Overview

Dataset statistics

Number of variables25
Number of observations684
Missing cells6906
Missing cells (%)40.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.9 KiB
Average record size in memory175.1 B

Variable types

DateTime1
Categorical9
Numeric8
Text5
Unsupported1
Boolean1

Alerts

Työkokemus is highly overall correlated with Kuukausipalkka and 2 other fieldsHigh correlation
Montako vuotta olet tehnyt laskuttavaa työtä alalla? is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Tuntilaskutus (ALV 0%, euroina) is highly overall correlated with Vuosilaskutus (ALV 0%, euroina) and 2 other fieldsHigh correlation
Vuosilaskutus (ALV 0%, euroina) is highly overall correlated with Tuntilaskutus (ALV 0%, euroina) and 1 other fieldsHigh correlation
Työaika is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Kuukausipalkka is highly overall correlated with Työkokemus and 4 other fieldsHigh correlation
Vuositulot is highly overall correlated with Työkokemus and 4 other fieldsHigh correlation
Kk-tulot is highly overall correlated with Työkokemus and 4 other fieldsHigh correlation
Oletko palkansaaja vai laskuttaja? is highly overall correlated with Montako vuotta olet tehnyt laskuttavaa työtä alalla? and 13 other fieldsHigh correlation
Sukupuoli is highly overall correlated with Tuntilaskutus (ALV 0%, euroina)High correlation
Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita? is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Mistä asiakkaat ovat? is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Kaupunki is highly overall correlated with Kuukausipalkka and 3 other fieldsHigh correlation
Millaisessa yrityksessä työskentelet is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Etä- vai lähityö is highly overall correlated with Oletko palkansaaja vai laskuttaja? and 1 other fieldsHigh correlation
Kilpailukykyinen is highly overall correlated with Oletko palkansaaja vai laskuttaja?High correlation
Etä is highly overall correlated with Oletko palkansaaja vai laskuttaja? and 1 other fieldsHigh correlation
Oletko palkansaaja vai laskuttaja? is highly imbalanced (53.3%)Imbalance
Sukupuoli is highly imbalanced (59.9%)Imbalance
Kaupunki is highly imbalanced (54.9%)Imbalance
Millaisessa yrityksessä työskentelet is highly imbalanced (51.7%)Imbalance
Etä- vai lähityö is highly imbalanced (58.2%)Imbalance
Sukupuoli has 53 (7.7%) missing valuesMissing
Montako vuotta olet tehnyt laskuttavaa työtä alalla? has 617 (90.2%) missing valuesMissing
Palvelut has 618 (90.4%) missing valuesMissing
Tuntilaskutus (ALV 0%, euroina) has 625 (91.4%) missing valuesMissing
Vuosilaskutus (ALV 0%, euroina) has 622 (90.9%) missing valuesMissing
Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita? has 616 (90.1%) missing valuesMissing
Mistä asiakkaat ovat? has 616 (90.1%) missing valuesMissing
Työpaikka has 537 (78.5%) missing valuesMissing
Kaupunki has 80 (11.7%) missing valuesMissing
Millaisessa yrityksessä työskentelet has 75 (11.0%) missing valuesMissing
Työaika has 72 (10.5%) missing valuesMissing
Rooli has 90 (13.2%) missing valuesMissing
Etä- vai lähityö has 71 (10.4%) missing valuesMissing
Kuukausipalkka has 73 (10.7%) missing valuesMissing
Vuositulot has 90 (13.2%) missing valuesMissing
Vapaa kuvaus kokonaiskompensaatiomallista has 498 (72.8%) missing valuesMissing
Kilpailukykyinen has 80 (11.7%) missing valuesMissing
Vapaa sana has 643 (94.0%) missing valuesMissing
Ideoita ensi vuoden kyselyyn has 653 (95.5%) missing valuesMissing
Etä has 80 (11.7%) missing valuesMissing
Kk-tulot has 90 (13.2%) missing valuesMissing
Timestamp has unique valuesUnique
Vapaa kuvaus kokonaiskompensaatiomallista is an unsupported type, check if it needs cleaning or further analysisUnsupported
Työkokemus has 13 (1.9%) zerosZeros

Reproduction

Analysis started2023-09-24 18:24:23.340758
Analysis finished2023-09-24 18:24:32.582980
Duration9.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Timestamp
Date

UNIQUE 

Distinct684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Minimum2022-09-26 16:35:50.002000
Maximum2022-10-10 07:49:49.204000
2023-09-24T18:24:32.669886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:32.836020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Oletko palkansaaja vai laskuttaja?
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Palkansaaja
616 
Laskuttaja
68 

Length

Max length11
Median length11
Mean length10.900585
Min length10

Characters and Unicode

Total characters7456
Distinct characters10
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 rowPalkansaaja
2nd rowPalkansaaja
3rd rowPalkansaaja
4th rowPalkansaaja
5th rowLaskuttaja

