Overview

Dataset statistics

Number of variables9
Number of observations130844
Missing cells215065
Missing cells (%)18.3%
Total size in memory9.0 MiB
Average record size in memory72.0 B

Variable types

Text2
Numeric7

Dataset

DescriptionA dataset from the WAMEX database.
URLhttps://www.dmp.wa.gov.au/WAMEX-Minerals-Exploration-1476.aspx

Alerts

Gamma has 27716 (21.2%) missing valuesMissing
MagSusc has 39182 (29.9%) missing valuesMissing
Caliper has 74081 (56.6%) missing valuesMissing
Density has 74086 (56.6%) missing valuesMissing
Gamma is highly skewed (γ1 = -321.1155986)Skewed
MagSusc has 19506 (14.9%) zerosZeros
Caliper has 19529 (14.9%) zerosZeros
Density has 19534 (14.9%) zerosZeros

Reproduction

Analysis started2023-07-19 23:04:37.330836
Analysis finished2023-07-19 23:04:37.799245
Duration0.47 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

HOLEID
Text

Distinct312
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1022.3 KiB
2023-07-20T07:04:38.909345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.369218306
Min length6

Characters and Unicode

Total characters833374
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCB0002
2nd rowCB0002
3rd rowCB0002
4th rowCB0002
5th rowCB0002
ValueCountFrequency (%)
cc0016 1670
 
1.3%
cc0919 1211
 
0.9%
cc0026 1137
 
0.9%
cc0042 1076
 
0.8%
ccd0026 1073
 
0.8%
cc0065 1011
 
0.8%
cc0032 1005
 
0.8%
cc0048 1005
 
0.8%
cc0523 1003
 
0.8%
ccd0001 996
 
0.8%
Other values (302) 119657
91.5%
2023-07-20T07:04:40.828556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 243487
29.2%
C 243428
29.2%
1 49822
 
6.0%
D 48310
 
5.8%
4 36789
 
4.4%
2 35712
 
4.3%
3 30341
 
3.6%
5 28271
 
3.4%
6 28229
 
3.4%
7 25663
 
3.1%
Other values (3) 63322
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 523376
62.8%
Uppercase Letter 309998
37.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 243487
46.5%
1 49822
 
9.5%
4 36789
 
7.0%
2 35712
 
6.8%
3 30341
 
5.8%
5 28271
 
5.4%
6 28229
 
5.4%
7 25663
 
4.9%
8 22983
 
4.4%
9 22079
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
C 243428
78.5%
D 48310
 
15.6%
B 18260
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 523376
62.8%
Latin 309998
37.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 243487
46.5%
1 49822
 
9.5%
4 36789
 
7.0%
2 35712
 
6.8%
3 30341
 
5.8%
5 28271
 
5.4%
6 28229
 
5.4%
7 25663
 
4.9%
8 22983
 
4.4%
9 22079
 
4.2%
Latin
ValueCountFrequency (%)
C 243428
78.5%
D 48310
 
15.6%
B 18260
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 833374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 243487
29.2%
C 243428
29.2%
1 49822
 
6.0%
D 48310
 
5.8%
4 36789
 
4.4%
2 35712
 
4.3%
3 30341
 
3.6%
5 28271
 
3.4%
6 28229
 
3.4%
7 25663
 
3.1%
Other values (3) 63322
 
7.6%

PROJECTCODE
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1022.3 KiB
2023-07-20T07:04:41.256737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters261688
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCB
2nd rowCB
3rd rowCB
4th rowCB
5th rowCB
ValueCountFrequency (%)
cc 112584
86.0%
cb 18260
 
14.0%
2023-07-20T07:04:42.238917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 243428
93.0%
B 18260
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 261688
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 243428
93.0%
B 18260
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 261688
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 243428
93.0%
B 18260
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 243428
93.0%
B 18260
 
7.0%

GEOLFROM
Real number (ℝ)

Distinct5671
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.25823202
Minimum-0.1
Maximum86.3
Zeros144
Zeros (%)0.1%
Negative1
Negative (%)< 0.1%
Memory size1022.3 KiB
2023-07-20T07:04:42.939697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.1
5-th percentile2.4
Q17.8
median14.82
Q323.8
95-th percentile41.0185
Maximum86.3
Range86.4
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.34705189
Coefficient of variation (CV)0.7154297079
Kurtosis1.683387354
Mean17.25823202
Median Absolute Deviation (MAD)7.7
Skewness1.170599152
Sum2258136.11
Variance152.4496904
MonotonicityNot monotonic
2023-07-20T07:04:43.871225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.7 179
 
0.1%
7.8 179
 
0.1%
7.6 179
 
0.1%
7.5 179
 
0.1%
7.4 179
 
0.1%
7.3 179
 
0.1%
7.2 179
 
0.1%
7.1 179
 
0.1%
7 179
 
0.1%
6.9 179
 
0.1%
Other values (5661) 129054
98.6%
ValueCountFrequency (%)
-0.1 1
 
< 0.1%
0 144
0.1%
0.02 3
 
< 0.1%
0.04 1
 
< 0.1%
0.06 1
 
< 0.1%
ValueCountFrequency (%)
86.3 1
< 0.1%
86.2 1
< 0.1%
86.1 1
< 0.1%
86 1
< 0.1%
85.9 1
< 0.1%

