Overview

Dataset statistics

Number of variables15
Number of observations46265
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory3.4 MiB
Average record size in memory78.0 B

Variable types

Numeric2
Boolean6
DateTime1
Categorical6

Alerts

people_fully_vaccinated has constant value ""Constant
people_vaccinated has constant value ""Constant
positive_rate has constant value ""Constant
total_boosters has constant value ""Constant
total_vaccinations has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
raw_conditions has a high cardinality: 21203 distinct valuesHigh cardinality
condition__obesity is highly imbalanced (68.2%)Imbalance
serial is uniformly distributedUniform

Reproduction

Analysis started2023-05-04 15:10:46.655960
Analysis finished2023-05-04 15:10:50.490403
Duration3.83 seconds
Software versionydata-profiling vv4.1.2
Download configurationconfig.json

Variables

serial
Real number (ℝ)

Distinct46264
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23134.277
Minimum1
Maximum46266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size361.6 KiB
2023-05-04T15:10:50.574249image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2315.2
Q111568
median23134
Q334701
95-th percentile43953.8
Maximum46266
Range46265
Interquartile range (IQR)23133

Descriptive statistics

Standard deviation13356.137
Coefficient of variation (CV)0.57733106
Kurtosis-1.1999921
Mean23134.277
Median Absolute Deviation (MAD)11567
Skewness2.0580958 × 10-5
Sum1.0703073 × 109
Variance1.7838639 × 108
MonotonicityNot monotonic
2023-05-04T15:10:50.728027image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46265 2
 
< 0.1%
46217 1
 
< 0.1%
30857 1
 
< 0.1%
30848 1
 
< 0.1%
30849 1
 
< 0.1%
30850 1
 
< 0.1%
30851 1
 
< 0.1%
30853 1
 
< 0.1%
30844 1
 
< 0.1%
30854 1
 
< 0.1%
Other values (46254) 46254
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
46266 1
< 0.1%
46265 2
< 0.1%
46264 1
< 0.1%
46263 1
< 0.1%
46262 1
< 0.1%
46261 1
< 0.1%
46260 1
< 0.1%
46259 1
< 0.1%
46258 1
< 0.1%
46257 1
< 0.1%

age
Real number (ℝ)

Distinct95
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.892792
Minimum0
Maximum104
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size361.6 KiB
2023-05-04T15:10:50.882947image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51
Q166
median75
Q383
95-th percentile91
Maximum104
Range104
Interquartile range (IQR)17

Descriptive statistics

Standard deviation12.625904
Coefficient of variation (CV)0.17086788
Kurtosis0.88115696
Mean73.892792
Median Absolute Deviation (MAD)8
Skewness-0.77169218
Sum3418650
Variance159.41346
MonotonicityNot monotonic
2023-05-04T15:10:51.037050image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 1551
 
3.4%
79 1541
 
3.3%
78 1528
 
3.3%
81 1512
 
3.3%
83 1475
 
3.2%
77 1470
 
3.2%
73 1447
 
3.1%
82 1441
 
3.1%
76 1428
 
3.1%
84 1417
 
3.1%
Other values (85) 31455
68.0%
ValueCountFrequency (%)
0 5
< 0.1%
1 2
 
< 0.1%
2 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
14 1
 
< 0.1%
16 4
< 0.1%
17 2
 
< 0.1%
18 3
< 0.1%
19 7
< 0.1%
ValueCountFrequency (%)
104 2
 
< 0.1%
103 5
 
< 0.1%
102 6
 
< 0.1%
101 21
 
< 0.1%
100 23
 
< 0.1%
99 65
 
0.1%
98 96
 
0.2%
97 134
0.3%
96 192
0.4%
95 261
0.6%

condition__blood_pressure
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
True
30284 
False
15981 
ValueCountFrequency (%)
True 30284
65.5%
False 15981
34.5%
2023-05-04T15:10:51.171777image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

condition__diabetes
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
False
33001 
True
13264 
ValueCountFrequency (%)
False 33001
71.3%
True 13264
28.7%
2023-05-04T15:10:51.270986image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

condition__heart
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
False
31616 
True
14649 
ValueCountFrequency (%)
False 31616
68.3%
True 14649
31.7%
2023-05-04T15:10:51.369207image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

condition__lungs
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
False
40703 
True
5562 
ValueCountFrequency (%)
False 40703
88.0%
True 5562
 
