Overview

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

Categorical2
Numeric25

Alerts

LEEFTIJDSKLASSE has a high cardinality: 91 distinct valuesHigh cardinality
AANTAL_BSN is highly overall correlated with AANTAL_VERZEKERDEJAREN and 13 other fieldsHigh correlation
AANTAL_VERZEKERDEJAREN is highly overall correlated with AANTAL_BSN and 14 other fieldsHigh correlation
KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG is highly overall correlated with AANTAL_BSN and 14 other fieldsHigh correlation
KOSTEN_FARMACIE is highly overall correlated with AANTAL_BSN and 12 other fieldsHigh correlation
KOSTEN_SPECIALISTISCHE_GGZ is highly overall correlated with AANTAL_BSN and 4 other fieldsHigh correlation
KOSTEN_HUISARTS_INSCHRIJFTARIEF is highly overall correlated with AANTAL_BSN and 16 other fieldsHigh correlation
KOSTEN_HUISARTS_CONSULT is highly overall correlated with AANTAL_BSN and 14 other fieldsHigh correlation
KOSTEN_HUISARTS_MDZ is highly overall correlated with KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG and 7 other fieldsHigh correlation
KOSTEN_HUISARTS_OVERIG is highly overall correlated with AANTAL_BSN and 14 other fieldsHigh correlation
KOSTEN_HULPMIDDELEN is highly overall correlated with AANTAL_BSN and 11 other fieldsHigh correlation
KOSTEN_MONDZORG is highly overall correlated with AANTAL_VERZEKERDEJAREN and 3 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_ZIEKENVERVOER_ZITTEND is highly overall correlated with KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG and 1 other fieldsHigh correlation
KOSTEN_ZIEKENVERVOER_LIGGEND is highly overall correlated with KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG and 9 other fieldsHigh correlation
KOSTEN_KRAAMZORG is highly overall correlated with KOSTEN_VERLOSKUNDIGE_ZORGHigh correlation
KOSTEN_VERLOSKUNDIGE_ZORG is highly overall correlated with KOSTEN_KRAAMZORGHigh correlation
KOSTEN_GENERALISTISCHE_BASIS_GGZ is highly overall correlated with AANTAL_BSN and 2 other fieldsHigh correlation
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG is highly overall correlated with AANTAL_BSN and 6 other fieldsHigh correlation
KOSTEN_GERIATRISCHE_REVALIDATIEZORG is highly overall correlated with KOSTEN_ZIEKENVERVOER_LIGGEND and 1 other fieldsHigh correlation
KOSTEN_VERPLEGING_EN_VERZORGING is highly overall correlated with KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG and 6 other fieldsHigh correlation
KOSTEN_OVERIG is highly overall correlated with KOSTEN_MEDISCH_SPECIALISTISCHE_ZORG and 6 other fieldsHigh correlation
GESLACHT is highly overall correlated with AANTAL_BSN and 5 other fieldsHigh correlation
LEEFTIJDSKLASSE is highly overall correlated with AANTAL_BSN and 5 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%) zerosZeros
KOSTEN_HUISARTS_MDZ has 11082 (8.1%) zerosZeros
KOSTEN_HULPMIDDELEN has 6525 (4.8%) zerosZeros
KOSTEN_MONDZORG has 27688 (20.2%) zerosZeros
KOSTEN_PARAMEDISCHE_ZORG_FYSIOTHERAPIE has 29337 (21.4%) zerosZeros
KOSTEN_PARAMEDISCHE_ZORG_OVERIG has 22856 (16.7%) zerosZeros
KOSTEN_ZIEKENVERVOER_ZITTEND has 88328 (64.5%) zerosZeros
KOSTEN_ZIEKENVERVOER_LIGGEND has 32887 (24.0%) zerosZeros
KOSTEN_KRAAMZORG has 119707 (87.4%) zerosZeros
KOSTEN_VERLOSKUNDIGE_ZORG has 118983 (86.9%) zerosZeros
KOSTEN_GENERALISTISCHE_BASIS_GGZ has 75148 (54.9%) zerosZeros
KOSTEN_LANGDURIGE_GGZ has 134601 (98.3%) zerosZeros
KOSTEN_GRENSOVERSCHRIJDENDE_ZORG has 53547 (39.1%) zerosZeros
KOSTEN_EERSTELIJNS_ONDERSTEUNING has 58122 (42.5%) zerosZeros
KOSTEN_GERIATRISCHE_REVALIDATIEZORG has 113073 (82.6%) zerosZeros
KOSTEN_VERPLEGING_EN_VERZORGING has 63022 (46.0%) zerosZeros
KOSTEN_OVERIG has 48825 (35.7%) zerosZeros

