Overview

Dataset statistics

Number of variables6
Number of observations424
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.5 KiB
Average record size in memory54.3 B

Variable types

Numeric6

Alerts

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

Reproduction

Analysis started2024-03-13 12:50:17.687029
Analysis finished2024-03-13 12:50:23.880782
Duration6.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SPOT_LO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct424
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.39889
Minimum129.39883
Maximum129.39895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:50:23.996507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.39883
5-th percentile129.39884
Q1129.39886
median129.39889
Q3129.39892
95-th percentile129.39894
Maximum129.39895
Range0.0001200928
Interquartile range (IQR)5.615005 × 10-5

Descriptive statistics

Standard deviation3.3444098 × 10-5
Coefficient of variation (CV)2.5845737 × 10-7
Kurtosis-1.1668728
Mean129.39889
Median Absolute Deviation (MAD)2.887995 × 10-5
Skewness-0.04667088
Sum54865.131
Variance1.1185077 × 10-9
MonotonicityNot monotonic
2024-03-13T21:50:24.221852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.3989067373 1
 
0.2%
129.3988644534 1
 
0.2%
129.3988600082 1
 
0.2%
129.3988577856 1
 
0.2%
129.398855563 1
 
0.2%
129.3988533404 1
 
0.2%
129.3988511178 1
 
0.2%
129.3988488952 1
 
0.2%
129.3988466727 1
 
0.2%
129.3988444501 1
 
0.2%
Other values (414) 414
97.6%
ValueCountFrequency (%)
129.3988310963 1
0.2%
129.3988333189 1
0.2%
129.398833328 1
0.2%
129.3988333371 1
0.2%
129.3988333462 1
0.2%
129.3988333554 1
0.2%
129.3988355415 1
0.2%
129.3988355506 1
0.2%
129.3988355597 1
0.2%
129.3988355688 1
0.2%
ValueCountFrequency (%)
129.3989511891 1
0.2%
129.39895118 1
0.2%
129.3989511708 1
0.2%
129.3989489665 1
0.2%
129.3989489574 1
0.2%
129.3989489483 1
0.2%
129.3989489391 1
0.2%
129.39894893 1
0.2%
129.3989489209 1
0.2%
129.3989467439 1
0.2%

SPOT_LA
Real number (ℝ)

UNIQUE 

Distinct424
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.158454
Minimum36.158447
Maximum36.158461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:50:24.470582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.158447
5-th percentile36.158447
Q136.15845
median36.158454
Q336.158457
95-th percentile36.15846
Maximum36.158461
Range1.44708 × 10-5
Interquartile range (IQR)7.2058 × 10-6

Descriptive statistics

Standard deviation4.2658326 × 10-6
Coefficient of variation (CV)1.1797608 × 10-7
Kurtosis-1.1442894
Mean36.158454
Median Absolute Deviation (MAD)3.60475 × 10-6
Skewness0
Sum15331.184
Variance1.8197328 × 10-11
MonotonicityStrictly decreasing
2024-03-13T21:50:24.713024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.1584611381 1
 
0.2%
36.1584504645 1
 
0.2%
36.1584504793 1
 
0.2%
36.1584504867 1
 
0.2%
36.1584504941 1
 
0.2%
36.1584505015 1
 
0.2%
36.1584505089 1
 
0.2%
36.1584505163 1
 
0.2%
36.1584505237 1
 
0.2%
36.1584505312 1
 
0.2%
Other values (414) 414
97.6%
ValueCountFrequency (%)
36.1584466673 1
0.2%
36.1584466747 1
0.2%
36.1584466821 1
0.2%
36.1584466895 1
0.2%
36.1584466969 1
0.2%
36.1584467043 1
0.2%
36.1584467117 1
0.2%
36.1584467191 1
0.2%
36.1584467265 1
0.2%
36.1584467339 1
0.2%
ValueCountFrequency (%)
36.1584611381 1
0.2%
36.1584611307 1
0.2%
36.1584611233 1
0.2%
36.1584611159 1
0.2%
36.1584611085 1
0.2%
36.1584611011 1
0.2%
36.1584610937 1
0.2%
36.1584610863 1
0.2%
36.1584610789 1
0.2%
36.1584610715 1
0.2%

SPOT_AL
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.39046462
Minimum-0.622
Maximum0.666
Zeros0
Zeros (%)0.0%
Negative352
Negative (%)83.0%
Memory size3.9 KiB
2024-03-13T21:50:24.899900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.622
5-th percentile-0.612
Q1-0.606
median-0.572
Q3-0.319
95-th percentile0.392
Maximum0.666
Range1.288
Interquartile range (IQR)0.287