12.0%
2023-05-04T15:10:51.467701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

condition__obesity
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
False
43598 
True
 
2667
ValueCountFrequency (%)
False 43598
94.2%
True 2667
 
5.8%
2023-05-04T15:10:51.563871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

estimated_date
Date

Distinct611
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
Minimum2020-03-20 00:00:00
Maximum2023-01-22 00:00:00
2023-05-04T15:10:51.680668image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-04T15:10:51.822696image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

is_male
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
True
23487 
False
22778 
ValueCountFrequency (%)
True 23487
50.8%
False 22778
49.2%
2023-05-04T15:10:51.947245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

people_fully_vaccinated
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
0
46265 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46265
Distinct characters1
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

Common Values

ValueCountFrequency (%)
0 46265
100.0%

Length

2023-05-04T15:10:52.046412image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-04T15:10:52.153908image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 46265
100.0%

Most occurring characters

ValueCountFrequency (%)
0 46265
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46265
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46265
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46265
100.0%

people_vaccinated
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
0
46265 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46265
Distinct characters1
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

Common Values

ValueCountFrequency (%)
0 46265
100.0%

Length

2023-05-04T15:10:52.238686image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-04T15:10:52.346818image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 46265
100.0%

Most occurring characters

ValueCountFrequency (%)
0 46265
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46265
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46265
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46265
100.0%

positive_rate
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
0.0
46265 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters138795
Distinct characters2
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 row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 46265
100.0%

Length

2023-05-04T15:10:52.430943image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-04T15:10:52.539586image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0.0 46265
100.0%

Most occurring characters

ValueCountFrequency (%)
0 92530
66.7%
. 46265
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92530
66.7%
Other Punctuation 46265
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92530
100.0%
Other Punctuation
ValueCountFrequency (%)
. 46265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138795
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92530
66.7%
. 46265
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92530
66.7%
. 46265
33.3%

raw_conditions
Categorical

Distinct21203
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
magasvérnyomás-betegség
 
2544
nem ismert alapbetegség
 
1950
magasvérnyomás-betegség, cukorbetegség
 
1456
magas vérnyomás
 
850
daganatos megbetegedés
 
672
Other values (21198)
38793 

Length

Max length434
Median length193
Mean length46.863071
Min length3

Characters and Unicode

Total characters2168120
Distinct characters56
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18742 ?
Unique (%)40.5%

Sample

1st rowmagasvérnyomás-betegség
2nd rowagyi infraktus
3rd rowcukorbetegség, hasi tályog
4th rowtüdő rosszindulatú daganata, májbetegség
5th rowtüdőfibrózis, cukorbetegség

Common Values

ValueCountFrequency (%)
magasvérnyomás-betegség 2544
 
5.5%
nem ismert alapbetegség 1950
 
4.2%
magasvérnyomás-betegség, cukorbetegség 1456
 
3.1%
magas vérnyomás 850
 
1.8%
daganatos megbetegedés 672
 
1.5%
magas vérnyomás, cukorbetegség 589
 
1.3%
adat feltöltés alatt 484
 
1.0%
cukorbetegség 478
 
1.0%
magasvérnyomás-betegség, iszkémiás szívbetegség 422
 
0.9%
cukorbetegség, magasvérnyomás-betegség 418
 
0.9%
Other values (21193) 36402
78.7%

Length

2023-05-04T15:10:52.662764image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
magasvérnyomás-betegség 20768
 
12.2%
cukorbetegség 13229
 
7.8%
magas 9770
 
5.8%
szívbetegség 9032
 
5.3%
vérnyomás 9011
 
5.3%
iszkémiás 5283
 
3.1%
veseelégtelenség 4603
 
2.7%
krónikus 4581
 
2.7%
tüdőbetegség 4201
 
2.5%
megbetegedés 3599
 
2.1%
Other values (3538) 85664
50.5%

Most occurring characters

ValueCountFrequency (%)
s 230510
 
10.6%
e 214040
 
9.9%
g 189067
 
8.7%
é 138215
 
6.4%
123457
 
5.7%
a 122791
 
5.7%
t 111853
 
5.2%
m 96965
 
4.5%
r 95320
 
4.4%
n 72309
 
3.3%
Other values (46) 773593
35.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1949662
89.9%
Space Separator 123477
 