Reproduction

Analysis started2023-01-25 14:27:30.198418
Analysis finished2023-01-25 14:29:11.007915
Duration1 minute and 40.81 seconds
Software versionpandas-profiling v0.0.dev0
Download configurationconfig.json

Variables

GESLACHT
Categorical

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

2023-01-25T14:29:11.063245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-01-25T14:29:11.181195image/svg+xmlMatplotlib v3.6.3, 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 (%)
Uppercase Letter 136915
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Latin 136915
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
ASCII 136915
100.0%

Most frequent character per block

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

LEEFTIJDSKLASSE
Categorical

HIGH CARDINALITY  HIGH CORRELATION 

Distinct91
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size1.0 MiB
54
 
1562
57
 
1559
48
 
1559
50
 
1558
55
 
1558
Other values (86)
129119 

Length

Max length3
Median length2
Mean length1.8997334
Min length1

Characters and Unicode

Total characters260102
Distinct characters11
Distinct categories2 ?
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

Common Values

ValueCountFrequency (%)
54 1562
 
1.1%
57 1559
 
1.1%
48 1559
 
1.1%
50 1558
 
1.1%
55 1558
 
1.1%
52 1558
 
1.1%
47 1557
 
1.1%
60 1556
 
1.1%
51 1556
 
1.1%
49 1556
 
1.1%
Other values (81) 121336
88.6%

Length

2023-01-25T14:29:11.288777image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
54 1562
 
1.1%
48 1559
 
1.1%
57 1559
 
1.1%
50 1558
 
1.1%
52 1558
 
1.1%
55 1558
 
1.1%
47 1557
 
1.1%
60 1556
 
1.1%
51 1556
 
1.1%
49 1556
 
1.1%
Other values (81) 121336
88.6%

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 (%)
Decimal Number 258668
99.4%
Math Symbol 1434
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 29124
11.3%
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
10.3%
0 15142
5.9%
9 14724
5.7%
Math Symbol
ValueCountFrequency (%)
+ 1434
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 260102
100.0%

Most frequent character per script

Common
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 (%)
ASCII 260102
100.0%

Most frequent character per block

ASCII
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
2023-01-25T14:29:11.454379image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:11.601413image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
487 182
 
0.1%
721 182
 
0.1%
947 182
 
0.1%
723 182
 
0.1%
462 182
 
0.1%
461 182
 
0.1%
724 182
 
0.1%
725 182
 
0.1%
456 182
 
0.1%
727 182
 
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
2023-01-25T14:29:11.744319image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:11.887511image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 1161
 
0.8%
21 1148
 
0.8%
29 1147
 
0.8%
28 1140
 
0.8%
22 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
2023-01-25T14:29:12.041908image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:12.191226image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:12.345188image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:12.490052image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
< 0.1%
9678.78 2
 
< 0.1%
178377 2
 
< 0.1%
10727.73 2
 
< 0.1%
47971.66 2
 
< 0.1%
14471.36 2
 
< 0.1%
12525.43 2
 
< 0.1%
14029.62 2
 
< 0.1%
12914.14 2
 
< 0.1%
174692.61 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
2023-01-25T14:29:12.765370image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:12.907172image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1102.83 3
 
< 0.1%
913.71 3
 
< 0.1%
2911.12 3
 
< 0.1%
7758.7 3
 
< 0.1%
1991.88 3
 
< 0.1%
263.26 3
 
< 0.1%
2217.62 3
 
< 0.1%
6247.63 3
 
< 0.1%
15623.32 3
 
< 0.1%
2447.93 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
2023-01-25T14:29:13.052260image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:13.201284image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:13.364791image/svg+xmlMatplotlib v3.6.3, 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
2023-01-25T14:29:13.518502image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
719.52 529
 
