Overview

Dataset statistics

Number of variables6
Number of observations341
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.1 KiB
Average record size in memory54.4 B

Variable types

Numeric6

Alerts

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

Reproduction

Analysis started2024-03-13 12:27:55.005658
Analysis finished2024-03-13 12:28:05.514495
Duration10.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SPOT_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct341
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.32742
Minimum126.32729
Maximum126.32749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:05.709848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.32729
5-th percentile126.32732
Q1126.32739
median126.32743
Q3126.32747
95-th percentile126.32749
Maximum126.32749
Range0.0002053718
Interquartile range (IQR)7.81112 × 10-5

Descriptive statistics

Standard deviation5.2481368 × 10-5
Coefficient of variation (CV)4.1543924 × 10-7
Kurtosis-0.48391242
Mean126.32742
Median Absolute Deviation (MAD)3.79393 × 10-5
Skewness-0.65151199
Sum43077.651
Variance2.754294 × 10-9
MonotonicityNot monotonic
2024-03-13T21:28:06.146482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.3274719509 1
 
0.3%
126.327458633 1
 
0.3%
126.3274764941 1
 
0.3%
126.3274742615 1
 
0.3%
126.3274720288 1
 
0.3%
126.3274697962 1
 
0.3%
126.3274675636 1
 
0.3%
126.3274653309 1
 
0.3%
126.3274630983 1
 
0.3%
126.3274608656 1
 
0.3%
Other values (331) 331
97.1%
ValueCountFrequency (%)
126.3272867508 1
0.3%
126.3272889835 1
0.3%
126.3272912161 1
0.3%
126.3272934487 1
0.3%
126.3272956814 1
0.3%
126.327297914 1
0.3%
126.3273001467 1
0.3%
126.3273023793 1
0.3%
126.327304612 1
0.3%
126.3273068446 1
0.3%
ValueCountFrequency (%)
126.3274921226 1
0.3%
126.327492107 1
0.3%
126.3274920914 1
0.3%
126.3274920758 1
0.3%
126.3274920602 1
0.3%
126.3274920446 1
0.3%
126.3274899056 1
0.3%
126.32748989 1
0.3%
126.3274898744 1
0.3%
126.3274898588 1
0.3%

SPOT_LA
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct341
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.515008
Minimum36.515002
Maximum36.515016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:06.422956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.515002
5-th percentile36.515002
Q136.515005
median36.515008
Q336.51501
95-th percentile36.515014
Maximum36.515016
Range1.37736 × 10-5
Interquartile range (IQR)5.3562 × 10-6

Descriptive statistics

Standard deviation3.4205724 × 10-6
Coefficient of variation (CV)9.3675797 × 10-8
Kurtosis-0.58217791
Mean36.515008
Median Absolute Deviation (MAD)2.4694 × 10-6
Skewness0
Sum12451.618
Variance1.1700316 × 10-11
MonotonicityNot monotonic
2024-03-13T21:28:06.723216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.5150154997 1
 
0.3%
36.5150064132 1
 
0.3%
36.5150065139 1
 
0.3%
36.5150065013 1
 
0.3%
36.5150064887 1
 
0.3%
36.5150064762 1
 
0.3%
36.5150064636 1
 
0.3%
36.515006451 1
 
0.3%
36.5150064384 1
 
0.3%
36.5150064258 1
 
0.3%
Other values (331) 331
97.1%
ValueCountFrequency (%)
36.5150018394 1
0.3%
36.515001852 1
0.3%
36.5150018646 1
0.3%
36.5150018772 1
0.3%
36.5150018898 1
0.3%
36.5150019024 1
0.3%
36.515001915 1
0.3%
36.5150019276 1
0.3%
36.5150019402 1
0.3%
36.5150019528 1
0.3%
ValueCountFrequency (%)
36.515015613 1
0.3%
36.5150156004 1
0.3%
36.5150155878 1
0.3%
36.5150155752 1
0.3%
36.5150155626 1
0.3%
36.51501555 1
0.3%
36.5150155374 1
0.3%
36.5150155249 1
0.3%
36.5150155123 1
0.3%
36.5150154997 1
0.3%

SPOT_AL
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9478299
Minimum1.944
Maximum3.878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:06.998589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.944
5-th percentile1.977
Q12.515
median2.935
Q33.369
95-th percentile3.784
Maximum3.878
Range1.934
Interquartile range (IQR)0.854

