Overview

Brought to you by YData

Dataset statistics

Number of variables4
Number of observations67
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory33.9 B

Variable types

Categorical2
Text1
Numeric1

Alerts

Období has constant value "2021" Constant
Typ is highly overall correlated with ČástkaHigh correlation
Částka is highly overall correlated with TypHigh correlation
Kompletní jméno has unique values Unique

Reproduction

Analysis started2024-11-11 11:54:42.456498
Analysis finished2024-11-11 11:54:43.461273
Duration1 second
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

Období
Categorical

Constant 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size664.0 B
2021
67 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters268
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 row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 67
100.0%

Length

2024-11-11T12:54:43.564837image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-11T12:54:43.662446image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
2021 67
100.0%

Most occurring characters

ValueCountFrequency (%)
2 134
50.0%
0 67
25.0%
1 67
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 134
50.0%
0 67
25.0%
1 67
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 134
50.0%
0 67
25.0%
1 67
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 134
50.0%
0 67
25.0%
1 67
25.0%

Kompletní jméno
Text

Unique 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size664.0 B
2024-11-11T12:54:44.427838image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length39
Median length31
Mean length19.80597
Min length9

Characters and Unicode

Total characters1327
Distinct characters61
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

Unique67 ?
Unique (%)100.0%

Sample

1st rowArden Martin
2nd rowBenda Martin Mgr.
3rd rowBeránek Jaromír Mgr. Ing.
4th rowBílek Václav
5th rowBrož Lubomír Ing.
ValueCountFrequency (%)
ing 23
 
11.1%
mgr 17
 
8.2%
petr 6
 
2.9%
jiří 5
 
2.4%
judr 4
 
1.9%
jan 4
 
1.9%
ph.d 4
 
1.9%
pavel 4
 
1.9%
tomáš 4
 
1.9%
martin 4
 
1.9%
Other values (116) 133
63.9%
2024-11-11T12:54:44.966290image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
15.7%
a 95
 
7.2%
r 86
 
6.5%
. 76
 
5.7%
n 71
 
5.4%
e 58
 
4.4%
o 52
 
3.9%
k 42
 
3.2%
g 42
 
3.2%
M 41
 
3.1%
Other values (51) 556
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1327
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
208
 
15.7%
a 95
 
7.2%
r 86
 
6.5%
. 76
 
5.7%
n 71
 
5.4%
e 58
 
4.4%
o 52
 
3.9%
k 42
 
3.2%
g 42
 
3.2%
M 41
 
3.1%
Other values (51) 556
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1327
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
208
 
15.7%
a 95
 
7.2%
r 86
 
6.5%
. 76
 
5.7%
n 71
 
5.4%
e 58
 
4.4%
o 52
 
3.9%
k 42
 
3.2%
g 42
 
3.2%
M 41
 
3.1%
Other values (51) 556
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1327
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
208
 
15.7%
a 95
 
7.2%
r 86
 
6.5%
. 76
 
5.7%
n 71
 
5.4%
e 58
 
4.4%
o 52
 
3.9%
k 42
 
3.2%
g 42
 
3.2%
M 41
 
3.1%
Other values (51) 556
41.9%

Typ
Categorical

High correlation 

Distinct2
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size664.0 B
neuvolnění
45 
uvolnění
22 

Length

Max length10
Median length10
Mean length9.3432836
Min length8

Characters and Unicode

Total characters626
Distinct characters8
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 rowneuvolnění
2nd rowneuvolnění
3rd rowuvolnění
4th rowneuvolnění
5th rowneuvolnění

Common Values

ValueCountFrequency (%)
neuvolnění 45
67.2%
uvolnění 22
32.8%

Length

2024-11-11T12:54:45.135109image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-11T12:54:45.237247image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
neuvolnění 45
67.2%
uvolnění 22
32.8%

Most occurring characters

ValueCountFrequency (%)
n 179
28.6%
u 67
 
10.7%
v 67
 
10.7%
o 67
 
10.7%
l 67
 
10.7%
ě 67
 
10.7%
í 67
 
10.7%
e 45
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 626
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 179
28.6%
u 67
 