0.4%
659.56 488
 
0.4%
1259.16 483
 
0.4%
1019.32 477
 
0.3%
1139.24 474
 
0.3%
1199.2 469
 
0.3%
959.36 465
 
0.3%
899.4 453
 
0.3%
1319.12 452
 
0.3%
599.6 446
 
0.3%
Other values (35365) 132180
96.5%
ValueCountFrequency (%)
59.96 1
 
< 0.1%
104.93 1
 
< 0.1%
149.9 2
 
< 0.1%
164.89 8
< 0.1%
179.88 6
< 0.1%
194.87 7
< 0.1%
196.54 1
 
< 0.1%
209.86 11
< 0.1%
211.53 1
 
< 0.1%
224.85 6
< 0.1%
ValueCountFrequency (%)
3973069.45 1
< 0.1%
133923.66 1
< 0.1%
130108.5 1
< 0.1%
127593.25 1
< 0.1%
121932.84 1
< 0.1%
119787.76 1
< 0.1%
118717.95 1
< 0.1%
116719.14 1
< 0.1%
109312.39 1
< 0.1%
108843.81 1
< 0.1%

KOSTEN_HUISARTS_CONSULT
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct95969
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5202.9354
Minimum0
Maximum1261062.7
Zeros38
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2023-01-25T14:29:13.676380image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile429.185
Q11440.44
median3217.68
Q36764.4125
95-th percentile16346.91
Maximum1261062.7
Range1261062.7
Interquartile range (IQR)5323.9725

Descriptive statistics

Standard deviation7016.1062
Coefficient of variation (CV)1.34849
Kurtosis7525.289
Mean5202.9354
Median Absolute Deviation (MAD)2165.86
Skewness44.702957
Sum7.123651 × 108
Variance49225747
MonotonicityNot monotonic
2023-01-25T14:29:13.830549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
< 0.1%
198.49 22
 
< 0.1%
249.27 20
 
< 0.1%
272.36 20
 
< 0.1%
337 19
 
< 0.1%
355.45 19
 
< 0.1%
332.37 19
 
< 0.1%
226.2 19
 
< 0.1%
360.07 18
 
< 0.1%
300.04 18
 
< 0.1%
Other values (95959) 136704
99.8%
ValueCountFrequency (%)
0 38
< 0.1%
1.75 1
 
< 0.1%
2 1
 
< 0.1%
2.48 3
 
< 0.1%
2.92 1
 
< 0.1%
3.12 2
 
< 0.1%
3.4 1
 
< 0.1%
3.5 1
 
< 0.1%
3.8 1
 
< 0.1%
4.62 17
< 0.1%
ValueCountFrequency (%)
1261062.66 1
< 0.1%
236449.85 1
< 0.1%
166311.62 1
< 0.1%
150052.21 1
< 0.1%
144627.1 1
< 0.1%
144054.24 1
< 0.1%
137037.69 1
< 0.1%
118429.84 1
< 0.1%
118425.91 1
< 0.1%
117121.59 1
< 0.1%

KOSTEN_HUISARTS_MDZ
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102579
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4141.7536
Minimum0
Maximum793129.65
Zeros11082
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2023-01-25T14:29:13.984074image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1168.6
median1474.31
Q35177.05
95-th percentile17146.29
Maximum793129.65
Range793129.65
Interquartile range (IQR)5008.45

Descriptive statistics

Standard deviation7124.6244
Coefficient of variation (CV)1.7201951
Kurtosis1113.4781
Mean4141.7536
Median Absolute Deviation (MAD)1453.43
Skewness12.896496
Sum5.6707234 × 108
Variance50760272
MonotonicityNot monotonic
2023-01-25T14:29:14.130397image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11082
 
8.1%
0.22 177
 
0.1%
22.82 160
 
0.1%
0.33 157
 
0.1%
41.82 137
 
0.1%
414.48 124
 
0.1%
235 122
 
0.1%
0.26 121
 
0.1%
3.2 121
 
0.1%
0.55 112
 
0.1%
Other values (102569) 124603
91.0%
ValueCountFrequency (%)
0 11082
8.1%
0.11 68
 
