Overview

Brought to you by YData

Dataset statistics

Number of variables27
Number of observations136916
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.2 MiB
Average record size in memory216.0 B

Variable types

Categorical1
Text1
Numeric25

Alerts

AANTAL_BSN is highly overall correlated with AANTAL_VERZEKERDEJAREN and 12 other fieldsHigh correlation
AANTAL_VERZEKERDEJAREN is highly overall correlated with AANTAL_BSN and 13 other fieldsHigh correlation
GESLACHT is highly overall correlated with AANTAL_BSN and 5 other fieldsHigh correlation
KOSTEN_FARMACIE is highly overall correlated with AANTAL_BSN and 12 other fieldsHigh correlation
KOSTEN_GENERALISTISCHE_BASIS_GGZ is highly overall correlated with AANTAL_BSN and 2 other fieldsHigh correlation
KOSTEN_GERIATRISCHE_REVALIDATIEZORG is highly overall correlated with KOSTEN_VERPLEGING_EN_VERZORGING and 1 other fieldsHigh correlation
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG is highly overall correlated with AANTAL_BSN and 5 other fieldsHigh correlation
KOSTEN_HUISARTS_CONSULT is highly overall correlated with AANTAL_BSN and 14 other fieldsHigh correlation
KOSTEN_HUISARTS_INSCHRIJFTARIEF is highly overall correlated with AANTAL_BSN and 15 other fieldsHigh correlation
KOSTEN_HUISARTS_MDZ is highly overall correlated with KOSTEN_FARMACIE and 7 other fieldsHigh correlation
KOSTEN_HUISARTS_OVERIG is highly overall correlated with AANTAL_BSN and 13 other fieldsHigh correlation
KOSTEN_HULPMIDDELEN is highly overall correlated with AANTAL_BSN and 11 other fieldsHigh correlation
KOSTEN_KRAAMZORG is highly overall correlated with KOSTEN_VERLOSKUNDIGE_ZORGHigh correlation
KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG is highly overall correlated with AANTAL_BSN and 13 other fieldsHigh correlation
KOSTEN_MONDZORG is highly overall correlated with AANTAL_VERZEKERDEJAREN and 3 other fieldsHigh correlation
KOSTEN_OVERIG is highly overall correlated with KOSTEN_FARMACIE and 6 other fieldsHigh correlation
KOSTEN_PARAMEDISCHE_ZORG_FYSIOTHERAPIE is highly overall correlated with AANTAL_BSN and 9 other fieldsHigh correlation
KOSTEN_PARAMEDISCHE_ZORG_OVERIG is highly overall correlated with AANTAL_BSN and 6 other fieldsHigh correlation
KOSTEN_SPECIALISTISCHE_GGZ is highly overall correlated with AANTAL_BSN and 4 other fieldsHigh correlation
KOSTEN_VERLOSKUNDIGE_ZORG is highly overall correlated with KOSTEN_KRAAMZORGHigh correlation
KOSTEN_VERPLEGING_EN_VERZORGING is highly overall correlated with KOSTEN_FARMACIE and 6 other fieldsHigh correlation
KOSTEN_ZIEKENVERVOER_LIGGEND is highly overall correlated with KOSTEN_FARMACIE and 9 other fieldsHigh correlation
KOSTEN_ZIEKENVERVOER_ZITTEND is highly overall correlated with KOSTEN_FARMACIE and 1 other fieldsHigh correlation
AANTAL_BSN is highly skewed (γ1 = 359.9627084) Skewed
AANTAL_VERZEKERDEJAREN is highly skewed (γ1 = 339.5691361) Skewed
KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG is highly skewed (γ1 = 52.17140102) Skewed
KOSTEN_FARMACIE is highly skewed (γ1 = 29.41423327) Skewed
KOSTEN_SPECIALISTISCHE_GGZ is highly skewed (γ1 = 27.03511978) Skewed
KOSTEN_HUISARTS_INSCHRIJFTARIEF is highly skewed (γ1 = 190.2163179) Skewed
KOSTEN_HUISARTS_CONSULT is highly skewed (γ1 = 44.70295717) Skewed
KOSTEN_HUISARTS_OVERIG is highly skewed (γ1 = 195.4210711) Skewed
KOSTEN_ZIEKENVERVOER_LIGGEND is highly skewed (γ1 = 80.99502686) Skewed
KOSTEN_GENERALISTISCHE_BASIS_GGZ is highly skewed (γ1 = 26.69994527) Skewed
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG is highly skewed (γ1 = 366.9142618) Skewed
KOSTEN_SPECIALISTISCHE_GGZ has 52814 (38.6%) zeros Zeros
KOSTEN_HUISARTS_MDZ has 11082 (8.1%) zeros Zeros
KOSTEN_HULPMIDDELEN has 6525 (4.8%) zeros Zeros
KOSTEN_MONDZORG has 27688 (20.2%) zeros Zeros
KOSTEN_PARAMEDISCHE_ZORG_FYSIOTHERAPIE has 29337 (21.4%) zeros Zeros
KOSTEN_PARAMEDISCHE_ZORG_OVERIG has 22856 (16.7%) zeros Zeros
KOSTEN_ZIEKENVERVOER_ZITTEND has 88328 (64.5%) zeros Zeros
KOSTEN_ZIEKENVERVOER_LIGGEND has 32887 (24.0%) zeros Zeros
KOSTEN_KRAAMZORG has 119707 (87.4%) zeros Zeros
KOSTEN_VERLOSKUNDIGE_ZORG has 118983 (86.9%) zeros Zeros
KOSTEN_GENERALISTISCHE_BASIS_GGZ has 75148 (54.9%) zeros Zeros
KOSTEN_LANGDURIGE_GGZ has 134601 (98.3%) zeros Zeros
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG has 53547 (39.1%) zeros Zeros
KOSTEN_EERSTELIJNS_ONDERSTEUNING has 58122 (42.5%) zeros Zeros
KOSTEN_GERIATRISCHE_REVALIDATIEZORG has 113073 (82.6%) zeros Zeros
KOSTEN_VERPLEGING_EN_VERZORGING has 63022 (46.0%) zeros Zeros
KOSTEN_OVERIG has 48825 (35.7%) zeros Zeros