Common Values

ValueCountFrequency (%)
Palkansaaja 616
90.1%
Laskuttaja 68
 
9.9%

Length

2023-09-24T18:24:32.989533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:33.107384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
palkansaaja 616
90.1%
laskuttaja 68
 
9.9%

Most occurring characters

ValueCountFrequency (%)
a 3284
44.0%
k 684
 
9.2%
s 684
 
9.2%
j 684
 
9.2%
P 616
 
8.3%
l 616
 
8.3%
n 616
 
8.3%
t 136
 
1.8%
L 68
 
0.9%
u 68
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6772
90.8%
Uppercase Letter 684
 
9.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3284
48.5%
k 684
 
10.1%
s 684
 
10.1%
j 684
 
10.1%
l 616
 
9.1%
n 616
 
9.1%
t 136
 
2.0%
u 68
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
P 616
90.1%
L 68
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 7456
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3284
44.0%
k 684
 
9.2%
s 684
 
9.2%
j 684
 
9.2%
P 616
 
8.3%
l 616
 
8.3%
n 616
 
8.3%
t 136
 
1.8%
L 68
 
0.9%
u 68
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3284
44.0%
k 684
 
9.2%
s 684
 
9.2%
j 684
 
9.2%
P 616
 
8.3%
l 616
 
8.3%
n 616
 
8.3%
t 136
 
1.8%
L 68
 
0.9%
u 68
 
0.9%

Ikä
Categorical

Distinct8
Distinct (%)1.2%
Missing3
Missing (%)0.4%
Memory size1.2 KiB
33
202 
38
196 
28
135 
43
93 
48
25 
23
24 
53
 
5
> 55 v
 
1

Length

Max length6
Median length2
Mean length2.0058737
Min length2

Characters and Unicode

Total characters1366
Distinct characters8
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row33
2nd row33
3rd row33
4th row38
5th row28

Common Values

ValueCountFrequency (%)
33 202
29.5%
38 196
28.7%
28 135
19.7%
43 93
13.6%
48 25
 
3.7%
23 24
 
3.5%
53 5
 
0.7%
> 55 v 1
 
0.1%
(Missing) 3
 
0.4%

Length

2023-09-24T18:24:33.246321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:33.394168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
33 202
29.6%
38 196
28.7%
28 135
19.8%
43 93
13.6%
48 25
 
3.7%
23 24
 
3.5%
53 5
 
0.7%
1
 
0.1%
55 1
 
0.1%
v 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3 722
52.9%
8 356
26.1%
2 159
 
11.6%
4 118
 
8.6%
5 7
 
0.5%
2
 
0.1%
> 1
 
0.1%
v 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1362
99.7%
Space Separator 2
 
0.1%
Math Symbol 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 722
53.0%
8 356
26.1%
2 159
 
11.7%
4 118
 
8.7%
5 7
 
0.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
v 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1365
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 722
52.9%
8 356
26.1%
2 159
 
11.6%
4 118
 
8.6%
5 7
 
0.5%
2
 
0.1%
> 1
 
0.1%
Latin
ValueCountFrequency (%)
v 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 722
52.9%
8 356
26.1%
2 159
 
11.6%
4 118
 
8.6%
5 7
 
0.5%
2
 
0.1%
> 1
 
0.1%
v 1
 
0.1%

Sukupuoli
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)0.5%
Missing53
Missing (%)7.7%
Memory size948.0 B
mies
548 
nainen
72 
muu
 
11

Length

Max length6
Median length4
Mean length4.2107765
Min length3

Characters and Unicode

Total characters2657
Distinct characters7
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 rowmies
2nd rowmies
3rd rowmies
4th rowmies
5th rowmies

Common Values

ValueCountFrequency (%)
mies 548
80.1%
nainen 72
 
10.5%
muu 11
 
1.6%
(Missing) 53
 
7.7%

Length

2023-09-24T18:24:33.549219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:33.671400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mies 548
86.8%
nainen 72
 
11.4%
muu 11
 
1.7%

Most occurring characters

ValueCountFrequency (%)
i 620
23.3%
e 620
23.3%
m 559
21.0%
s 548
20.6%
n 216
 
8.1%
a 72
 
2.7%
u 22
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2657
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 620
23.3%
e 620
23.3%
m 559
21.0%
s 548
20.6%
n 216
 
8.1%
a 72
 
2.7%
u 22
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 2657
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 620
23.3%
e 620
23.3%
m 559
21.0%
s 548
20.6%
n 216
 
8.1%
a 72
 
2.7%
u 22
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 620
23.3%
e 620
23.3%
m 559
21.0%
s 548
20.6%
n 216
 
8.1%
a 72
 
2.7%
u 22
 
0.8%

Työkokemus
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)4.4%
Missing4
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean10.2
Minimum0
Maximum31
Zeros13
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:33.792821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median10
Q315
95-th percentile22
Maximum31
Range31
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.1659429
Coefficient of variation (CV)0.6045042
Kurtosis-0.29056756
Mean10.2
Median Absolute Deviation (MAD)5
Skewness0.53277455
Sum6936
Variance38.018851
MonotonicityNot monotonic
2023-09-24T18:24:33.936357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10 58
 