< 0.1%
0.12 2
 
< 0.1%
0.13 26
 
< 0.1%
0.16 6
 
< 0.1%
0.17 6
 
< 0.1%
0.18 17
 
< 0.1%
0.2 2
 
< 0.1%
0.21 4
 
< 0.1%
0.22 177
 
0.1%
ValueCountFrequency (%)
793129.65 1
< 0.1%
148980.28 1
< 0.1%
134874.46 1
< 0.1%
116405.58 1
< 0.1%
107586.71 1
< 0.1%
98644.7 1
< 0.1%
96674.67 1
< 0.1%
87317.59 1
< 0.1%
84933.97 1
< 0.1%
81301.22 1
< 0.1%

KOSTEN_HUISARTS_OVERIG
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct128820
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6182.3304
Minimum-236.47
Maximum3402557.1
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)< 0.1%
Memory size1.0 MiB
2023-01-25T14:29:14.289688image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-236.47
5-th percentile725.16
Q11980.7975
median3995.355
Q37954.2975
95-th percentile18781
Maximum3402557.1
Range3402793.5
Interquartile range (IQR)5973.5

Descriptive statistics

Standard deviation11369.879
Coefficient of variation (CV)1.8390928
Kurtosis58158.583
Mean6182.3304
Median Absolute Deviation (MAD)2480.33
Skewness195.42107
Sum8.4645995 × 108
Variance1.2927416 × 108
MonotonicityNot monotonic
2023-01-25T14:29:14.435738image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3563.21 4
 
< 0.1%
3999 4
 
< 0.1%
4844.22 4
 
< 0.1%
2232.35 4
 
< 0.1%
1770.46 4
 
< 0.1%
2543.64 4
 
< 0.1%
1342.71 4
 
< 0.1%
1966.38 4
 
< 0.1%
4802.8 4
 
< 0.1%
1038.09 4
 
< 0.1%
Other values (128810) 136876
> 99.9%
ValueCountFrequency (%)
-236.47 1
< 0.1%
31.38 1
< 0.1%
70.32 1
< 0.1%
72.26 1
< 0.1%
82.15 1
< 0.1%
82.43 1
< 0.1%
84.36 1
< 0.1%
87.57 1
< 0.1%
87.71 1
< 0.1%
89.85 1
< 0.1%
ValueCountFrequency (%)
3402557.07 1
< 0.1%
192792.03 1
< 0.1%
161228.24 1
< 0.1%
143081.98 1
< 0.1%
137433.24 1
< 0.1%
136809.62 1
< 0.1%
117383.66 1
< 0.1%
111467.95 1
< 0.1%
110544.05 1
< 0.1%
107780.39 1
< 0.1%

KOSTEN_HULPMIDDELEN
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119605
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10638.331
Minimum0
Maximum1675945.1
Zeros6525
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2023-01-25T14:29:14.591653image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.4075
Q11028.1325
median5060.01
Q313791.972
95-th percentile39410.215
Maximum1675945.1
Range1675945.1
Interquartile range (IQR)12763.84

Descriptive statistics

Standard deviation16990.324
Coefficient of variation (CV)1.5970855
Kurtosis755.64183
Mean10638.331
Median Absolute Deviation (MAD)4713.01
Skewness12.122831
Sum1.4565577 × 109
Variance2.886711 × 108
MonotonicityNot monotonic
2023-01-25T14:29:14.735881image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6525
 
4.8%
29.1 838
 
0.6%
30.55 285
 
0.2%
23.5 273
 
0.2%
58.2 173
 
0.1%
30.71 141
 
0.1%
29.42 131
 
0.1%
46 126
 
0.1%
32.33 118
 
0.1%
59.65 86
 
0.1%
Other values (119595) 128220
93.6%
ValueCountFrequency (%)
0 6525
4.8%
0.18 1
 
< 0.1%
0.19 1
 
< 0.1%
0.2 3
 
< 0.1%
0.21 2
 
< 0.1%
0.24 1
 
< 0.1%
0.26 1
 
< 0.1%
0.27 2
 
< 0.1%
0.29 1
 
< 0.1%
0.31 2
 
< 0.1%
ValueCountFrequency (%)
1675945.12 1
< 0.1%
706827.19 1
< 0.1%
543395.35 1
< 0.1%
461447.34 1
< 0.1%
454747.29 1
< 0.1%
436153.56 1
< 0.1%
412941.03 1
< 0.1%
412223.07 1
< 0.1%
405370.9 1
< 0.1%
405047.17 1
< 0.1%

