Overview

Dataset statistics

Number of variables6
Number of observations438
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.2 KiB
Average record size in memory54.3 B

Variable types

Numeric6

Alerts

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 12:47:35.204832
Analysis finished2024-03-13 12:47:41.298841
Duration6.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SPOT_LO
Real number (ℝ)

UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.12092
Minimum129.12086
Maximum129.12095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-13T21:47:41.427949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.12086
5-th percentile129.12088
Q1129.1209
median129.12092
Q3129.12093
95-th percentile129.12095
Maximum129.12095
Range9.21841 × 10-5
Interquartile range (IQR)3.2922875 × 10-5

Descriptive statistics

Standard deviation2.1955777 × 10-5
Coefficient of variation (CV)1.7004044 × 10-7
Kurtosis-0.7046295
Mean129.12092
Median Absolute Deviation (MAD)1.53929 × 10-5
Skewness-0.32343643
Sum56554.961
Variance4.8205615 × 10-10
MonotonicityNot monotonic
2024-03-13T21:47:41.669269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1209224065 1
 
0.2%
129.1208784863 1
 
0.2%
129.1209026248 1
 
0.2%
129.1209004304 1
 
0.2%
129.120898236 1
 
0.2%
129.1208960416 1
 
0.2%
129.1208938472 1
 
0.2%
129.1208916527 1
 
0.2%
129.1208894583 1
 
0.2%
129.1208872639 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
129.1208609229 1
0.2%
129.1208631174 1
0.2%
129.12086312 1
0.2%
129.1208653118 1
0.2%
129.1208653144 1
0.2%
129.1208675062 1
0.2%
129.1208675089 1
0.2%
129.1208675115 1
0.2%
129.1208697006 1
0.2%
129.1208697033 1
0.2%
ValueCountFrequency (%)
129.120953107 1
0.2%
129.1209531044 1
0.2%
129.1209531017 1
0.2%
129.120953099 1
0.2%
129.1209530964 1
0.2%
129.1209530937 1
0.2%
129.120953091 1
0.2%
129.1209509153 1
0.2%
129.1209509126 1
0.2%
129.1209509099 1
0.2%

SPOT_LA
Real number (ℝ)

UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.132959
Minimum35.132948
Maximum35.132975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-13T21:47:41.888068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.132948
5-th percentile35.132948
Q135.132952
median35.132957
Q335.132965
95-th percentile35.132972
Maximum35.132975
Range2.70474 × 10-5
Interquartile range (IQR)1.2569825 × 10-5

Descriptive statistics

Standard deviation7.3460582 × 10-6
Coefficient of variation (CV)2.0909307 × 10-7
Kurtosis-0.87113234
Mean35.132959
Median Absolute Deviation (MAD)5.4213 × 10-6
Skewness0.38795185
Sum15388.236
Variance5.396457 × 10-11
MonotonicityStrictly decreasing
2024-03-13T21:47:42.119913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1329753598 1
 
0.2%
35.1329537709 1
 
0.2%
35.1329537468 1
 
0.2%
35.132953749 1
 
0.2%
35.1329537512 1
 
0.2%
35.1329537534 1
 
0.2%
35.1329537556 1
 
0.2%
35.1329537577 1
 
0.2%
35.1329537599 1
 
0.2%
35.1329537621 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
35.1329483124 1
0.2%
35.1329483145 1
0.2%
35.1329483167 1
0.2%
35.1329483189 1
0.2%
35.1329483211 1
0.2%
35.1329483233 1
0.2%
35.1329483255 1
0.2%
35.1329483277 1
0.2%
35.1329483299 1
0.2%
35.1329483321 1
0.2%
ValueCountFrequency (%)
35.1329753598 1
0.2%
35.1329753576 1
0.2%
35.1329753554 1
0.2%
35.1329753532 1
0.2%
35.132975351 1
0.2%
35.1329753488 1
0.2%
35.1329735658 1
0.2%
35.1329735636 1
0.2%
35.1329735614 1
0.2%
35.1329735592 1
0.2%

SPOT_AL
Real number (ℝ)

Distinct356
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.046130137
Minimum-0.681
Maximum2.351
Zeros0
Zeros (%)0.0%
Negative208
Negative (%)47.5%
Memory size4.0 KiB
2024-03-13T21:47:42.385369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.681
5-th percentile-0.46145
Q1-0.2455
median0.0215
Q30.314
95-th percentile0.62045
Maximum2.351
Range3.032
Interquartile range (IQR)0.5595