8.5%
5 54
 
7.9%
12 49
 
7.2%
15 49
 
7.2%
8 47
 
6.9%
7 43
 
6.3%
4 41
 
6.0%
6 35
 
5.1%
2 29
 
4.2%
14 26
 
3.8%
Other values (20) 249
36.4%
ValueCountFrequency (%)
0 13
 
1.9%
1 23
3.4%
2 29
4.2%
3 24
3.5%
4 41
6.0%
5 54
7.9%
6 35
5.1%
7 43
6.3%
8 47
6.9%
9 22
3.2%
ValueCountFrequency (%)
31 1
 
0.1%
28 1
 
0.1%
27 1
 
0.1%
26 2
 
0.3%
25 8
1.2%
24 5
 
0.7%
23 9
1.3%
22 17
2.5%
21 4
 
0.6%
20 19
2.8%

Montako vuotta olet tehnyt laskuttavaa työtä alalla?
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)26.9%
Missing617
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean3.5820896
Minimum0
Maximum16
Zeros3
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:34.067364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q11
median2
Q34
95-th percentile11.7
Maximum16
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7046214
Coefficient of variation (CV)1.0342068
Kurtosis2.4742083
Mean3.5820896
Median Absolute Deviation (MAD)1
Skewness1.731398
Sum240
Variance13.72422
MonotonicityNot monotonic
2023-09-24T18:24:34.203154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 18
 
2.6%
2 11
 
1.6%
4 7
 
1.0%
3 6
 
0.9%
5 4
 
0.6%
0 3
 
0.4%
1.5 3
 
0.4%
8 3
 
0.4%
0.5 2
 
0.3%
10 2
 
0.3%
Other values (8) 8
 
1.2%
(Missing) 617
90.2%
ValueCountFrequency (%)
0 3
 
0.4%
0.5 2
 
0.3%
1 18
2.6%
1.5 3
 
0.4%
2 11
1.6%
2.5 1
 
0.1%
3 6
 
0.9%
4 7
 
1.0%
5 4
 
0.6%
6 1
 
0.1%
ValueCountFrequency (%)
16 1
 
0.1%
15 1
 
0.1%
13 1
 
0.1%
12 1
 
0.1%
11 1
 
0.1%
10 2
0.3%
9 1
 
0.1%
8 3
0.4%
6 1
 
0.1%
5 4
0.6%

Palvelut
Text

MISSING 

Distinct52
Distinct (%)78.8%
Missing618
Missing (%)90.4%
Memory size5.5 KiB
2023-09-24T18:24:34.478536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length130
Median length50
Mean length27.606061
Min length3

Characters and Unicode

Total characters1822
Distinct characters53
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)75.8%

Sample

1st rowData-analytiikka, Arkkitehtuuri, Data Engineering,
2nd rowFullstack
3rd rowFull-stack developer ja arkkitehti
4th rowFull stack
5th rowDevausta ja projarointia
ValueCountFrequency (%)
full 37
 
16.3%
stack 37
 
16.3%
ja 13
 
5.7%
devops 9
 
4.0%
backend 7
 
3.1%
arkkitehtuuria 6
 
2.6%
6
 
2.6%
frontend 5
 
2.2%
softadevausta 5
 
2.2%
arkkitehtuuri 5
 
2.2%
Other values (73) 97
42.7%
2023-09-24T18:24:34.935661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 175
 
9.6%
t 167
 
9.2%
162
 
8.9%
l 127
 
7.0%
e 116
 
6.4%
k 109
 
6.0%
u 106
 
5.8%
s 100
 
5.5%
i 97
 
5.3%
o 67
 
3.7%
Other values (43) 596
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1502
82.4%
Space Separator 162
 
8.9%
Uppercase Letter 88
 
4.8%
Other Punctuation 58
 
3.2%
Dash Punctuation 8
 
0.4%
Decimal Number 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 175
11.7%
t 167
11.1%
l 127
 
8.5%
e 116
 
7.7%
k 109
 
7.3%
u 106
 
7.1%
s 100
 
6.7%
i 97
 
6.5%
o 67
 
4.5%
n 65
 
4.3%
Other values (17) 373
24.8%
Uppercase Letter
ValueCountFrequency (%)
F 37
42.0%
S 10
 
11.4%
D 8
 
9.1%
B 6
 
6.8%
A 4
 
4.5%
C 4
 
4.5%
E 3
 
3.4%
O 3
 
3.4%
W 3
 
3.4%
T 3
 
3.4%
Other values (5) 7
 
8.0%
Other Punctuation
ValueCountFrequency (%)
, 47
81.0%
. 4
 
6.9%
/ 4
 
6.9%
& 2
 
3.4%
: 1
 
1.7%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1590
87.3%
Common 232
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 175
 