KOSTEN_MONDZORG
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct95906
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5379.1956
Minimum-444.08
Maximum938749.29
Zeros27688
Zeros (%)20.2%
Negative20
Negative (%)< 0.1%
Memory size1.0 MiB
2023-01-25T14:29:14.891113image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-444.08
5-th percentile0
Q1144.4775
median1653.65
Q35704.5075
95-th percentile22786.168
Maximum938749.29
Range939193.37
Interquartile range (IQR)5560.03

Descriptive statistics

Standard deviation11338.419
Coefficient of variation (CV)2.1078279
Kurtosis395.02844
Mean5379.1956
Median Absolute Deviation (MAD)1653.65
Skewness9.6610261
Sum7.3649794 × 108
Variance1.2855974 × 108
MonotonicityNot monotonic
2023-01-25T14:29:15.030142image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27688
 
20.2%
84.98 267
 
0.2%
20.44 222
 
0.2%
74.19 198
 
0.1%
40.88 128
 
0.1%
61.32 90
 
0.1%
59.53 79
 
0.1%
162.55 75
 
0.1%
120.3 75
 
0.1%
156.31 70
 
0.1%
Other values (95896) 108024
78.9%
ValueCountFrequency (%)
-444.08 1
 
< 0.1%
-441.9 1
 
< 0.1%
-83.5 13
 
< 0.1%
-82.88 1
 
< 0.1%
-48.02 1
 
< 0.1%
-46.85 1
 
< 0.1%
-35.75 1
 
< 0.1%
-15.03 1
 
< 0.1%
0 27688
20.2%
0.01 2
 
< 0.1%
ValueCountFrequency (%)
938749.29 1
< 0.1%
271261.5 1
< 0.1%
270464.06 1
< 0.1%
265425.58 1
< 0.1%
261961.26 1
< 0.1%
255148.13 1
< 0.1%
254949.17 1
< 0.1%
234917.24 1
< 0.1%
232668.48 1
< 0.1%
226923.05 1
< 0.1%

KOSTEN_PARAMEDISCHE_ZORG_FYSIOTHERAPIE
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76018
Distinct (%)55.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3625.3103
Minimum0
Maximum340085.91
Zeros29337
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2023-01-25T14:29:15.174018image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1171
median1768.425
Q34883.5
95-th percentile13733.587
Maximum340085.91
Range340085.91
Interquartile range (IQR)4712.5

Descriptive statistics

Standard deviation5253.3449
Coefficient of variation (CV)1.4490746
Kurtosis139.11742
Mean3625.3103
Median Absolute Deviation (MAD)1768.425
Skewness4.8664849
Sum4.9636298 × 108
Variance27597633
MonotonicityNot monotonic
2023-01-25T14:29:15.444951image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29337
 
21.4%
29.5 131
 
0.1%
28.5 119
 
0.1%
59 98
 
0.1%
85.5 97
 
0.1%
57 93
 
0.1%
88.5 91
 
0.1%
206.5 89
 
0.1%
32.75 89
 
0.1%
29.25 86
 
0.1%
Other values (76008) 106686
77.9%
ValueCountFrequency (%)
0 29337
21.4%
7.12 1
 
< 0.1%
9.05 1
 
< 0.1%
10 1
 
< 0.1%
12.65 1
 
< 0.1%
15 1
 
< 0.1%
16 2
 
< 0.1%
16.6 1
 
< 0.1%
17.5 1
 
< 0.1%
17.86 2
 
< 0.1%
ValueCountFrequency (%)
340085.91 1
< 0.1%
121763.26 1
< 0.1%
92821.35 1
< 0.1%
88719.4 1
< 0.1%
79761.98 1
< 0.1%
75395.72 1
< 0.1%
74152.85 1
< 0.1%
73666.86 1
< 0.1%
70915.7 1
< 0.1%
70697 1
< 0.1%

KOSTEN_PARAMEDISCHE_ZORG_OVERIG
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74302
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1736.7396
Minimum-46.02
Maximum258441.47
Zeros22856
Zeros (%)16.7%
Negative2
Negative (%)< 0.1%
Memory size1.0 MiB
2023-01-25T14:29:15.596337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-46.02
5-th percentile0
Q1122.045
median518.47
Q31514.2375
95-th percentile6435.145
Maximum258441.47
Range258487.49
Interquartile range (IQR)1392.1925