Reproduction

Analysis started2024-10-29 15:17:11.045870
Analysis finished2024-10-29 15:18:29.481639
Duration1 minute and 18.44 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

GESLACHT
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size1.0 MiB
V
68671 
M
68244 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters136915
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 rowM
2nd rowM
3rd rowM
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
V 68671
50.2%
M 68244
49.8%
(Missing) 1
 
< 0.1%

Length

2024-10-29T15:18:29.566385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T15:18:29.669631image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
v 68671
50.2%
m 68244
49.8%

Most occurring characters

ValueCountFrequency (%)
V 68671
50.2%
M 68244
49.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 136915
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
V 68671
50.2%
M 68244
49.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 136915
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
V 68671
50.2%
M 68244
49.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 136915
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
V 68671
50.2%
M 68244
49.8%
Distinct91
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size1.0 MiB
2024-10-29T15:18:29.905843image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.8997334
Min length1

Characters and Unicode

Total characters260102
Distinct characters11
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 row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
54 1562
 
1.1%
48 1559
 
1.1%
57 1559
 
1.1%
52 1558
 
1.1%
55 1558
 
1.1%
50 1558
 
1.1%
47 1557
 
1.1%
51 1556
 
1.1%
60 1556
 
1.1%
49 1556
 
1.1%
Other values (81) 121336
88.6%
2024-10-29T15:18:30.310669image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 29124
11.2%
1 29067
11.2%
6 29022
11.2%
4 29012
11.2%
3 28759
11.1%
2 28743
11.1%
7 28500
11.0%
8 26575
10.2%
0 15142
5.8%
9 14724
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 260102
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 29124
11.2%
1 29067
11.2%
6 29022
11.2%
4 29012
11.2%
3 28759
11.1%
2 28743
11.1%
7 28500
11.0%
8 26575
10.2%
0 15142
5.8%
9 14724
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 260102
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 29124
11.2%
1 29067
11.2%
6 29022
11.2%
4 29012
11.2%
3 28759
11.1%
2 28743
11.1%
7 28500
11.0%
8 26575
10.2%
0 15142
5.8%
9 14724
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 260102
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 29124
11.2%
1 29067
11.2%
6 29022
11.2%
4 29012
11.2%
3 28759
11.1%
2 28743
11.1%
7 28500
11.0%
8 26575
10.2%
0 15142
5.8%
9 14724
5.7%

