Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations363659
Missing cells59122
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.8 MiB
Average record size in memory112.0 B

Variable types

Categorical3
DateTime1
Numeric9
Text1

Alerts

VERSIE has constant value "1.0"Constant
DATUM_BESTAND has constant value "2024-06-21"Constant
PEILDATUM has constant value "2024-06-01"Constant
AANTAL_PAT_PER_DIAG is highly overall correlated with AANTAL_SUBTRAJECT_PER_DIAGHigh correlation
AANTAL_PAT_PER_SPC is highly overall correlated with AANTAL_SUBTRAJECT_PER_SPC and 1 other fieldsHigh correlation
AANTAL_PAT_PER_ZPD is highly overall correlated with AANTAL_SUBTRAJECT_PER_ZPDHigh correlation
AANTAL_SUBTRAJECT_PER_DIAG is highly overall correlated with AANTAL_PAT_PER_DIAGHigh correlation
AANTAL_SUBTRAJECT_PER_SPC is highly overall correlated with AANTAL_PAT_PER_SPCHigh correlation
AANTAL_SUBTRAJECT_PER_ZPD is highly overall correlated with AANTAL_PAT_PER_ZPDHigh correlation
BEHANDELEND_SPECIALISME_CD is highly overall correlated with AANTAL_PAT_PER_SPCHigh correlation
GEMIDDELDE_VERKOOPPRIJS has 59122 (16.3%) missing valuesMissing
AANTAL_SUBTRAJECT_PER_ZPD is highly skewed (γ1 = 21.23686011)Skewed

Reproduction

Analysis started2024-07-15 20:39:18.134331
Analysis finished2024-07-15 20:39:37.035567
Duration18.9 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

VERSIE
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
1.0
363659 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1090977
Distinct characters3
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 row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 363659
100.0%

Length

2024-07-15T20:39:37.130504image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-15T20:39:37.271723image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 363659
100.0%

Most occurring characters

ValueCountFrequency (%)
1 363659
33.3%
. 363659
33.3%
0 363659
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1090977
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 363659
33.3%
. 363659
33.3%
0 363659
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1090977
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 363659
33.3%
. 363659
33.3%
0 363659
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1090977
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 363659
33.3%
. 363659
33.3%
0 363659
33.3%

DATUM_BESTAND
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2024-06-21
363659 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3636590
Distinct characters6
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 row2024-06-21
2nd row2024-06-21
3rd row2024-06-21
4th row2024-06-21
5th row2024-06-21

Common Values

ValueCountFrequency (%)
2024-06-21 363659
100.0%

Length

2024-07-15T20:39:37.419633image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-15T20:39:37.558342image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
2024-06-21 363659
100.0%

Most occurring characters

ValueCountFrequency (%)
2 1090977
30.0%
0 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 1090977
30.0%
0 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 1090977
30.0%
0 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 1090977
30.0%
0 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

PEILDATUM
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2024-06-01
363659 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3636590
Distinct characters6
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 row2024-06-01
2nd row2024-06-01
3rd row2024-06-01
4th row2024-06-01
5th row2024-06-01

Common Values

ValueCountFrequency (%)
2024-06-01 363659
100.0%

Length

2024-07-15T20:39:37.706741image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-15T20:39:37.845792image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
2024-06-01 363659
100.0%

Most occurring characters

ValueCountFrequency (%)
0 1090977
30.0%
2 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1090977
30.0%
2 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1090977
30.0%
2 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3636590
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1090977
30.0%
2 727318
20.0%
- 727318
20.0%
4 363659
 
10.0%
6 363659
 
10.0%
1 363659
 
10.0%

JAAR
Date

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
Minimum2012-01-01 00:00:00
Maximum2024-01-01 00:00:00
2024-07-15T20:39:37.973148image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-15T20:39:38.137711image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

BEHANDELEND_SPECIALISME_CD
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459.25334
Minimum301
Maximum8418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:38.315379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum301
5-th percentile302
Q1305
median313
Q3322
95-th percentile361
Maximum8418
Range8117
Interquartile range (IQR)17

Descriptive statistics

Standard deviation1069.5272
Coefficient of variation (CV)2.3288393
Kurtosis51.300322
Mean459.25334
Median Absolute Deviation (MAD)8
Skewness7.2962265
Sum1.6701161 × 108
Variance1143888.5
MonotonicityNot monotonic
2024-07-15T20:39:38.506735image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
305 50894
14.0%
313 47340
13.0%
303 41946
11.5%
330 28525
 