Descriptive statistics

Standard deviation0.33823957
Coefficient of variation (CV)-0.86624896
Kurtosis1.1677616
Mean-0.39046462
Median Absolute Deviation (MAD)0.04
Skewness1.5782149
Sum-165.557
Variance0.11440601
MonotonicityNot monotonic
2024-03-13T21:50:25.127594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.612 77
18.2%
-0.606 50
 
11.8%
-0.572 29
 
6.8%
-0.587 26
 
6.1%
-0.529 19
 
4.5%
-0.622 18
 
4.2%
-0.467 15
 
3.5%
-0.586 12
 
2.8%
-0.443 10
 
2.4%
-0.506 10
 
2.4%
Other values (41) 158
37.3%
ValueCountFrequency (%)
-0.622 18
 
4.2%
-0.612 77
18.2%
-0.606 50
11.8%
-0.595 4
 
0.9%
-0.589 1
 
0.2%
-0.587 26
 
6.1%
-0.586 12
 
2.8%
-0.572 29
 
6.8%
-0.571 8
 
1.9%
-0.555 8
 
1.9%
ValueCountFrequency (%)
0.666 1
 
0.2%
0.618 1
 
0.2%
0.602 1
 
0.2%
0.558 7
1.7%
0.512 3
0.7%
0.483 1
 
0.2%
0.438 6
1.4%
0.392 3
0.7%
0.349 6
1.4%
0.348 1
 
0.2%

GRDNT_RT
Real number (ℝ)

HIGH CORRELATION 

Distinct247
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.909575
Minimum0.02
Maximum59.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:50:25.338764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.03
Q10.11
median4.125
Q323.275
95-th percentile43.1715
Maximum59.66
Range59.64
Interquartile range (IQR)23.165

Descriptive statistics

Standard deviation15.308587
Coefficient of variation (CV)1.2854016
Kurtosis-0.035939175
Mean11.909575
Median Absolute Deviation (MAD)4.085
Skewness1.1535233
Sum5049.66
Variance234.35283
MonotonicityNot monotonic
2024-03-13T21:50:25.608918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04 35
 
8.3%
0.05 22
 
5.2%
0.03 21
 
5.0%
1.6 7
 
1.7%
0.06 7
 
1.7%
0.93 6
 
1.4%
1.14 6
 
1.4%
0.53 5
 
1.2%
0.1 5
 
1.2%
4.22 5
 
1.2%
Other values (237) 305
71.9%
ValueCountFrequency (%)
0.02 3
 
0.7%
0.03 21
5.0%
0.04 35
8.3%
0.05 22
5.2%
0.06 7
 
1.7%
0.07 4
 
0.9%
0.08 4
 
0.9%
0.09 3
 
0.7%
0.1 5
 
1.2%
0.11 4
 
0.9%
ValueCountFrequency (%)
59.66 1
0.2%
56.61 1
0.2%
52.68 1
0.2%
50.85 1
0.2%
50.62 1
0.2%
49.78 1
0.2%
49.59 1
0.2%
49.11 1
0.2%
48.99 1
0.2%
48.3 1
0.2%

GRDNT_VAL
Real number (ℝ)

HIGH CORRELATION 

Distinct225
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5781604
Minimum0.01
Maximum30.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:50:25.849386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.02
Q10.06
median2.36
Q313.1025
95-th percentile23.3515
Maximum30.82
Range30.81
Interquartile range (IQR)13.0425

Descriptive statistics

Standard deviation8.3172676
Coefficient of variation (CV)1.2643759
Kurtosis-0.24509771
Mean6.5781604
Median Absolute Deviation (MAD)2.335
Skewness1.0932624
Sum2789.14
Variance69.17694
MonotonicityNot monotonic
2024-03-13T21:50:26.039842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 54
 
12.7%
0.03 29
 
6.8%
0.04 8
 
1.9%
2.42 7
 
1.7%
0.06 7
 
1.7%
0.53 7
 
1.7%
0.07 6
 
1.4%
2.05 6
 
1.4%
0.05 6
 
1.4%
3.72 6
 
1.4%
Other values (215) 288
67.9%
ValueCountFrequency (%)
0.01 3
 
0.7%
0.02 54
12.7%
0.03 29
6.8%
0.04 8
 
1.9%
0.05 6
 
1.4%
0.06 7
 
1.7%
0.07 6
 
1.4%
0.08 6
 
1.4%
0.09 2
 
0.5%
0.1 2
 
0.5%
ValueCountFrequency (%)
30.82 1
0.2%
29.52 1
0.2%
27.78 1
0.2%
26.95 1
0.2%
26.85 1
0.2%
26.46 1
0.2%
26.38 1
0.2%
26.16 1
0.2%
26.1 1
0.2%
25.78 1
0.2%