POSTCODE_3
Real number (ℝ)

Distinct794
Distinct (%)0.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean541.17856
Minimum0
Maximum999
Zeros182
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2024-10-29T15:18:30.454818image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile144
Q1318
median539
Q3763
95-th percentile955
Maximum999
Range999
Interquartile range (IQR)445

Descriptive statistics

Standard deviation258.22974
Coefficient of variation (CV)0.47716181
Kurtosis-1.1671681
Mean541.17856
Median Absolute Deviation (MAD)223
Skewness0.035766181
Sum74095462
Variance66682.597
MonotonicityNot monotonic
2024-10-29T15:18:30.607433image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
998 182
 
0.1%
993 182
 
0.1%
990 182
 
0.1%
135 182
 
0.1%
133 182
 
0.1%
132 182
 
0.1%
131 182
 
0.1%
127 182
 
0.1%
126 182
 
0.1%
125 182
 
0.1%
Other values (784) 135095
98.7%
ValueCountFrequency (%)
0 182
0.1%
101 182
0.1%
102 182
0.1%
103 182
0.1%
104 16
 
< 0.1%
105 182
0.1%
106 182
0.1%
107 182
0.1%
108 182
0.1%
109 182
0.1%
ValueCountFrequency (%)
999 166
0.1%
998 182
0.1%
997 172
0.1%
996 176
0.1%
995 180
0.1%
994 171
0.1%
993 182
0.1%
992 84
0.1%
991 174
0.1%
990 182
0.1%

AANTAL_BSN
Real number (ℝ)

High correlation  Skewed 

Distinct1126
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.83875
Minimum10
Maximum356551
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2024-10-29T15:18:30.747162image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile16
Q141
median82
Q3163
95-th percentile381
Maximum356551
Range356541
Interquartile range (IQR)122

Descriptive statistics

Standard deviation972.15351
Coefficient of variation (CV)7.6045294
Kurtosis131972.19
Mean127.83875
Median Absolute Deviation (MAD)50
Skewness359.96271
Sum17503170
Variance945082.45
MonotonicityNot monotonic
2024-10-29T15:18:30.898882image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 1161
 
0.8%
21 1148
 
0.8%
29 1147
 
0.8%
22 1140
 
0.8%
28 1140
 
0.8%
20 1137
 
0.8%
18 1133
 
0.8%
33 1128
 
0.8%
35 1127
 
0.8%
30 1123
 
0.8%
Other values (1116) 125532
91.7%
ValueCountFrequency (%)
10 1022
0.7%
11 1034
0.8%
12 1078
0.8%
13 1066
0.8%
14 1066
0.8%
15 1081
0.8%
16 1095
0.8%
17 1102
0.8%
18 1133
0.8%
19 1161
0.8%
ValueCountFrequency (%)
356551 1
< 0.1%
2311 1
< 0.1%
2292 1
< 0.1%
2232 1
< 0.1%
2130 1
< 0.1%
2125 1
< 0.1%
2097 1
< 0.1%
2020 1
< 0.1%
2019 1
< 0.1%
1982 1
< 0.1%

AANTAL_VERZEKERDEJAREN
Real number (ℝ)

High correlation  Skewed 

Distinct34846
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.52548
Minimum3.09
Maximum196219.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2024-10-29T15:18:31.051812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.09
5-th percentile15.27
Q140
median81
Q3160.34
95-th percentile376.0325
Maximum196219.74
Range196216.65
Interquartile range (IQR)120.34