Descriptive statistics

Standard deviation5016.9489
Coefficient of variation (CV)2.8887169
Kurtosis247.18961
Mean1736.7396
Median Absolute Deviation (MAD)518.47
Skewness11.488014
Sum2.3778743 × 108
Variance25169776
MonotonicityNot monotonic
2023-01-25T14:29:15.744201image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22856
 
16.7%
176.88 512
 
0.4%
178.8 455
 
0.3%
186 422
 
0.3%
93 376
 
0.3%
88.44 375
 
0.3%
117.92 358
 
0.3%
180 344
 
0.3%
89.4 302
 
0.2%
124 300
 
0.2%
Other values (74292) 110616
80.8%
ValueCountFrequency (%)
-46.02 1
 
< 0.1%
-28.9 1
 
< 0.1%
0 22856
16.7%
3.88 1
 
< 0.1%
8.94 1
 
< 0.1%
9 3
 
< 0.1%
9.68 1
 
< 0.1%
9.92 3
 
< 0.1%
10 1
 
< 0.1%
10.22 1
 
< 0.1%
ValueCountFrequency (%)
258441.47 1
< 0.1%
219682.47 1
< 0.1%
207652.46 1
< 0.1%
184182.51 1
< 0.1%
168919.61 1
< 0.1%
165150.9 1
< 0.1%
154776.24 1
< 0.1%
142722.86 1
< 0.1%
141009.93 1
< 0.1%
131540.9 1
< 0.1%

KOSTEN_ZIEKENVERVOER_ZITTEND
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33337
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean760.08146
Minimum-114.92
Maximum136850
Zeros88328
Zeros (%)64.5%
Negative3
Negative (%)< 0.1%
Memory size1.0 MiB
2023-01-25T14:29:15.887337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-114.92
5-th percentile0
Q10
median0
Q3412.985
95-th percentile4466.335
Maximum136850
Range136964.92
Interquartile range (IQR)412.985

Descriptive statistics

Standard deviation2134.0316
Coefficient of variation (CV)2.8076354
Kurtosis162.84722
Mean760.08146
Median Absolute Deviation (MAD)0
Skewness7.0258945
Sum1.0406731 × 108
Variance4554091
MonotonicityNot monotonic
2023-01-25T14:29:16.025419image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 88328
64.5%
68 53
 
< 0.1%
0.8 46
 
< 0.1%
101.6 45
 
< 0.1%
28.8 42
 
< 0.1%
12 40
 
< 0.1%
236 39
 
< 0.1%
202.4 38
 
< 0.1%
404 35
 
< 0.1%
14.4 34
 
< 0.1%
Other values (33327) 48216
35.2%
ValueCountFrequency (%)
-114.92 1
 
< 0.1%
-100 1
 
< 0.1%
-39.12 1
 
< 0.1%
0 88328
64.5%
0.01 1
 
< 0.1%
0.04 1
 
< 0.1%
0.05 1
 
< 0.1%
0.06 1
 
< 0.1%
0.12 1
 
< 0.1%
0.15 2
 
< 0.1%
ValueCountFrequency (%)
136850 1
< 0.1%
46078.71 1
< 0.1%
42960.97 1
< 0.1%
41745.03 1
< 0.1%
41298.8 1
< 0.1%
40493.05 1
< 0.1%
39954.89 1
< 0.1%
39794.51 1
< 0.1%
39333.8 1
< 0.1%
39110.92 1
< 0.1%

KOSTEN_ZIEKENVERVOER_LIGGEND
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct34449
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4087.4063
Minimum0
Maximum1863993.8
Zeros32887
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size1.0 MiB
2023-01-25T14:29:16.180504image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1509.39
median1781.67
Q35094.565
95-th percentile15605.573
Maximum1863993.8
Range1863993.8
Interquartile range (IQR)4585.175

Descriptive statistics

Standard deviation8478.1134
Coefficient of variation (CV)2.0742037
Kurtosis16981.064
Mean4087.4063
Median Absolute Deviation (MAD)1781.67
Skewness80.995027
Sum5.5963132 × 108
Variance71878407
MonotonicityNot monotonic
2023-01-25T14:29:16.327119image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/