10.7%
v 67
 
10.7%
o 67
 
10.7%
l 67
 
10.7%
ě 67
 
10.7%
í 67
 
10.7%
e 45
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 626
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 179
28.6%
u 67
 
10.7%
v 67
 
10.7%
o 67
 
10.7%
l 67
 
10.7%
ě 67
 
10.7%
í 67
 
10.7%
e 45
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 626
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 179
28.6%
u 67
 
10.7%
v 67
 
10.7%
o 67
 
10.7%
l 67
 
10.7%
ě 67
 
10.7%
í 67
 
10.7%
e 45
 
7.2%

Částka
Real number (ℝ)

High correlation 

Distinct20
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean602637.97
Minimum70884
Maximum1723152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size664.0 B
2024-11-11T12:54:45.326082image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum70884
5-th percentile137911.5
Q1306216
median306216
Q31167792
95-th percentile1519008
Maximum1723152
Range1652268
Interquartile range (IQR)861576

Descriptive statistics

Standard deviation495656.95
Coefficient of variation (CV)0.8224788
Kurtosis-0.92264258
Mean602637.97
Median Absolute Deviation (MAD)18145
Skewness0.90478835
Sum40376744
Variance2.4567582 × 1011
MonotonicityNot monotonic
2024-11-11T12:54:45.793677image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
306216 24
35.8%
323220 9
 
13.4%
1178772 6
 
9.0%
1360944 6
 
9.0%
204144 4
 
6.0%
1519008 3
 
4.5%
1156812 2
 
3.0%
187132 1
 
1.5%
214144 1
 
1.5%
1039337 1
 
1.5%
Other values (10) 10
14.9%
ValueCountFrequency (%)
70884 1
 
1.5%
73908 1
 
1.5%
108276 1
 
1.5%
116817 1
 
1.5%
187132 1
 
1.5%
204144 4
 
6.0%
214144 1
 
1.5%
288071 1
 
1.5%
306216 24
35.8%
323220 9
 
13.4%
ValueCountFrequency (%)
1723152 1
 
1.5%
1529008 1
 
1.5%
1519008 3
4.5%
1360944 6
9.0%
1178772 6
9.0%
1156812 2
 
3.0%
1144879 1
 
1.5%
1039337 1
 
1.5%
357228 1
 
1.5%
340224 1
 
1.5%

Interactions

2024-11-11T12:54:42.759204image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-11-11T12:54:45.890328image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
TypČástka
Typ1.0000.928
Částka0.9281.000

Missing values

2024-11-11T12:54:43.310205image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-11T12:54:43.413564image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

ObdobíKompletní jménoTypČástka
02021Arden Martinneuvolnění306216
12021Benda Martin Mgr.neuvolnění357228
22021Beránek Jaromír Mgr. Ing.uvolnění1178772
32021Bílek Václavneuvolnění306216
42021Brož Lubomír Ing.neuvolnění306216
52021Burgerová Lenka Ing. arch. PhDr. Ph.D.neuvolnění323220
62021Čapková Mariana Ing.uvolnění1178772
72021Čižinský Jan Mgr.neuvolnění306216
82021Dlouhý Martin prof. Ing. Mgr. Dr. MSc.neuvolnění306216
92021Fifka Petr PharmDr.neuvolnění306216
ObdobíKompletní jménoTypČástka
572021Udženija Alexandra Ing.uvolnění1039337
582021Vodrážka David Ing.neuvolnění214144
592021Vondra Radek Mgr.neuvolnění323220
602021Vyhnánek Pavel M.A.uvolnění1519008
612021Wolf Januvolnění1156812
622021Zábranský Adamuvolnění1360944
632021Zajac Jiříneuvolnění306216
642021Zajíček Zdeněk Mgr.neuvolnění306216
652021Zelenka Paveluvolnění1178772
662021Zeman Petruvolnění1144879