Descriptive statistics

Standard deviation545.37184
Coefficient of variation (CV)4.3796005
Kurtosis122082.86
Mean124.52548
Median Absolute Deviation (MAD)50
Skewness339.56914
Sum17049530
Variance297430.44
MonotonicityNot monotonic
2024-10-29T15:18:31.337587image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 749
 
0.5%
11 738
 
0.5%
19 718
 
0.5%
21 710
 
0.5%
15 707
 
0.5%
10 704
 
0.5%
16 703
 
0.5%
14 701
 
0.5%
13 689
 
0.5%
18 682
 
0.5%
Other values (34836) 129815
94.8%
ValueCountFrequency (%)
3.09 1
< 0.1%
3.95 1
< 0.1%
4.1 1
< 0.1%
4.33 1
< 0.1%
4.47 1
< 0.1%
4.55 1
< 0.1%
4.6 1
< 0.1%
4.7 1
< 0.1%
4.71 1
< 0.1%
4.75 2
< 0.1%
ValueCountFrequency (%)
196219.74 1
< 0.1%
2220.62 1
< 0.1%
2191.36 1
< 0.1%
2130.01 1
< 0.1%
2047.13 1
< 0.1%
2044.54 1
< 0.1%
2015.59 1
< 0.1%
1935.15 1
< 0.1%
1920.07 1
< 0.1%
1888.45 1
< 0.1%

KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG
Real number (ℝ)

High correlation  Skewed 

Distinct136549
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean165218.8
Minimum-7777
Maximum46978767
Zeros19
Zeros (%)< 0.1%
Negative1
Negative (%)< 0.1%
Memory size1.0 MiB
2024-10-29T15:18:31.491888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-7777
5-th percentile6303.62
Q132441.967
median88496.32
Q3215527.94
95-th percentile576265.55
Maximum46978767
Range46986544
Interquartile range (IQR)183085.97

Descriptive statistics

Standard deviation246118.06
Coefficient of variation (CV)1.4896492
Kurtosis9567.9535
Mean165218.8
Median Absolute Deviation (MAD)68699.18
Skewness52.171401
Sum2.2621098 × 1010
Variance6.0574099 × 1010
MonotonicityNot monotonic
2024-10-29T15:18:31.640878image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
< 0.1%
10727.73 2
 
< 0.1%
84062.81 2
 
< 0.1%
47971.66 2
 
< 0.1%
12525.43 2
 
< 0.1%
14471.36 2
 
< 0.1%
14029.62 2
 
< 0.1%
12914.14 2
 
< 0.1%
174692.61 2
 
< 0.1%
9696.57 2
 
< 0.1%
Other values (136539) 136879
> 99.9%
ValueCountFrequency (%)
-7777 1
 
< 0.1%
0 19
< 0.1%
12.52 1
 
< 0.1%
23 1
 
< 0.1%
25.71 1
 
< 0.1%
31.35 1
 
< 0.1%
32.76 1
 
< 0.1%
38.36 1
 
< 0.1%
39.38 1
 
< 0.1%
48.52 1
 
< 0.1%
ValueCountFrequency (%)
46978766.76 1
< 0.1%
4462180.08 1
< 0.1%
4142347.5 1
< 0.1%
3839430.5 1
< 0.1%
3616606.71 1
< 0.1%
3608489.09 1
< 0.1%
3254328.15 1
< 0.1%
3132180.45 1
< 0.1%
3086536 1
< 0.1%
2956602.55 1
< 0.1%

KOSTEN_FARMACIE
Real number (ℝ)

High correlation  Skewed 

Distinct134842
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33974.632
Minimum14.11
Maximum8368957.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2024-10-29T15:18:31.787051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum14.11
5-th percentile906.0675
Q14957.82
median15929.88
Q343154.03
95-th percentile125922.99
Maximum8368957.1
Range8368943
Interquartile range (IQR)38196.21

Descriptive statistics

Standard deviation54331.6
Coefficient of variation (CV)1.5991814
Kurtosis4067.4161
Mean33974.632
Median Absolute Deviation (MAD)13287.735
Skewness29.414233
Sum4.6516707 × 109
Variance2.9519227 × 109
MonotonicityNot monotonic
2024-10-29T15:18:31.934574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2848.8 3
 