5.7%
Other Punctuation 69221
 
3.2%
Dash Punctuation 25561
 
1.2%
Decimal Number 82
 
< 0.1%
Close Punctuation 57
 
< 0.1%
Open Punctuation 57
 
< 0.1%
Control 2
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 230510
 
11.8%
e 214040
 
11.0%
g 189067
 
9.7%
é 138215
 
7.1%
a 122791
 
6.3%
t 111853
 
5.7%
m 96965
 
5.0%
r 95320
 
4.9%
n 72309
 
3.7%
o 67590
 
3.5%
Other values (25) 611002
31.3%
Decimal Number
ValueCountFrequency (%)
2 63
76.8%
1 10
 
12.2%
0 4
 
4.9%
3 2
 
2.4%
4 1
 
1.2%
5 1
 
1.2%
9 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 69014
99.7%
. 169
 
0.2%
? 18
 
< 0.1%
; 16
 
< 0.1%
/ 2
 
< 0.1%
: 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
123457
> 99.9%
  20
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 56
98.2%
„ 1
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 25561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Control
ValueCountFrequency (%)
– 2
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1949662
89.9%
Common 218458
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 230510
 
11.8%
e 214040
 
11.0%
g 189067
 
9.7%
é 138215
 
7.1%
a 122791
 
6.3%
t 111853
 
5.7%
m 96965
 
5.0%
r 95320
 
4.9%
n 72309
 
3.7%
o 67590
 
3.5%
Other values (25) 611002
31.3%
Common
ValueCountFrequency (%)
123457
56.5%
, 69014
31.6%
- 25561
 
11.7%
. 169
 
0.1%
2 63
 
< 0.1%
) 57
 
< 0.1%
( 56
 
< 0.1%
  20
 
< 0.1%
? 18
 
< 0.1%
; 16
 
< 0.1%
Other values (11) 27
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1916060
88.4%
None 252058
 
11.6%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 230510
 
12.0%
e 214040
 
11.2%
g 189067
 
9.9%
123457
 
6.4%
a 122791
 
6.4%
t 111853
 
5.8%
m 96965
 
5.1%
r 95320
 
5.0%
n 72309
 
3.8%
, 69014
 
3.6%
Other values (32) 590734
30.8%
None
ValueCountFrequency (%)
é 138215
54.8%
á 54087
 
21.5%
í 22451
 
8.9%
ó 12450
 
4.9%
ü 8744
 
3.5%
ő 7805
 
3.1%
ö 3371
 
1.3%
û 2629
 
1.0%
ú 1987
 
0.8%
ű 297
 
0.1%
Other values (2) 22
 
< 0.1%
Punctuation
ValueCountFrequency (%)
„ 1
50.0%
” 1
50.0%

total_boosters
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
0
46265 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46265
Distinct characters1
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

Common Values

ValueCountFrequency (%)
0 46265
100.0%

Length

2023-05-04T15:10:52.791791image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-04T15:10:52.897015image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 46265
100.0%

Most occurring characters

ValueCountFrequency (%)
0 46265
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46265
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46265
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46265
100.0%

total_vaccinations
Categorical

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size361.6 KiB
0
46265 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters46265
Distinct characters1
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

Common Values

ValueCountFrequency (%)
0 46265
100.0%

Length

2023-05-04T15:10:52.984011image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-04T15:10:53.089722image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 46265
100.0%

Most occurring characters

ValueCountFrequency (%)
0 46265
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46265
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46265
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46265
100.0%

Interactions

2023-05-04T15:10:49.417380image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-04T15:10:49.176320image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-04T15:10:49.536905image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-05-04T15:10:49.296355image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2023-05-04T15:10:53.172822image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
serialagecondition__blood_pressurecondition__diabetescondition__heartcondition__lungscondition__obesityis_male
serial1.000-0.0320.0490.0340.0680.0580.0940.031
age-0.0321.0000.1820.1140.2000.0750.2110.226
condition__blood_pressure0.0490.1821.0000.1960.0880.0260.0530.070
condition__diabetes0.0340.1140.1961.0000.0200.0380.0850.000
condition__heart0.0680.2000.0880.0201.0000.0260.0290.023
condition__lungs0.0580.0750.0260.0380.0261.0000.0050.027
condition__obesity0.0940.2110.0530.0850.0290.0051.0000.009
is_male0.0310.2260.0700.0000.0230.0270.0091.000