SLANT_DRC
Real number (ℝ)

HIGH CORRELATION 

Distinct380
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.388632
Minimum46.74
Maximum144.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:50:26.214388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46.74
5-th percentile63.7245
Q178.175
median90.345
Q3116.7125
95-th percentile135.1155
Maximum144.27
Range97.53
Interquartile range (IQR)38.5375

Descriptive statistics

Standard deviation23.842642
Coefficient of variation (CV)0.24481956
Kurtosis-1.0339201
Mean97.388632
Median Absolute Deviation (MAD)18.52
Skewness0.17654333
Sum41292.78
Variance568.47158
MonotonicityNot monotonic
2024-03-13T21:50:26.412572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.03 7
 
1.7%
90.06 6
 
1.4%
90.07 5
 
1.2%
89.83 3
 
0.7%
90.05 3
 
0.7%
90.02 3
 
0.7%
135.01 3
 
0.7%
89.82 2
 
0.5%
79.52 2
 
0.5%
89.73 2
 
0.5%
Other values (370) 388
91.5%
ValueCountFrequency (%)
46.74 1
0.2%
47.39 1
0.2%
47.79 1
0.2%
47.94 1
0.2%
48.91 1
0.2%
54.49 1
0.2%
54.87 1
0.2%
56.74 1
0.2%
57.0 1
0.2%
57.57 1
0.2%
ValueCountFrequency (%)
144.27 1
0.2%
142.51 1
0.2%
142.08 1
0.2%
141.94 1
0.2%
141.33 1
0.2%
139.96 1
0.2%
138.37 1
0.2%
138.24 1
0.2%
137.96 1
0.2%
137.47 1
0.2%

Interactions

2024-03-13T21:50:22.789195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:17.984553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.869376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:19.749151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.996839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.879469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.932508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.130324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.973864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.290037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.143509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.074819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:23.102068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.294229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:19.135330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.446716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.306599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.246362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:23.233541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.457507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:19.281265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.586421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.489192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.390941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:23.360221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.601907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:19.439533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.716603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.622766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.546813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:23.485453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:18.741257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:19.563708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:20.849327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:21.750619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:50:22.672293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:50:27.055367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.2370.9270.5860.6340.629
SPOT_LA0.2371.0000.0000.2620.2220.307
SPOT_AL0.9270.0001.0000.3820.4550.461
GRDNT_RT0.5860.2620.3821.0000.9810.750
GRDNT_VAL0.6340.2220.4550.9811.0000.779
SLANT_DRC0.6290.3070.4610.7500.7791.000
2024-03-13T21:50:27.188321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
SPOT_LO1.0000.127-0.9940.0700.0740.036
SPOT_LA0.1271.000-0.091-0.149-0.1440.067
SPOT_AL-0.994-0.0911.000-0.083-0.088-0.020
GRDNT_RT0.070-0.149-0.0831.0000.999-0.842
GRDNT_VAL0.074-0.144-0.0880.9991.000-0.842
SLANT_DRC0.0360.067-0.020-0.842-0.8421.000

Missing values

2024-03-13T21:50:23.662897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:50:23.819791image/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
0129.39890736.158461-0.5870.050.03115.45
1129.39890936.158461-0.5874.152.3799.96
2129.39891136.158461-0.5874.972.85106.41
3129.39891336.158461-0.5951.010.58134.28
4129.39891636.158461-0.6060.030.02114.05
5129.39891836.158461-0.6060.030.02114.92
6129.3989236.158461-0.6060.030.02117.88
7129.39892236.158461-0.6061.140.65108.77
8129.39892536.158461-0.6061.60.91116.62
9129.39892736.158461-0.6060.530.3133.93
SPOT_LOSPOT_LASPOT_ALGRDNT_RTGRDNT_VALSLANT_DRC
414129.39890236.158447-0.58741.1322.3674.22
415129.39890436.158447-0.58733.718.6375.36
416129.39890736.158447-0.58725.914.5285.51
417129.39890936.158447-0.59526.314.7489.75
418129.39891136.158447-0.60617.810.0984.96
419129.39891336.158447-0.60634.4819.0274.02
420129.39891636.158447-0.60648.325.7867.9
421129.39891836.158447-0.60636.3519.9760.27
422129.3989236.158447-0.60636.2319.9263.2
423129.39892236.158447-0.61232.8318.1766.86