1217795 × 10-8
MonotonicityNot monotonic
2024-03-13T21:38:34.035770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.574174957153 1
 
0.2%
126.578046354967 1
 
0.2%
126.57811522659 1
 
0.2%
126.578113004614 1
 
0.2%
126.578110782637 1
 
0.2%
126.578108560661 1
 
0.2%
126.578106338684 1
 
0.2%
126.578104116707 1
 
0.2%
126.578101894731 1
 
0.2%
126.578099672754 1
 
0.2%
Other values (419) 419
97.7%
ValueCountFrequency (%)
126.574174957153 1
0.2%
126.574174966891 1
0.2%
126.578037496011 1
0.2%
126.578039708338 1
0.2%
126.578039717988 1
0.2%
126.578041920664 1
0.2%
126.578041930314 1
0.2%
126.578041939964 1
0.2%
126.57804413299 1
0.2%
126.57804414264 1
0.2%
ValueCountFrequency (%)
126.578121921465 1
0.2%
126.578119699489 1
0.2%
126.578119689841 1
0.2%
126.578117477513 1
0.2%
126.578117467864 1
0.2%
126.578117458216 1
0.2%
126.578115255536 1
0.2%
126.578115245888 1
0.2%
126.578115236239 1
0.2%
126.57811522659 1
0.2%

SPOT_LA
Real number (ℝ)

UNIQUE 

Distinct429
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.136971
Minimum36.133396
Maximum36.137013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:34.315612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.133396
5-th percentile36.136975
Q136.13698
median36.136986
Q336.136993
95-th percentile36.137005
Maximum36.137013
Range0.0036168385
Interquartile range (IQR)1.278884 × 10-5

Descriptive statistics

Standard deviation0.00024505005
Coefficient of variation (CV)6.7811453 × 10-6
Kurtosis211.37806
Mean36.136971
Median Absolute Deviation (MAD)7.1625458 × 10-6
Skewness-14.563237
Sum15502.761
Variance6.0049527 × 10-8
MonotonicityNot monotonic
2024-03-13T21:38:34.539398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.1333978756743 1
 
0.2%
36.136980351618 1
 
0.2%
36.1369823966374 1
 
0.2%
36.1369823888108 1
 
0.2%
36.1369823809843 1
 
0.2%
36.1369823731576 1
 
0.2%
36.136982365331 1
 
0.2%
36.1369823575042 1
 
0.2%
36.1369823496775 1
 
0.2%
36.1369823418507 1
 
0.2%
Other values (419) 419
97.7%
ValueCountFrequency (%)
36.1333960732968 1
0.2%
36.1333978756743 1
0.2%
36.1369749131746 1
0.2%
36.1369749210026 1
0.2%
36.1369749288305 1
0.2%
36.1369749366584 1
0.2%
36.1369749444862 1
0.2%
36.136974952314 1
0.2%
36.1369749601417 1
0.2%
36.1369749679694 1
0.2%
ValueCountFrequency (%)
36.1370129118213 1
0.2%
36.1370111172712 1
0.2%
36.137011109444 1
0.2%
36.1370111016168 1
0.2%
36.1370093148939 1
0.2%
36.1370093070668 1
0.2%
36.1370092992395 1
0.2%
36.1370092914123 1
0.2%
36.1370075203438 1
0.2%
36.1370075125167 1
0.2%

SPOT_AL
Real number (ℝ)

HIGH CORRELATION 

Distinct280
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9097599
Minimum1.138
Maximum2.146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:34.737902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.138
5-th percentile1.6198
Q11.832
median1.939
Q32.02
95-th percentile2.0902
Maximum2.146
Range1.008
Interquartile range (IQR)0.188

Descriptive statistics

Standard deviation0.14574196
Coefficient of variation (CV)0.076314286
Kurtosis2.7641906
Mean1.9097599
Median Absolute Deviation (MAD)0.089
Skewness-1.220515
Sum819.287
Variance0.02124072
MonotonicityNot monotonic
2024-03-13T21:38:35.052321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.879 7
 