7.8%
316 24589
 
6.8%
308 19645
 
5.4%
306 15255
 
4.2%
324 14776
 
4.1%
301 14568
 
4.0%
304 11842
 
3.3%
Other values (18) 94279
25.9%
ValueCountFrequency (%)
301 14568
 
4.0%
302 8032
 
2.2%
303 41946
11.5%
304 11842
 
3.3%
305 50894
14.0%
306 15255
 
4.2%
307 6460
 
1.8%
308 19645
 
5.4%
310 4029
 
1.1%
313 47340
13.0%
ValueCountFrequency (%)
8418 5016
 
1.4%
8416 1425
 
0.4%
1900 245
 
0.1%
390 1014
 
0.3%
389 3821
 
1.1%
362 4556
 
1.3%
361 2660
 
0.7%
335 3641
 
1.0%
330 28525
7.8%
329 961
 
0.3%
Distinct1904
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:38.952418image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.3519286
Min length2

Characters and Unicode

Total characters1218959
Distinct characters25
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

Unique8 ?
Unique (%)< 0.1%

Sample

1st row07
2nd row02
3rd row16
4th row15
5th row12
ValueCountFrequency (%)
101 1565
 
0.4%
402 1508
 
0.4%
301 1473
 
0.4%
403 1466
 
0.4%
201 1404
 
0.4%
203 1370
 
0.4%
401 1229
 
0.3%
404 1222
 
0.3%
409 1195
 
0.3%
302 1177
 
0.3%
Other values (1894) 350050
96.3%
2024-07-15T20:39:39.586056image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 232938
19.1%
0 224357
18.4%
2 161521
13.3%
3 131847
10.8%
5 93986
7.7%
9 87818
 
7.2%
4 86302
 
7.1%
7 71819
 
5.9%
6 63463
 
5.2%
8 52597
 
4.3%
Other values (15) 12311
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1218959
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 232938
19.1%
0 224357
18.4%
2 161521
13.3%
3 131847
10.8%
5 93986
7.7%
9 87818
 
7.2%
4 86302
 
7.1%
7 71819
 
5.9%
6 63463
 
5.2%
8 52597
 
4.3%
Other values (15) 12311
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1218959
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 232938
19.1%
0 224357
18.4%
2 161521
13.3%
3 131847
10.8%
5 93986
7.7%
9 87818
 
7.2%
4 86302
 
7.1%
7 71819
 
5.9%
6 63463
 
5.2%
8 52597
 
4.3%
Other values (15) 12311
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1218959
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 232938
19.1%
0 224357
18.4%
2 161521
13.3%
3 131847
10.8%
5 93986
7.7%
9 87818
 
7.2%
4 86302
 
7.1%
7 71819
 
5.9%
6 63463
 
5.2%
8 52597
 
4.3%
Other values (15) 12311
 
1.0%

ZORGPRODUCT_CD
Real number (ℝ)

Distinct6273
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3965861 × 108
Minimum10501002
Maximum9.9841808 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:39.797848image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum10501002
5-th percentile28999040
Q199799061
median1.4959902 × 108
Q39.9000302 × 108
95-th percentile9.9051606 × 108
Maximum9.9841808 × 108
Range9.8791708 × 108
Interquartile range (IQR)8.9020396 × 108

Descriptive statistics

Standard deviation4.2863675 × 108
Coefficient of variation (CV)0.97493088
Kurtosis-1.7317419
Mean4.3965861 × 108
Median Absolute Deviation (MAD)1.1960001 × 108
Skewness0.47334058
Sum1.5988581 × 1014
Variance1.8372947 × 1017
MonotonicityNot monotonic
2024-07-15T20:39:40.153800image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
990004009 2655
 
0.7%
990004007 2605
 
0.7%
990003004 2505
 
0.7%
990004006 2093
 
0.6%
990356076 1912
 
0.5%
131999228 1850
 
0.5%
131999164 1816
 
0.5%
990356073 1772
 
0.5%
131999194 1606
 
0.4%
990003007 1603
 
0.4%
Other values (6263) 343242
94.4%
ValueCountFrequency (%)
10501002 9
< 0.1%
10501003 13
< 0.1%
10501004 13
< 0.1%
10501005 13
< 0.1%
10501007 3
 
< 0.1%
10501008 13
< 0.1%
10501010 13
< 0.1%
10501011 4
 
< 0.1%
11101002 11
< 0.1%
11101003 13
< 0.1%
ValueCountFrequency (%)
998418081 182
0.1%
998418080 169
< 0.1%
998418079 43
 