11.0%
t 167
 
10.5%
l 127
 
8.0%
e 116
 
7.3%
k 109
 
6.9%
u 106
 
6.7%
s 100
 
6.3%
i 97
 
6.1%
o 67
 
4.2%
n 65
 
4.1%
Other values (32) 461
29.0%
Common
ValueCountFrequency (%)
162
69.8%
, 47
 
20.3%
- 8
 
3.4%
. 4
 
1.7%
/ 4
 
1.7%
& 2
 
0.9%
3 1
 
0.4%
( 1
 
0.4%
) 1
 
0.4%
+ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1799
98.7%
None 23
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 175
 
9.7%
t 167
 
9.3%
162
 
9.0%
l 127
 
7.1%
e 116
 
6.4%
k 109
 
6.1%
u 106
 
5.9%
s 100
 
5.6%
i 97
 
5.4%
o 67
 
3.7%
Other values (41) 573
31.9%
None
ValueCountFrequency (%)
ä 20
87.0%
ö 3
 
13.0%

Tuntilaskutus (ALV 0%, euroina)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)42.4%
Missing625
Missing (%)91.4%
Infinite0
Infinite (%)0.0%
Mean93.5
Minimum50
Maximum170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:35.095941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile65
Q180
median90
Q399.5
95-th percentile132
Maximum170
Range120
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation21.639085
Coefficient of variation (CV)0.23143406
Kurtosis2.6342677
Mean93.5
Median Absolute Deviation (MAD)10
Skewness1.3123042
Sum5516.5
Variance468.25
MonotonicityNot monotonic
2023-09-24T18:24:35.235123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
80 11
 
1.6%
90 10
 
1.5%
85 6
 
0.9%
120 5
 
0.7%
95 3
 
0.4%
105 2
 
0.3%
88 2
 
0.3%
150 2
 
0.3%
65 2
 
0.3%
98 1
 
0.1%
Other values (15) 15
 
2.2%
(Missing) 625
91.4%
ValueCountFrequency (%)
50 1
 
0.1%
60 1
 
0.1%
65 2
 
0.3%
70 1
 
0.1%
72 1
 
0.1%
76 1
 
0.1%
80 11
1.6%
84 1
 
0.1%
85 6
0.9%
86 1
 
0.1%
ValueCountFrequency (%)
170 1
 
0.1%
150 2
 
0.3%
130 1
 
0.1%
120 5
0.7%
116 1
 
0.1%
110 1
 
0.1%
107.5 1
 
0.1%
105 2
 
0.3%
100 1
 
0.1%
99 1
 
0.1%

Vuosilaskutus (ALV 0%, euroina)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)54.8%
Missing622
Missing (%)90.9%
Infinite0
Infinite (%)0.0%
Mean134460.16
Minimum0
Maximum300000
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:35.375491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32000
Q1112500
median138000
Q3160000
95-th percentile200000
Maximum300000
Range300000
Interquartile range (IQR)47500

Descriptive statistics

Standard deviation51161.923
Coefficient of variation (CV)0.38049875
Kurtosis2.0578273
Mean134460.16
Median Absolute Deviation (MAD)22000
Skewness-0.066051067
Sum8336530
Variance2.6175423 × 109
MonotonicityNot monotonic
2023-09-24T18:24:35.518800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
150000 5
 
0.7%
140000 5
 
0.7%
125000 4
 
0.6%
120000 4
 
0.6%
160000 4
 
0.6%
135000 4
 
0.6%
180000 3
 
0.4%
100000 2
 
0.3%
200000 2
 
0.3%
145000 2
 
0.3%
Other values (24) 27
 
3.9%
(Missing) 622
90.9%
ValueCountFrequency (%)
0 1
0.1%
30 1
0.1%
29500 1
0.1%
30000 1
0.1%
70000 1
0.1%
75000 1
0.1%
80000 2
0.3%
84000 1
0.1%
93000 1
0.1%
95000 1
0.1%
ValueCountFrequency (%)
300000 1
 
0.1%
236000 1
 
0.1%
230000 1
 
0.1%
200000 2
0.3%
190000 2
0.3%
180000 3
0.4%
170000 2
0.3%
166000 1
 
0.1%
160000 4
0.6%
155000 1
 
0.1%

Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita?
Categorical

HIGH CORRELATION  MISSING 

Distinct5
Distinct (%)7.4%
Missing616
Missing (%)90.1%
Memory size5.5 KiB
Käytän välitysfirmoja
27 
Itse
26 
Itse, Käytän välitysfirmoja
13 
Itse, Verkosto
 
1
Käytän välitysfirmoja, LinkedIn:istä tullut suoraan monta kyselyä, nykyinenkin projekti
 
1

Length

Max length87
Median length27
Mean length16.514706
Min length4

Characters and Unicode

Total characters1123
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.9%

Sample

1st rowKäytän välitysfirmoja
2nd rowItse
3rd rowKäytän välitysfirmoja
4th rowKäytän välitysfirmoja
5th rowItse