< 0.1%
972.28 3
 
< 0.1%
3227.15 3
 
< 0.1%
2911.12 3
 
< 0.1%
28952.86 3
 
< 0.1%
6985.33 3
 
< 0.1%
7758.7 3
 
< 0.1%
1991.88 3
 
< 0.1%
2306.41 3
 
< 0.1%
1102.83 3
 
< 0.1%
Other values (134832) 136886
> 99.9%
ValueCountFrequency (%)
14.11 1
< 0.1%
14.14 1
< 0.1%
14.16 1
< 0.1%
14.32 1
< 0.1%
14.98 1
< 0.1%
15 1
< 0.1%
16.26 1
< 0.1%
16.32 1
< 0.1%
16.83 1
< 0.1%
19.87 1
< 0.1%
ValueCountFrequency (%)
8368957.11 1
< 0.1%
1231629.74 1
< 0.1%
1166271.42 1
< 0.1%
1147381.84 1
< 0.1%
1015539.56 1
< 0.1%
970984.66 1
< 0.1%
927593.72 1
< 0.1%
923080.7 1
< 0.1%
904922.34 1
< 0.1%
892637.9 1
< 0.1%

KOSTEN_SPECIALISTISCHE_GGZ
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct69094
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21524.512
Minimum-66348.6
Maximum7669881.8
Zeros52814
Zeros (%)38.6%
Negative5
Negative (%)< 0.1%
Memory size1.0 MiB
2024-10-29T15:18:32.078971image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-66348.6
5-th percentile0
Q10
median2561.32
Q319746.377
95-th percentile108695.9
Maximum7669881.8
Range7736230.4
Interquartile range (IQR)19746.377

Descriptive statistics

Standard deviation51905.62
Coefficient of variation (CV)2.4114655
Kurtosis3468.2366
Mean21524.512
Median Absolute Deviation (MAD)2561.32
Skewness27.03512
Sum2.9470501 × 109
Variance2.6941934 × 109
MonotonicityNot monotonic
2024-10-29T15:18:32.239836image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52814
38.6%
616.73 181
 
0.1%
1109.94 163
 
0.1%
2502.32 145
 
0.1%
1028.98 125
 
0.1%
2500.54 106
 
0.1%
2450.72 98
 
0.1%
585.66 93
 
0.1%
635.02 88
 
0.1%
320.74 87
 
0.1%
Other values (69084) 83016
60.6%
ValueCountFrequency (%)
-66348.6 1
 
< 0.1%
-56879.22 1
 
< 0.1%
-28221.91 1
 
< 0.1%
-17118.93 1
 
< 0.1%
-15556.56 1
 
< 0.1%
0 52814
38.6%
26.95 1
 
< 0.1%
95.8 1
 
< 0.1%
99.88 1
 
< 0.1%
102.26 1
 
< 0.1%
ValueCountFrequency (%)
7669881.83 1
< 0.1%
1160281.64 1
< 0.1%
910582.08 1
< 0.1%
890716.44 1
< 0.1%
857109.74 1
< 0.1%
847733.64 1
< 0.1%
830797.11 1
< 0.1%
810819 1
< 0.1%
808372.35 1
< 0.1%
775105.51 1
< 0.1%

KOSTEN_HUISARTS_INSCHRIJFTARIEF
Real number (ℝ)

High correlation  Skewed 

Distinct35375
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8055.8898
Minimum59.96
Maximum3973069.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2024-10-29T15:18:32.399032image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum59.96
5-th percentile1074
Q12698.2
median5456.36
Q310611.45
95-th percentile23699.993
Maximum3973069.5
Range3973009.5
Interquartile range (IQR)7913.25

Descriptive statistics

Standard deviation13390.557
Coefficient of variation (CV)1.662207
Kurtosis56149.538
Mean8055.8898
Median Absolute Deviation (MAD)3327.78
Skewness190.21632
Sum1.1029802 × 109
Variance1.7930701 × 108
MonotonicityNot monotonic
2024-10-29T15:18:32.561468image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/