Descriptive statistics

Standard deviation0.53628953
Coefficient of variation (CV)0.18192689
Kurtosis-0.94859789
Mean2.9478299
Median Absolute Deviation (MAD)0.433
Skewness-0.14254634
Sum1005.21
Variance0.28760647
MonotonicityNot monotonic
2024-03-13T21:28:07.245388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.426 6
 
1.8%
1.944 5
 
1.5%
2.843 4
 
1.2%
3.235 3
 
0.9%
2.84 3
 
0.9%
2.844 3
 
0.9%
3.339 3
 
0.9%
1.945 3
 
0.9%
2.424 3
 
0.9%
3.368 3
 
0.9%
Other values (273) 305
89.4%
ValueCountFrequency (%)
1.944 5
1.5%
1.945 3
0.9%
1.946 1
 
0.3%
1.947 1
 
0.3%
1.949 1
 
0.3%
1.951 1
 
0.3%
1.953 1
 
0.3%
1.965 1
 
0.3%
1.97 1
 
0.3%
1.975 2
 
0.6%
ValueCountFrequency (%)
3.878 3
0.9%
3.877 1
 
0.3%
3.874 1
 
0.3%
3.87 1
 
0.3%
3.855 1
 
0.3%
3.839 1
 
0.3%
3.836 1
 
0.3%
3.828 1
 
0.3%
3.827 1
 
0.3%
3.826 1
 
0.3%

GRDNT_RT
Real number (ℝ)

HIGH CORRELATION 

Distinct324
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.624194
Minimum0.06
Maximum61.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:07.586271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile1.72
Q19.4
median13.93
Q320.53
95-th percentile34.23
Maximum61.9
Range61.84
Interquartile range (IQR)11.13

Descriptive statistics

Standard deviation10.129157
Coefficient of variation (CV)0.64829954
Kurtosis3.490852
Mean15.624194
Median Absolute Deviation (MAD)5.21
Skewness1.4428192
Sum5327.85
Variance102.59983
MonotonicityNot monotonic
2024-03-13T21:28:07.908351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.1 2
 
0.6%
2.18 2
 
0.6%
12.92 2
 
0.6%
14.11 2
 
0.6%
18.5 2
 
0.6%
8.99 2
 
0.6%
13.17 2
 
0.6%
0.99 2
 
0.6%
20.2 2
 
0.6%
5.53 2
 
0.6%
Other values (314) 321
94.1%
ValueCountFrequency (%)
0.06 1
0.3%
0.19 1
0.3%
0.26 1
0.3%
0.34 1
0.3%
0.44 1
0.3%
0.81 1
0.3%
0.99 2
0.6%
1.11 1
0.3%
1.13 1
0.3%
1.16 1
0.3%
ValueCountFrequency (%)
61.9 1
0.3%
60.2 1
0.3%
56.43 1
0.3%
51.47 1
0.3%
50.24 1
0.3%
47.18 1
0.3%
46.34 1
0.3%
46.14 1
0.3%
44.74 1
0.3%
41.85 1
0.3%

GRDNT_VAL
Real number (ℝ)

HIGH CORRELATION 

Distinct303
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.7747801
Minimum0.03
Maximum31.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:08.285259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.98
Q15.37
median7.93
Q311.6
95-th percentile18.9
Maximum31.76
Range31.73
Interquartile range (IQR)6.23

Descriptive statistics

Standard deviation5.4572947
Coefficient of variation (CV)0.62192951
Kurtosis2.5034919
Mean8.7747801
Median Absolute Deviation (MAD)2.93
Skewness1.2165416
Sum2992.2
Variance29.782065
MonotonicityNot monotonic
2024-03-13T21:28:08.576015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.55 3
 
0.9%
11.42 3
 
0.9%
0.98 2
 
0.6%
9.06 2
 
0.6%
15.93 2
 
0.6%
0.57 2
 
0.6%
11.82 2
 
0.6%
3.17 2
 
0.6%
7.38 2
 
0.6%
7.56 2
 
0.6%
Other values (293) 319
93.5%
ValueCountFrequency (%)
0.03 1
0.3%
0.11 1
0.3%
0.15 1
0.3%
0.2 1
0.3%
0.25 1
0.3%
0.46 1
0.3%
0.57 2
0.6%
0.63 1
0.3%
0.64 1
0.3%
0.66 1
0.3%
ValueCountFrequency (%)
31.76 1
0.3%
31.05 1
0.3%
29.44 1
0.3%
27.24 1
0.3%
26.68 1
0.3%
25.26 1
0.3%
24.86 1
0.3%
24.77 1
0.3%
24.1 1
0.3%
22.71 1
0.3%