Common Values

ValueCountFrequency (%)
Käytän välitysfirmoja 27
 
3.9%
Itse 26
 
3.8%
Itse, Käytän välitysfirmoja 13
 
1.9%
Itse, Verkosto 1
 
0.1%
Käytän välitysfirmoja, LinkedIn:istä tullut suoraan monta kyselyä, nykyinenkin projekti 1
 
0.1%
(Missing) 616
90.1%

Length

2023-09-24T18:24:35.660704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:35.781733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
käytän 41
31.5%
välitysfirmoja 41
31.5%
itse 40
30.8%
verkosto 1
 
0.8%
linkedin:istä 1
 
0.8%
tullut 1
 
0.8%
suoraan 1
 
0.8%
monta 1
 
0.8%
kyselyä 1
 
0.8%
nykyinenkin 1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
t 128
 
11.4%
ä 125
 
11.1%
i 87
 
7.7%
y 86
 
7.7%
s 85
 
7.6%
62
 
5.5%
n 49
 
4.4%
o 46
 
4.1%
e 45
 
4.0%
a 44
 
3.9%
Other values (16) 366
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 960
85.5%
Uppercase Letter 84
 
7.5%
Space Separator 62
 
5.5%
Other Punctuation 17
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 128
13.3%
ä 125
13.0%
i 87
 
9.1%
y 86
 
9.0%
s 85
 
8.9%
n 49
 
5.1%
o 46
 
4.8%
e 45
 
4.7%
a 44
 
4.6%
l 44
 
4.6%
Other values (9) 221
23.0%
Uppercase Letter
ValueCountFrequency (%)
I 41
48.8%
K 41
48.8%
V 1
 
1.2%
L 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
: 1
 
5.9%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1044
93.0%
Common 79
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 128
12.3%
ä 125
12.0%
i 87
 
8.3%
y 86
 
8.2%
s 85
 
8.1%
n 49
 
4.7%
o 46
 
4.4%
e 45
 
4.3%
a 44
 
4.2%
l 44
 
4.2%
Other values (13) 305
29.2%
Common
ValueCountFrequency (%)
62
78.5%
, 16
 
20.3%
: 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 998
88.9%
None 125
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 128
 
12.8%
i 87
 
8.7%
y 86
 
8.6%
s 85
 
8.5%
62
 
6.2%
n 49
 
4.9%
o 46
 
4.6%
e 45
 
4.5%
a 44
 
4.4%
l 44
 
4.4%
Other values (15) 322
32.3%
None
ValueCountFrequency (%)
ä 125
100.0%

Mistä asiakkaat ovat?
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)4.4%
Missing616
Missing (%)90.1%
Memory size5.5 KiB
Suomesta
45 
Suomesta, Ulkomailta
12 
Ulkomailta
11 

Length

Max length20
Median length8
Mean length10.441176
Min length8

Characters and Unicode

Total characters710
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
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 rowSuomesta
2nd rowSuomesta, Ulkomailta
3rd rowSuomesta
4th rowSuomesta
5th rowSuomesta

Common Values

ValueCountFrequency (%)
Suomesta 45
 
6.6%
Suomesta, Ulkomailta 12
 
1.8%
Ulkomailta 11
 
1.6%
(Missing) 616
90.1%

Length

2023-09-24T18:24:36.053645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:36.174696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
suomesta 57
71.2%
ulkomailta 23
28.7%

Most occurring characters

ValueCountFrequency (%)
a 103
14.5%
o 80
11.3%
m 80
11.3%
t 80
11.3%
S 57
8.0%
u 57
8.0%
e 57
8.0%
s 57
8.0%
l 46
6.5%
U 23
 
3.2%
Other values (4) 70
9.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 606
85.4%
Uppercase Letter 80
 
11.3%
Other Punctuation 12
 
1.7%
Space Separator 12
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 103
17.0%
o 80
13.2%
m 80
13.2%
t 80
13.2%
u 57
9.4%
e 57
9.4%
s 57
9.4%
l 46
7.6%
k 23
 
3.8%
i 23
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
S 57
71.2%
U 23
28.7%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 686
96.6%
Common 24
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 103
15.0%
o 80
11.7%
m 80
11.7%
t 80
11.7%
S 57
8.3%
u 57
8.3%
e 57
8.3%
s 57
8.3%
l 46
6.7%
U 23
 
3.4%
Other values (2) 46
6.7%
Common
ValueCountFrequency (%)
, 12
50.0%
12
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 103
14.5%
o 80
11.3%
m 80
11.3%
t 80
11.3%
S 57
8.0%
u 57
8.0%
e 57
8.0%
s 57
8.0%
l 46
6.5%
U 23
 
3.2%
Other values (4) 70
9.9%

Työpaikka
Text

MISSING 

Distinct86
Distinct (%)58.5%
Missing537
Missing (%)78.5%
Memory size5.5 KiB
2023-09-24T18:24:36.466315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length9.0340136
Min length2

Characters and Unicode

Total characters1328
Distinct characters57
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)46.9%

Sample

1st rowVisma
2nd rowTalenom
3rd rowGofore
4th rowVincit
5th rowWunderdog
ValueCountFrequency (%)
reaktor 13
 