GEOLTO
Real number (ℝ)

Distinct5671
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.25823202
Minimum-0.1
Maximum86.3
Zeros144
Zeros (%)0.1%
Negative1
Negative (%)< 0.1%
Memory size1022.3 KiB
2023-07-20T07:04:44.485211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.1
5-th percentile2.4
Q17.8
median14.82
Q323.8
95-th percentile41.0185
Maximum86.3
Range86.4
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.34705189
Coefficient of variation (CV)0.7154297079
Kurtosis1.683387354
Mean17.25823202
Median Absolute Deviation (MAD)7.7
Skewness1.170599152
Sum2258136.11
Variance152.4496904
MonotonicityNot monotonic
2023-07-20T07:04:45.106463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.7 179
 
0.1%
7.8 179
 
0.1%
7.6 179
 
0.1%
7.5 179
 
0.1%
7.4 179
 
0.1%
7.3 179
 
0.1%
7.2 179
 
0.1%
7.1 179
 
0.1%
7 179
 
0.1%
6.9 179
 
0.1%
Other values (5661) 129054
98.6%
ValueCountFrequency (%)
-0.1 1
 
< 0.1%
0 144
0.1%
0.02 3
 
< 0.1%
0.04 1
 
< 0.1%
0.06 1
 
< 0.1%
ValueCountFrequency (%)
86.3 1
< 0.1%
86.2 1
< 0.1%
86.1 1
< 0.1%
86 1
< 0.1%
85.9 1
< 0.1%

PRIORITY
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.05812265
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1022.3 KiB
2023-07-20T07:04:45.412643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q330
95-th percentile30
Maximum30
Range29
Interquartile range (IQR)29

Descriptive statistics

Standard deviation13.44013956
Coefficient of variation (CV)1.336247333
Kurtosis-1.344232933
Mean10.05812265
Median Absolute Deviation (MAD)0
Skewness0.8098071463
Sum1316045
Variance180.6373515
MonotonicityNot monotonic
2023-07-20T07:04:45.685670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 89975
68.8%
30 40869
31.2%
ValueCountFrequency (%)
1 89975
68.8%
30 40869
31.2%
ValueCountFrequency (%)
30 40869
31.2%
1 89975
68.8%

Gamma
Real number (ℝ)

MISSING  SKEWED 

Distinct12342
Distinct (%)12.0%
Missing27716
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean-250.2293953
Minimum-28074896.05
Maximum37062.19
Zeros1058
Zeros (%)0.8%
Negative2746
Negative (%)2.1%
Memory size1022.3 KiB
2023-07-20T07:04:46.207509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-28074896.05
5-th percentile0.38
Q18.7
median21.72
Q354.90625
95-th percentile136.6
Maximum37062.19
Range28111958.24
Interquartile range (IQR)46.20625

Descriptive statistics

Standard deviation87425.70791
Coefficient of variation (CV)-349.3822451
Kurtosis103119.4914
Mean-250.2293953
Median Absolute Deviation (MAD)16.69
Skewness-321.1155986
Sum-25805657.08
Variance7643254404
MonotonicityNot monotonic
2023-07-20T07:04:46.787577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-999.25 2745
 
2.1%
0 1058
 
0.8%
8.7 678
 
0.5%
17.3 505
 
0.4%
26 432
 
0.3%
34.7 329
 
0.3%
13 302
 
0.2%
16.5 289
 
0.2%
43.3 260
 
0.2%
52 247
 
0.2%
Other values (12332) 96283
73.6%
(Missing) 27716
 
21.2%
ValueCountFrequency (%)
-28074896.05 1
 
< 0.1%
-999.25 2745
2.1%
0 1058
 
0.8%
0.01 85
 
0.1%
0.02 65
 
< 0.1%
ValueCountFrequency (%)
37062.19 20
< 0.1%
30173.96 1
 
< 0.1%
17304.21 1
 
< 0.1%
13739.54 1
 
< 0.1%
9983.01 1
 
< 0.1%

MagSusc
Real number (ℝ)

MISSING  ZEROS 

Distinct6038
Distinct (%)6.6%
Missing39182
Missing (%)29.9%
Infinite0
Infinite (%)0.0%
Mean-15.74409755
Minimum-999.25
Maximum1327.45
Zeros19506
Zeros (%)14.9%
Negative2501
Negative (%)1.9%
Memory size1022.3 KiB
2023-07-20T07:04:47.266775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-999.25
5-th percentile0
Q10.38
median2.8
Q35.3
95-th percentile38.9
Maximum1327.45
Range2326.7
Interquartile range (IQR)4.92

Descriptive statistics

Standard deviation177.0906565
Coefficient of variation (CV)-11.24806652
Kurtosis29.54207752
Mean-15.74409755
Median Absolute Deviation (MAD)2.5
Skewness-3.756498413
Sum-1443135.47
Variance31361.10064
MonotonicityNot monotonic
2023-07-20T07:04:47.750804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19506
 