Descriptive statistics

Standard deviation0.37384451
Coefficient of variation (CV)8.1041274
Kurtosis5.1547323
Mean0.046130137
Median Absolute Deviation (MAD)0.284
Skewness1.1291184
Sum20.205
Variance0.13975972
MonotonicityNot monotonic
2024-03-13T21:47:43.090775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.015 4
 
0.9%
0.239 3
 
0.7%
0.155 3
 
0.7%
0.076 3
 
0.7%
0.33 3
 
0.7%
0.083 3
 
0.7%
-0.163 3
 
0.7%
-0.42 3
 
0.7%
0.526 2
 
0.5%
0.182 2
 
0.5%
Other values (346) 409
93.4%
ValueCountFrequency (%)
-0.681 1
0.2%
-0.66 1
0.2%
-0.636 1
0.2%
-0.631 1
0.2%
-0.629 1
0.2%
-0.596 1
0.2%
-0.58 1
0.2%
-0.577 1
0.2%
-0.571 1
0.2%
-0.567 2
0.5%
ValueCountFrequency (%)
2.351 1
0.2%
2.297 1
0.2%
1.428 1
0.2%
0.711 1
0.2%
0.71 1
0.2%
0.709 2
0.5%
0.707 1
0.2%
0.704 1
0.2%
0.698 1
0.2%
0.69 1
0.2%

GRDNT_RT
Real number (ℝ)

HIGH CORRELATION 

Distinct431
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.402146
Minimum2.07
Maximum290.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-13T21:47:43.275078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.07
5-th percentile8.076
Q121.1825
median40.25
Q360.1675
95-th percentile119.8605
Maximum290.71
Range288.64
Interquartile range (IQR)38.985

Descriptive statistics

Standard deviation34.422805
Coefficient of variation (CV)0.74183648
Kurtosis6.6235912
Mean46.402146
Median Absolute Deviation (MAD)19.26
Skewness1.8548165
Sum20324.14
Variance1184.9295
MonotonicityNot monotonic
2024-03-13T21:47:43.489876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.96 2
 
0.5%
17.21 2
 
0.5%
54.03 2
 
0.5%
53.35 2
 
0.5%
25.1 2
 
0.5%
53.72 2
 
0.5%
20.32 2
 
0.5%
55.31 1
 
0.2%
11.04 1
 
0.2%
6.15 1
 
0.2%
Other values (421) 421
96.1%
ValueCountFrequency (%)
2.07 1
0.2%
4.43 1
0.2%
4.54 1
0.2%
4.79 1
0.2%
4.83 1
0.2%
4.86 1
0.2%
5.3 1
0.2%
6.02 1
0.2%
6.13 1
0.2%
6.15 1
0.2%
ValueCountFrequency (%)
290.71 1
0.2%
195.05 1
0.2%
154.96 1
0.2%
150.23 1
0.2%
148.89 1
0.2%
142.83 1
0.2%
141.22 1
0.2%
140.92 1
0.2%
140.36 1
0.2%
140.23 1
0.2%

GRDNT_VAL
Real number (ℝ)

HIGH CORRELATION 

Distinct419
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.996598
Minimum1.19
Maximum71.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-13T21:47:43.663462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.19
5-th percentile4.6165
Q111.96
median21.925
Q331.035
95-th percentile50.163
Maximum71.02
Range69.83
Interquartile range (IQR)19.075

Descriptive statistics

Standard deviation13.455664
Coefficient of variation (CV)0.58511541
Kurtosis-0.093713557
Mean22.996598
Median Absolute Deviation (MAD)9.625
Skewness0.6334376
Sum10072.51
Variance181.05489
MonotonicityNot monotonic
2024-03-13T21:47:43.850197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.24 3
 
0.7%
28.38 3
 
0.7%
40.02 2
 
0.5%
14.09 2
 
0.5%
11.49 2
 
0.5%
6.42 2
 
0.5%
19.9 2
 
0.5%
9.84 2
 
0.5%
26.13 2
 
0.5%
28.95 2
 
0.5%
Other values (409) 416
95.0%
ValueCountFrequency (%)
1.19 1
0.2%
2.54 1
0.2%
2.6 1
0.2%
2.74 1
0.2%
2.76 1
0.2%
2.78 1
0.2%
3.03 1
0.2%
3.44 1
0.2%
3.51 1
0.2%
3.52 1
0.2%
ValueCountFrequency (%)
71.02 1
0.2%
62.86 1
0.2%
57.16 1
0.2%
56.35 1
0.2%
56.11 1
0.2%
55.0 1
0.2%
54.7 1
0.2%
54.64 1
0.2%
54.53 1
0.2%
54.51 1
0.2%