7.1%
vincit 10
 
5.4%
mavericks 9
 
4.9%
siili 7
 
3.8%
gofore 6
 
3.3%
futurice 5
 
2.7%
wolt 4
 
2.2%
fraktio 4
 
2.2%
mehiläinen 4
 
2.2%
compile 3
 
1.6%
Other values (107) 119
64.7%
2023-09-24T18:24:36.939723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 148
 
11.1%
e 113
 
8.5%
o 103
 
7.8%
t 94
 
7.1%
a 88
 
6.6%
r 73
 
5.5%
n 70
 
5.3%
l 63
 
4.7%
u 48
 
3.6%
k 47
 
3.5%
Other values (47) 481
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1100
82.8%
Uppercase Letter 180
 
13.6%
Space Separator 39
 
2.9%
Dash Punctuation 4
 
0.3%
Other Punctuation 3
 
0.2%
Decimal Number 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 148
13.5%
e 113
10.3%
o 103
9.4%
t 94
 
8.5%
a 88
 
8.0%
r 73
 
6.6%
n 70
 
6.4%
l 63
 
5.7%
u 48
 
4.4%
k 47
 
4.3%
Other values (18) 253
23.0%
Uppercase Letter
ValueCountFrequency (%)
S 24
13.3%
M 20
11.1%
V 17
9.4%
F 16
 
8.9%
R 15
 
8.3%
G 11
 
6.1%
A 11
 
6.1%
C 10
 
5.6%
W 8
 
4.4%
H 6
 
3.3%
Other values (13) 42
23.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1280
96.4%
Common 48
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 148
 
11.6%
e 113
 
8.8%
o 103
 
8.0%
t 94
 
7.3%
a 88
 
6.9%
r 73
 
5.7%
n 70
 
5.5%
l 63
 
4.9%
u 48
 
3.8%
k 47
 
3.7%
Other values (41) 433
33.8%
Common
ValueCountFrequency (%)
39
81.2%
- 4
 
8.3%
. 2
 
4.2%
, 1
 
2.1%
1 1
 
2.1%
2 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1320
99.4%
None 8
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 148
 
11.2%
e 113
 
8.6%
o 103
 
7.8%
t 94
 
7.1%
a 88
 
6.7%
r 73
 
5.5%
n 70
 
5.3%
l 63
 
4.8%
u 48
 
3.6%
k 47
 
3.6%
Other values (45) 473
35.8%
None
ValueCountFrequency (%)
ä 5
62.5%
ö 3
37.5%

Kaupunki
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct34
Distinct (%)5.6%
Missing80
Missing (%)11.7%
Memory size2.1 KiB
PK-Seutu
321 
Tampere
122 
Turku
67 
Oulu
33 
Jyväskylä
 
14
Vaasa
 
7
Kuopio
 
4
Pori
 
4
Joensuu
 
3
Lappeenranta
 
3
Seinäjoki
 
2
Kalifornia
 
2
Sydney, Australia
 
1
Viro
 
1
Ruotsi
 
1
Toimisto Lontoossa, teen itse etänä
 
1
Rauma
 
1
Ulkomailla
 
1
Zürich
 
1
Devaajat ympäri suomea, tasaisesti JKL-HKI
 
1
Other values (14)
 
14

Length

Max length42
Median length8
Mean length7.3642384
Min length2

Characters and Unicode

Total characters4448
Distinct characters44
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)3.6%

Sample

1st rowPK-Seutu
2nd rowPK-Seutu
3rd rowTurku
4th rowPK-Seutu
5th rowPK-Seutu

Common Values

ValueCountFrequency (%)
PK-Seutu 321
46.9%
Tampere 122
 
17.8%
Turku 67
 
9.8%
Oulu 33
 
4.8%
Jyväskylä 14
 
2.0%
Vaasa 7
 
1.0%
Kuopio 4
 
0.6%
Pori 4
 
0.6%
Joensuu 3
 
0.4%
Lappeenranta 3
 
0.4%
Other values (24) 26
 
3.8%
(Missing) 80
 
11.7%

Length

2023-09-24T18:24:37.126490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pk-seutu 321
52.1%
tampere 122
 
19.8%
turku 67
 
10.9%
oulu 33
 
5.4%
jyväskylä 14
 
2.3%
vaasa 7
 
1.1%
kuopio 4
 
0.6%
pori 4
 
0.6%
lappeenranta 3
 
0.5%
joensuu 3
 
0.5%
Other values (35) 38
 
6.2%

Most occurring characters

ValueCountFrequency (%)
u 860
19.3%
e 592
13.3%
t 341
 
7.7%
K 331
 
7.4%
P 325
 
7.3%
S 325
 
7.3%
- 323
 
7.3%
r 205
 
4.6%
T 190
 
4.3%
a 184
 
4.1%
Other values (34) 772
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2850
64.1%
Uppercase Letter 1258
28.3%
Dash Punctuation 323
 