14.9%
-999.25 2501
 
1.9%
2.6 1154
 
0.9%
2.8 1151
 
0.9%
2.4 1096
 
0.8%
2.7 995
 
0.8%
2.9 973
 
0.7%
3 936
 
0.7%
3.2 935
 
0.7%
3.3 894
 
0.7%
Other values (6028) 61521
47.0%
(Missing) 39182
29.9%
ValueCountFrequency (%)
-999.25 2501
 
1.9%
0 19506
14.9%
0.01 4
 
< 0.1%
0.02 10
 
< 0.1%
0.03 6
 
< 0.1%
ValueCountFrequency (%)
1327.45 1
< 0.1%
1325.79 1
< 0.1%
1323.22 1
< 0.1%
1322.88 1
< 0.1%
1321.9 1
< 0.1%

Caliper
Real number (ℝ)

MISSING  ZEROS 

Distinct121
Distinct (%)0.2%
Missing74081
Missing (%)56.6%
Infinite0
Infinite (%)0.0%
Mean-39.34055635
Minimum-999.25
Maximum20.3
Zeros19529
Zeros (%)14.9%
Negative2688
Negative (%)2.1%
Memory size1022.3 KiB
2023-07-20T07:04:48.186804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-999.25
5-th percentile0
Q10
median12.1
Q313.3
95-th percentile14.5
Maximum20.3
Range1019.55
Interquartile range (IQR)13.3

Descriptive statistics

Standard deviation214.1085291
Coefficient of variation (CV)-5.442437753
Kurtosis16.13629663
Mean-39.34055635
Median Absolute Deviation (MAD)2.1
Skewness-4.256424764
Sum-2233088
Variance45842.46224
MonotonicityNot monotonic
2023-07-20T07:04:48.671602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19529
 
14.9%
12.1 5502
 
4.2%
12.2 3154
 
2.4%
12 2951
 
2.3%
-999.25 2688
 
2.1%
14.3 1816
 
1.4%
14.2 1567
 
1.2%
11.9 1263
 
1.0%
12.3 1255
 
1.0%
13.8 1062
 
0.8%
Other values (111) 15976
 
12.2%
(Missing) 74081
56.6%
ValueCountFrequency (%)
-999.25 2688
 
2.1%
0 19529
14.9%
5.1 1
 
< 0.1%
6.6 2
 
< 0.1%
6.9 2
 
< 0.1%
ValueCountFrequency (%)
20.3 101
0.1%
20.2 1
 
< 0.1%
20.1 4
 
< 0.1%
20 6
 
< 0.1%
19.9 38
 
< 0.1%

Density
Real number (ℝ)

MISSING  ZEROS 

Distinct382
Distinct (%)0.7%
Missing74086
Missing (%)56.6%
Infinite0
Infinite (%)0.0%
Mean-44.81363403
Minimum-999.25
Maximum4.3
Zeros19534
Zeros (%)14.9%
Negative2632
Negative (%)2.0%
Memory size1022.3 KiB
2023-07-20T07:04:49.136345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-999.25
5-th percentile0
Q10
median1.92
Q32.68
95-th percentile3.36
Maximum4.3
Range1003.55
Interquartile range (IQR)2.68

Descriptive statistics

Standard deviation210.474142
Coefficient of variation (CV)-4.696654191
Kurtosis16.61335756
Mean-44.81363403
Median Absolute Deviation (MAD)1.2
Skewness-4.314156091
Sum-2543532.24
Variance44299.36447
MonotonicityNot monotonic
2023-07-20T07:04:49.695239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19534
 
14.9%
-999.25 2632
 
2.0%
2.44 240
 
0.2%
2.4 235
 
0.2%
2.48 232
 
0.2%
2.37 232
 
0.2%
2.57 231
 
0.2%
2.68 231
 
0.2%
2.67 231
 
0.2%
2.35 226
 
0.2%
Other values (372) 32734
25.0%
(Missing) 74086
56.6%
ValueCountFrequency (%)
-999.25 2632
 
2.0%
0 19534
14.9%
0.41 1
 
< 0.1%
0.45 1
 
< 0.1%
0.46 1
 
< 0.1%
ValueCountFrequency (%)
4.3 1
< 0.1%
4.29 1
< 0.1%
4.28 1
< 0.1%
4.27 1
< 0.1%
4.25 1
< 0.1%

Sample

HOLEIDPROJECTCODEGEOLFROMGEOLTOPRIORITYGammaMagSuscCaliperDensity
0CB0002CB0.140.143088.7800.00.00.0
1CB0002CB0.240.243088.1800.00.00.0
2CB0002CB0.340.343089.8300.00.00.0
3CB0002CB0.440.443089.7350.00.00.0
4CB0002CB0.540.543097.0900.00.00.0
5CB0002CB0.640.643092.1700.00.00.0
6CB0002CB0.740.743089.9650.00.00.0
7CB0002CB0.840.843087.5700.00.00.0
8CB0002CB0.940.943089.0750.00.00.0
9CB0002CB1.041.043092.4850.00.00.0