< 0.1%
998418077 10
 
< 0.1%
998418076 9
 
< 0.1%
998418075 7
 
< 0.1%
998418074 256
0.1%
998418073 250
0.1%
998418072 10
 
< 0.1%
998418071 10
 
< 0.1%

AANTAL_PAT_PER_ZPD
Real number (ℝ)

HIGH CORRELATION 

Distinct10765
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean518.0186
Minimum1
Maximum170178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:40.356945image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median13
Q3101
95-th percentile1749
Maximum170178
Range170177
Interquartile range (IQR)98

Descriptive statistics

Standard deviation3222.4851
Coefficient of variation (CV)6.2207904
Kurtosis413.24108
Mean518.0186
Median Absolute Deviation (MAD)12
Skewness16.789918
Sum1.8838212 × 108
Variance10384410
MonotonicityNot monotonic
2024-07-15T20:39:40.571031image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 61069
 
16.8%
2 29622
 
8.1%
3 19352
 
5.3%
4 14192
 
3.9%
5 11113
 
3.1%
6 9311
 
2.6%
7 7737
 
2.1%
8 6569
 
1.8%
9 5943
 
1.6%
10 5246
 
1.4%
Other values (10755) 193505
53.2%
ValueCountFrequency (%)
1 61069
16.8%
2 29622
8.1%
3 19352
 
5.3%
4 14192
 
3.9%
5 11113
 
3.1%
6 9311
 
2.6%
7 7737
 
2.1%
8 6569
 
1.8%
9 5943
 
1.6%
10 5246
 
1.4%
ValueCountFrequency (%)
170178 1
< 0.1%
165182 1
< 0.1%
163757 1
< 0.1%
155868 1
< 0.1%
154637 1
< 0.1%
154256 1
< 0.1%
148457 1
< 0.1%
144711 1
< 0.1%
118396 1
< 0.1%
115934 1
< 0.1%

AANTAL_SUBTRAJECT_PER_ZPD
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct11625
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean616.17669
Minimum1
Maximum240002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:40.781065image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median14
Q3110
95-th percentile2002.1
Maximum240002
Range240001
Interquartile range (IQR)107

Descriptive statistics

Standard deviation4171.7285
Coefficient of variation (CV)6.7703446
Kurtosis712.16297
Mean616.17669
Median Absolute Deviation (MAD)13
Skewness21.23686
Sum2.240782 × 108
Variance17403319
MonotonicityNot monotonic
2024-07-15T20:39:40.993408image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 58799
 
16.2%
2 29112
 
8.0%
3 19168
 
5.3%
4 13949
 
3.8%
5 11046
 
3.0%
6 9269
 
2.5%
7 7689
 
2.1%
8 6487
 
1.8%
9 5876
 
1.6%
10 5264
 
1.4%
Other values (11615) 197000
54.2%
ValueCountFrequency (%)
1 58799
16.2%
2 29112
8.0%
3 19168
 
5.3%
4 13949
 
3.8%
5 11046
 
3.0%
6 9269
 
2.5%
7 7689
 
2.1%
8 6487
 
1.8%
9 5876
 
1.6%
10 5264
 
1.4%
ValueCountFrequency (%)
240002 1
< 0.1%
232423 1
< 0.1%
231945 1
< 0.1%
230943 1
< 0.1%
227921 1
< 0.1%
227409 1
< 0.1%
226680 1
< 0.1%
223889 1
< 0.1%
218673 1
< 0.1%
216113 1
< 0.1%

AANTAL_PAT_PER_DIAG
Real number (ℝ)

HIGH CORRELATION 

Distinct9727
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7771.8252
Minimum1
Maximum242182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-07-15T20:39:41.192523image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile34
Q1376
median1688
Q36337
95-th percentile37206
Maximum242182
Range242181
Interquartile range (IQR)5961

Descriptive statistics

Standard deviation18152.681
Coefficient of variation (CV)2.3357037
Kurtosis34.648646
Mean7771.8252
Median Absolute Deviation (MAD)1558
Skewness5.0849733
Sum2.8262942 × 109
Variance3.2951983 × 108
MonotonicityNot monotonic
2024-07-15T20:39:41.402035image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 704
 
0.2%
8 649
 
0.2%
21 645
 
0.2%
7 642
 
0.2%
2 641
 
0.2%
5 635
 
0.2%
6 621
 
0.2%
1 612
 
0.2%
9 606
 
0.2%
17 601
 
0.2%
Other values (9717) 357303
98.3%