1.6%
2.041 5
 
1.2%
1.964 5
 
1.2%
1.939 5
 
1.2%
1.972 4
 
0.9%
1.894 4
 
0.9%
1.92 4
 
0.9%
1.979 4
 
0.9%
1.998 4
 
0.9%
1.988 4
 
0.9%
Other values (270) 383
89.3%
ValueCountFrequency (%)
1.138 1
0.2%
1.148 1
0.2%
1.533 1
0.2%
1.549 1
0.2%
1.564 1
0.2%
1.565 1
0.2%
1.575 1
0.2%
1.578 1
0.2%
1.582 1
0.2%
1.584 1
0.2%
ValueCountFrequency (%)
2.146 1
0.2%
2.144 1
0.2%
2.134 1
0.2%
2.125 1
0.2%
2.119 2
0.5%
2.111 1
0.2%
2.108 1
0.2%
2.106 1
0.2%
2.105 1
0.2%
2.103 1
0.2%

GRDNT_RT
Real number (ℝ)

HIGH CORRELATION 

Distinct343
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9012587
Minimum0.59
Maximum23.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:35.255723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.59
5-th percentile4.134
Q17.35
median8.65
Q310.1
95-th percentile14.496
Maximum23.3
Range22.71
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation3.0847851
Coefficient of variation (CV)0.34655606
Kurtosis3.2555441
Mean8.9012587
Median Absolute Deviation (MAD)1.4
Skewness0.92813012
Sum3818.64
Variance9.5158993
MonotonicityNot monotonic
2024-03-13T21:38:35.443875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.18 4
 
0.9%
7.17 3
 
0.7%
7.66 3
 
0.7%
8.65 3
 
0.7%
9.52 3
 
0.7%
9.06 3
 
0.7%
7.25 3
 
0.7%
8.57 3
 
0.7%
6.28 3
 
0.7%
7.71 3
 
0.7%
Other values (333) 398
92.8%
ValueCountFrequency (%)
0.59 1
0.2%
1.08 1
0.2%
1.37 1
0.2%
1.51 1
0.2%
1.81 1
0.2%
2.11 1
0.2%
2.13 1
0.2%
2.16 1
0.2%
2.24 1
0.2%
2.51 1
0.2%
ValueCountFrequency (%)
23.3 1
0.2%
22.3 1
0.2%
21.1 1
0.2%
20.8 1
0.2%
19.85 1
0.2%
19.13 1
0.2%
17.95 1
0.2%
17.57 1
0.2%
17.24 1
0.2%
16.62 1
0.2%

GRDNT_VAL
Real number (ℝ)

HIGH CORRELATION 

Distinct305
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0816783
Minimum0.34
Maximum13.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:35.667645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.34
5-th percentile2.366
Q14.21
median4.95
Q35.77
95-th percentile8.248
Maximum13.11
Range12.77
Interquartile range (IQR)1.56

Descriptive statistics

Standard deviation1.745872
Coefficient of variation (CV)0.34356209
Kurtosis3.1093345
Mean5.0816783
Median Absolute Deviation (MAD)0.8
Skewness0.88433675
Sum2180.04
Variance3.0480691
MonotonicityNot monotonic
2024-03-13T21:38:35.895900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.57 5
 
1.2%
5.53 4
 
0.9%
3.59 4
 
0.9%
5.5 4
 
0.9%
5.44 4
 
0.9%
4.35 3
 
0.7%
5.06 3
 
0.7%
4.95 3
 
0.7%
5.88 3
 
0.7%
4.84 3
 
0.7%
Other values (295) 393
91.6%
ValueCountFrequency (%)
0.34 1
0.2%
0.62 1
0.2%
0.78 1
0.2%
0.87 1
0.2%
1.04 1
0.2%
1.21 1
0.2%
1.22 1
0.2%
1.24 1
0.2%
1.28 1
0.2%
1.44 2
0.5%
ValueCountFrequency (%)
13.11 1
0.2%
12.57 1
0.2%
11.92 1
0.2%
11.75 1
0.2%
11.23 1
0.2%
10.83 1
0.2%
10.17 1
0.2%
9.96 1
0.2%
9.78 1
0.2%
9.44 1
0.2%

SLANT_DRC
Real number (ℝ)