7.3%
Space Separator 12
 
0.3%
Other Punctuation 5
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 860
30.2%
e 592
20.8%
t 341
 
12.0%
r 205
 
7.2%
a 184
 
6.5%
p 139
 
4.9%
m 131
 
4.6%
k 89
 
3.1%
l 58
 
2.0%
ä 43
 
1.5%
Other values (14) 208
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
K 331
26.3%
P 325
25.8%
S 325
25.8%
T 190
15.1%
O 33
 
2.6%
J 20
 
1.6%
V 8
 
0.6%
L 7
 
0.6%
E 4
 
0.3%
H 3
 
0.2%
Other values (7) 12
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 323
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4108
92.4%
Common 340
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 860
20.9%
e 592
14.4%
t 341
 
8.3%
K 331
 
8.1%
P 325
 
7.9%
S 325
 
7.9%
r 205
 
5.0%
T 190
 
4.6%
a 184
 
4.5%
p 139
 
3.4%
Other values (31) 616
15.0%
Common
ValueCountFrequency (%)
- 323
95.0%
12
 
3.5%
, 5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4401
98.9%
None 47
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 860
19.5%
e 592
13.5%
t 341
 
7.7%
K 331
 
7.5%
P 325
 
7.4%
S 325
 
7.4%
- 323
 
7.3%
r 205
 
4.7%
T 190
 
4.3%
a 184
 
4.2%
Other values (31) 725
16.5%
None
ValueCountFrequency (%)
ä 43
91.5%
ü 2
 
4.3%
ö 2
 
4.3%

Millaisessa yrityksessä työskentelet
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct13
Distinct (%)2.1%
Missing75
Missing (%)11.0%
Memory size5.5 KiB
Konsulttitalossa
290 
Tuotetalossa, jonka core-bisnes on softa
178 
Yrityksessä, jossa softa on tukeva toiminto (esim pankit, terveysala, yms)
109 
Julkinen tai kolmas sektori
 
23
Konsultointia ja omaa softaa
 
1
Mainos/digitoimisto
 
1
Konsulttitalossa ops-puolella
 
1
Infrastruktuuri-/kapasiteettipalvelut
 
1
Konsultointi + tuote hybridifirmassa
 
1
Tuotetalo, core-bisnes fyysisissä tuotteissa
 
1
teollisuus
 
1
Useita pienempiä asiakasprojekteja.
 
1
WordPress-projekteja
 
1

Length

Max length74
Median length44
Mean length34
Min length10

Characters and Unicode

Total characters20706
Distinct characters40
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.5%

Sample

1st rowKonsulttitalossa
2nd rowTuotetalossa, jonka core-bisnes on softa
3rd rowTuotetalossa, jonka core-bisnes on softa
4th rowKonsulttitalossa
5th rowKonsulttitalossa

Common Values

ValueCountFrequency (%)
Konsulttitalossa 290
42.4%
Tuotetalossa, jonka core-bisnes on softa 178
26.0%
Yrityksessä, jossa softa on tukeva toiminto (esim pankit, terveysala, yms) 109
 
15.9%
Julkinen tai kolmas sektori 23
 
3.4%
Konsultointia ja omaa softaa 1
 
0.1%
Mainos/digitoimisto 1
 
0.1%
Konsulttitalossa ops-puolella 1
 
0.1%
Infrastruktuuri-/kapasiteettipalvelut 1
 
0.1%
Konsultointi + tuote hybridifirmassa 1
 
0.1%
Tuotetalo, core-bisnes fyysisissä tuotteissa 1
 
0.1%
Other values (3) 3
 
0.4%
(Missing) 75
 
11.0%

Length

2023-09-24T18:24:37.287461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
konsulttitalossa 291
12.2%
on 287
12.0%
softa 287
12.0%
core-bisnes 179
 
7.5%
jonka 178
 
7.5%
tuotetalossa 178
 
7.5%
esim 109
 
4.6%
terveysala 109
 
4.6%
pankit 109
 
4.6%
yms 109
 
4.6%
Other values (27) 547
23.0%

Most occurring characters

ValueCountFrequency (%)
s 2815
13.6%
o 2261
10.9%
t 2240
10.8%
a 2016
9.7%
1775
 
8.6%
n 1206
 
5.8%
e 1143
 
5.5%
i 1107
 
5.3%
l 925
 
4.5%
u 613
 
3.0%
Other values (30) 4605
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17412
84.1%
Space Separator 1775
 
8.6%
Uppercase Letter 609
 
2.9%
Other Punctuation 509
 
2.5%
Dash Punctuation 182
 
0.9%
Close Punctuation 109
 
0.5%
Open Punctuation 109
 
0.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2815
16.2%
o 2261
13.0%
t 2240
12.9%
a 2016
11.6%
n 1206
6.9%
e 1143
6.6%
i 1107
 
6.4%
l 925
 
5.3%
u 613
 
3.5%
k 579
 
3.3%
Other values (13) 2507
14.4%
Uppercase Letter
ValueCountFrequency (%)
K 293
48.1%
T 179
29.4%
Y 109
 