Missing values

2023-05-04T15:10:49.737365image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-05-04T15:10:50.270968image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

serialagecondition__blood_pressurecondition__diabetescondition__heartcondition__lungscondition__obesityestimated_dateis_malepeople_fully_vaccinatedpeople_vaccinatedpositive_rateraw_conditionstotal_boosterstotal_vaccinations
04621790TrueFalseFalseFalseFalse2023-01-22True000.0magasvérnyomás-betegség00
14621887FalseFalseFalseFalseFalse2023-01-22False000.0agyi infraktus00
24621962FalseTrueFalseFalseFalse2023-01-22False000.0cukorbetegség, hasi tályog00
34622068FalseFalseFalseTrueFalse2023-01-22True000.0tüdő rosszindulatú daganata, májbetegség00
44622164FalseTrueFalseTrueFalse2023-01-22True000.0tüdőfibrózis, cukorbetegség00
54622282TrueFalseFalseFalseFalse2023-01-22False000.0magasvérnyomás-betegség00
64622379TrueFalseFalseFalseFalse2023-01-22True000.0magasvérnyomás-betegség00
74622463TrueFalseFalseFalseFalse2023-01-22True000.0daganatos-megbetegedés, érelmeszesedés, magasvérnyomás-betegség00
84622571TrueFalseFalseTrueFalse2023-01-22True000.0érelmeszesedés, magasvérnyomás-betegség, tüdő tumor, krónikus obstruktív tüdőbetegség00
94622675TrueTrueTrueFalseFalse2023-01-22True000.0magasvérnyomás-betegség, cukorbetegség, pajzsmirigy-alulmûködés, szívizomelhalás00
serialagecondition__blood_pressurecondition__diabetescondition__heartcondition__lungscondition__obesityestimated_dateis_malepeople_fully_vaccinatedpeople_vaccinatedpositive_rateraw_conditionstotal_boosterstotal_vaccinations
462554620778TrueFalseTrueFalseFalse2023-01-22False000.0iszkémiás szívbetegség, magasvérnyomás-betegség00
462564620888TrueFalseFalseFalseFalse2023-01-22False000.0magasvérnyomás-betegség00
462574620972TrueFalseTrueFalseFalse2023-01-22True000.0iszkémiás szívbetegség, magasvérnyomás-betegség00
462584621075TrueFalseTrueFalseFalse2023-01-22True000.0iszkémiás szívbetegség, magasvérnyomás betegség00
462594621181TrueTrueTrueFalseFalse2023-01-22False000.0cukorbetegség, magasvérnyomás-betegség, stroke, szívelégtelenség, vérszegénység, krónikus veseelégtelenség00
462604621270TrueFalseTrueTrueFalse2023-01-22False000.0szívelégtelenség, iszkémiás szívbetegség, magasvérnyomás-betegség, demencia, krónikus obstruktív tüdőbetegség00
462614621375FalseFalseFalseFalseFalse2023-01-22True000.0stroke, súlyos érszûkület00
462624621466TrueFalseFalseFalseFalse2023-01-22True000.0magasvérnyomás-betegség, daganatos megbetegedés00
462634621572FalseFalseTrueFalseFalse2023-01-22False000.0szívinfarktus, vérszegénység, leukémia00
462644621688TrueFalseFalseFalseFalse2023-01-22False000.0pajzsmirigy-betegség, magasvérnyomás-betegség, csontritkulás, veseelégtelenség00

Duplicate rows

Most frequently occurring

serialagecondition__blood_pressurecondition__diabetescondition__heartcondition__lungscondition__obesityestimated_dateis_malepeople_fully_vaccinatedpeople_vaccinatedpositive_rateraw_conditionstotal_boosterstotal_vaccinations# duplicates
04626586FalseFalseFalseFalseFalse2023-01-22False000.0asztma, vastagbélgyulladás002