HIGH CORRELATION 

Distinct404
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240.41737
Minimum159.06
Maximum278.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:38:36.492965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum159.06
5-th percentile224.966
Q1232.2
median238.63
Q3245.25
95-th percentile269.382
Maximum278.75
Range119.69
Interquartile range (IQR)13.05

Descriptive statistics

Standard deviation14.500394
Coefficient of variation (CV)0.060313421
Kurtosis5.4483709
Mean240.41737
Median Absolute Deviation (MAD)6.51
Skewness-0.50490329
Sum103139.05
Variance210.26142
MonotonicityNot monotonic
2024-03-13T21:38:36.706798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
244.24 2
 
0.5%
230.6 2
 
0.5%
237.73 2
 
0.5%
242.91 2
 
0.5%
271.3 2
 
0.5%
238.94 2
 
0.5%
239.2 2
 
0.5%
231.54 2
 
0.5%
235.13 2
 
0.5%
231.82 2
 
0.5%
Other values (394) 409
95.3%
ValueCountFrequency (%)
159.06 1
0.2%
160.63 1
0.2%
179.08 1
0.2%
179.56 1
0.2%
194.41 1
0.2%
210.01 1
0.2%
215.45 1
0.2%
216.39 1
0.2%
217.41 1
0.2%
218.3 1
0.2%
ValueCountFrequency (%)
278.75 1
0.2%
277.53 1
0.2%
276.43 1
0.2%
276.32 1
0.2%
275.64 1
0.2%
274.65 1
0.2%
274.46 1
0.2%
274.44 1
0.2%
273.76 1
0.2%
272.85 1
0.2%

Interactions

2024-03-13T21:38:32.304176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:27.257608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:28.327074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.643190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.627791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.398344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:32.443800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:27.445257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:28.932233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.801075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.795953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.574126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:32.652726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:27.638804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.087049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.004054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.943580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.729594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:32.848386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:27.799560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.210984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.133667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.044196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.856092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:33.010588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:27.998088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.352716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.299789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.148606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:32.022211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:33.167371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:28.178291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:29.495498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:30.482612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:31.274702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:38:32.174021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:38:36.845589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.9231.0000.0430.0640.000
SPOT_LA0.9231.0001.0000.0430.0640.000
SPOT_AL1.0001.0001.0000.5040.5160.424
GRDNT_RT0.0430.0430.5041.0000.9990.515
GRDNT_VAL0.0640.0640.5160.9991.0000.515
SLANT_DRC0.0000.0000.4240.5150.5151.000
2024-03-13T21:38:36.994159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.0950.909-0.225-0.225-0.508
SPOT_LA0.0951.0000.430-0.025-0.025-0.021
SPOT_AL0.9090.4301.000-0.215-0.215-0.432
GRDNT_RT-0.225-0.025-0.2151.0001.0000.344
GRDNT_VAL-0.225-0.025-0.2151.0001.0000.345
SLANT_DRC-0.508-0.021-0.4320.3440.3451.000

Missing values

2024-03-13T21:38:33.367873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:38:33.546505image/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

SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
0126.57417536.1333981.1484.612.64252.75
1126.57417536.1333961.1388.064.61261.11
2126.5780836.1370132.0512.161.24210.01
3126.57807736.1370112.0366.943.97224.34
4126.5780836.1370112.0475.032.88232.21
5126.57808236.1370112.0532.111.21233.48
6126.57807536.1370092.08.544.88234.91
7126.57807736.1370092.0211.236.41233.89
8126.5780836.1370092.0398.44.8235.7
9126.57808236.1370092.0493.632.08238.62
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
419126.57807536.1369751.8782.131.22216.39
420126.57807736.1369751.8792.241.28159.06
421126.5780836.1369751.8753.21.83160.63
422126.57808236.1369751.8744.012.3194.41
423126.57808436.1369751.8777.174.1228.42
424126.57808636.1369751.89410.05.71237.71
425126.57808936.1369751.9119.575.47235.73
426126.57809136.1369751.9268.654.94230.69
427126.57809336.1369751.9398.134.65224.95
428126.57809536.1369751.958.694.97226.74