SLANT_DRC
Real number (ℝ)

Distinct434
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.51756
Minimum0.53
Maximum358.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-13T21:47:44.038203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.53
5-th percentile16.098
Q179.1475
median117.965
Q3319.4925
95-th percentile349.2395
Maximum358.16
Range357.63
Interquartile range (IQR)240.345

Descriptive statistics

Standard deviation122.6396
Coefficient of variation (CV)0.69477282
Kurtosis-1.5675312
Mean176.51756
Median Absolute Deviation (MAD)87.76
Skewness0.28425607
Sum77314.69
Variance15040.472
MonotonicityNot monotonic
2024-03-13T21:47:44.229712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
87.32 2
 
0.5%
338.34 2
 
0.5%
344.38 2
 
0.5%
126.63 2
 
0.5%
106.76 1
 
0.2%
82.18 1
 
0.2%
100.81 1
 
0.2%
109.85 1
 
0.2%
96.77 1
 
0.2%
353.05 1
 
0.2%
Other values (424) 424
96.8%
ValueCountFrequency (%)
0.53 1
0.2%
1.16 1
0.2%
1.19 1
0.2%
1.3 1
0.2%
1.37 1
0.2%
2.45 1
0.2%
2.59 1
0.2%
2.62 1
0.2%
4.14 1
0.2%
5.37 1
0.2%
ValueCountFrequency (%)
358.16 1
0.2%
356.88 1
0.2%
356.75 1
0.2%
356.63 1
0.2%
356.04 1
0.2%
355.14 1
0.2%
354.77 1
0.2%
354.43 1
0.2%
354.37 1
0.2%
354.19 1
0.2%

Interactions

2024-03-13T21:47:40.016998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:35.548015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.545799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.414123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.365929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.148737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:40.228082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:35.743708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.680495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.556644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.523921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.280435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:40.408260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:35.915971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.827224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.697988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.639957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.422545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:40.553525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.069136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.974946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.883020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.739273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.566343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:40.717053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.213866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.124501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.070426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.864496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.694394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:40.838325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:36.386964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:37.269400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:38.217577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.015862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:47:39.857875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:47:44.361047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.4590.6680.3660.4980.650
SPOT_LA0.4591.0000.3830.2850.4390.535
SPOT_AL0.6680.3831.0000.2260.2730.451
GRDNT_RT0.3660.2850.2261.0000.9430.647
GRDNT_VAL0.4980.4390.2730.9431.0000.766
SLANT_DRC0.6500.5350.4510.6470.7661.000
2024-03-13T21:47:44.519704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.256-0.3770.2520.2520.257
SPOT_LA0.2561.000-0.2710.3030.3030.321
SPOT_AL-0.377-0.2711.0000.0570.057-0.039
GRDNT_RT0.2520.3030.0571.0001.0000.420
GRDNT_VAL0.2520.3030.0571.0001.0000.420
SLANT_DRC0.2570.321-0.0390.4200.4201.000

Missing values

2024-03-13T21:47:41.034390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:47:41.216257image/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
0129.12092235.132975-0.23572.4435.92335.85
1129.12092535.132975-0.18473.1736.19338.34
2129.12092735.132975-0.1465.3533.16340.79
3129.12092935.132975-0.08947.7225.51353.59
4129.12093135.132975-0.02789.8441.94311.82
5129.12093335.1329750.00961.9231.77319.47
6129.12091435.132974-0.57154.7528.7325.39
7129.12091635.132974-0.35358.1530.18323.79
8129.12091835.132974-0.22257.4329.87326.2
9129.1209235.132974-0.16348.7926.01332.84
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
428129.12090935.1329480.62328.4615.8924.87
429129.12091135.1329480.57729.1316.2422.63
430129.12091435.1329480.49126.2614.7116.23
431129.12091635.1329480.3920.0811.355.44
432129.12091835.1329480.31113.927.93348.99
433129.1209235.1329480.20526.1114.63248.28
434129.12092235.1329480.09680.9839.0216.0
435129.12092535.132948-0.002150.2356.35217.5
436129.12092735.132948-0.075154.9657.16206.27
437129.12092935.132948-0.163140.2354.51179.64