SLANT_DRC
Real number (ℝ)

Distinct331
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean255.47806
Minimum39.06
Maximum346.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T21:28:08.860781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.06
5-th percentile101.58
Q1242.87
median271.08
Q3284.51
95-th percentile319.6
Maximum346.95
Range307.89
Interquartile range (IQR)41.64

Descriptive statistics

Standard deviation59.08811
Coefficient of variation (CV)0.23128448
Kurtosis3.9490268
Mean255.47806
Median Absolute Deviation (MAD)21.34
Skewness-1.9405372
Sum87118.02
Variance3491.4048
MonotonicityNot monotonic
2024-03-13T21:28:09.094836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
239.56 2
 
0.6%
270.96 2
 
0.6%
274.44 2
 
0.6%
314.84 2
 
0.6%
274.51 2
 
0.6%
278.64 2
 
0.6%
284.43 2
 
0.6%
281.81 2
 
0.6%
310.25 2
 
0.6%
270.53 2
 
0.6%
Other values (321) 321
94.1%
ValueCountFrequency (%)
39.06 1
0.3%
40.09 1
0.3%
40.99 1
0.3%
43.3 1
0.3%
44.82 1
0.3%
53.33 1
0.3%
56.24 1
0.3%
57.2 1
0.3%
59.97 1
0.3%
60.49 1
0.3%
ValueCountFrequency (%)
346.95 1
0.3%
338.35 1
0.3%
336.01 1
0.3%
334.34 1
0.3%
331.88 1
0.3%
329.46 1
0.3%
328.35 1
0.3%
325.3 1
0.3%
325.22 1
0.3%
325.21 1
0.3%

Interactions

2024-03-13T21:28:03.846492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:55.478890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:56.800722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:58.584486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:01.370338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.608851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:04.114403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:55.718867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:57.013384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:58.850744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:01.604388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.796118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:04.415072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:55.958127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:57.288357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:59.320557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:01.819062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.970913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:04.584188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:56.171776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:57.968473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:59.965994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.039577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:03.172276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:04.748016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:56.371981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:58.168031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:00.560214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.212286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:03.434972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:04.929295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:56.590942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:27:58.372261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:01.043365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:02.407309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:03.663519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:28:09.740714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.8150.9780.4600.4220.746
SPOT_LA0.8151.0000.7910.4900.5100.689
SPOT_AL0.9780.7911.0000.4550.4350.717
GRDNT_RT0.4600.4900.4551.0000.9920.530
GRDNT_VAL0.4220.5100.4350.9921.0000.509
SLANT_DRC0.7460.6890.7170.5300.5091.000
2024-03-13T21:28:10.025996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.6740.9960.0490.0490.172
SPOT_LA0.6741.0000.6660.2140.2130.402
SPOT_AL0.9960.6661.0000.0490.0490.166
GRDNT_RT0.0490.2140.0491.0001.0000.423
GRDNT_VAL0.0490.2130.0491.0001.0000.423
SLANT_DRC0.1720.4020.1660.4230.4231.000

Missing values

2024-03-13T21:28:05.167673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:28:05.394113image/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
0126.32747236.5150153.36813.267.55338.35
1126.32747436.5150163.37132.4817.99312.92
2126.32747636.5150163.37560.231.05307.68
3126.32747936.5150163.41161.931.76304.55
4126.32748136.5150163.50141.8522.71295.79
5126.32748336.5150163.66122.6412.76284.51
6126.32748536.5150163.7423.0712.99270.53
7126.32748836.5150163.7824.2513.63264.89
8126.3274936.5150163.85515.818.99316.89
9126.32749236.5150163.87818.8910.7313.86
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
331126.32730936.5150021.94413.557.72288.73
332126.32731136.5150021.94712.637.2285.31
333126.32731436.5150021.95310.686.1277.11
334126.32731636.5150021.96512.497.12262.1
335126.32731836.5150021.97526.4114.79248.65
336126.3273236.5150021.98636.7520.18232.42
337126.32732236.5150022.01134.2318.9211.4
338126.32732536.5150022.04324.8513.95188.25
339126.32732736.5150022.06516.459.34157.44
340126.32732936.5150022.0829.675.52135.01