17.9%
J 23
 
3.8%
M 1
 
0.2%
I 1
 
0.2%
U 1
 
0.2%
W 1
 
0.2%
P 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 506
99.4%
/ 2
 
0.4%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1775
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18021
87.0%
Common 2685
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2815
15.6%
o 2261
12.5%
t 2240
12.4%
a 2016
11.2%
n 1206
 
6.7%
e 1143
 
6.3%
i 1107
 
6.1%
l 925
 
5.1%
u 613
 
3.4%
k 579
 
3.2%
Other values (22) 3116
17.3%
Common
ValueCountFrequency (%)
1775
66.1%
, 506
 
18.8%
- 182
 
6.8%
) 109
 
4.1%
( 109
 
4.1%
/ 2
 
0.1%
+ 1
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20595
99.5%
None 111
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2815
13.7%
o 2261
11.0%
t 2240
10.9%
a 2016
9.8%
1775
 
8.6%
n 1206
 
5.9%
e 1143
 
5.5%
i 1107
 
5.4%
l 925
 
4.5%
u 613
 
3.0%
Other values (29) 4494
21.8%
None
ValueCountFrequency (%)
ä 111
100.0%

Työaika
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)1.0%
Missing72
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean0.98513072
Minimum0.4
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:37.413088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile0.8
Q11
median1
Q31
95-th percentile1
Maximum1
Range0.6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.065416825
Coefficient of variation (CV)0.066404208
Kurtosis34.067053
Mean0.98513072
Median Absolute Deviation (MAD)0
Skewness-5.3984133
Sum602.9
Variance0.004279361
MonotonicityNot monotonic
2023-09-24T18:24:37.535578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 575
84.1%
0.8 28
 
4.1%
0.6 4
 
0.6%
0.4 2
 
0.3%
0.9 2
 
0.3%
0.5 1
 
0.1%
(Missing) 72
 
10.5%
ValueCountFrequency (%)
0.4 2
 
0.3%
0.5 1
 
0.1%
0.6 4
 
0.6%
0.8 28
 
4.1%
0.9 2
 
0.3%
1 575
84.1%
ValueCountFrequency (%)
1 575
84.1%
0.9 2
 
0.3%
0.8 28
 
4.1%
0.6 4
 
0.6%
0.5 1
 
0.1%
0.4 2
 
0.3%

Rooli
Text

MISSING 

Distinct263
Distinct (%)44.3%
Missing90
Missing (%)13.2%
Memory size5.5 KiB
2023-09-24T18:24:37.738288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length98
Median length68
Mean length17.053872
Min length2

Characters and Unicode

Total characters10130
Distinct characters60
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)35.4%

Sample

1st rowTeknologiajohtaja
2nd rowOhjelmistokehittäjä
3rd rowFull-stack-ohjelmistokehittäjä
4th rowDevaaja
5th rowFull-stack
ValueCountFrequency (%)
full-stack 169
 
16.9%
ohjelmistokehittäjä 98
 
9.8%
developer 64
 
6.4%
engineer 47
 
4.7%
lead 39
 
3.9%
arkkitehti 37
 
3.7%
backend 36
 
3.6%
senior 34
 
3.4%
software 28
 
2.8%
frontend 25
 
2.5%
Other values (200) 424
42.4%
2023-09-24T18:24:38.190420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1032
 
10.2%
t 957
 
9.4%
l 720
 
7.1%
i 684
 
6.8%
a 588
 
5.8%
k 558
 
5.5%
s 459
 
4.5%
415
 
4.1%
o 403
 
4.0%
n 376
 
3.7%
Other values (50) 3938
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8586
84.8%
Uppercase Letter 790
 
7.8%
Space Separator 415
 
4.1%
Dash Punctuation 212
 
2.1%
Other Punctuation 86
 
0.8%
Close Punctuation 17
 
0.2%
Open Punctuation 16
 
0.2%
Math Symbol 8
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1032
12.0%
t 957
 
11.1%
l 720
 
8.4%
i 684
 
8.0%
a 588
 
6.8%
k 558
 
6.5%
s 459
 
5.3%
o 403
 
4.7%
n 376
 
4.4%
r 353
 
4.1%
Other values (17) 2456
28.6%
Uppercase Letter
ValueCountFrequency (%)
F 207
26.2%
O 129
16.3%
S 100
12.7%
D 71
 
9.0%
A 44
 
5.6%
E 44
 
5.6%
L 38
 
4.8%
T 32
 
4.1%
B 27
 
3.4%
P 23
 
2.9%
Other values (13) 75
 
9.5%
Other Punctuation
ValueCountFrequency (%)
, 54
62.8%
/ 27
31.4%
. 2
 
2.3%
& 2
 
2.3%
: 1
 
1.2%
Space Separator
ValueCountFrequency (%)
415
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9376
92.6%
Common 754
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1032
 
11.0%
t 957
 
10.2%
l 720
 
7.7%
i 684
 
7.3%
a 588
 
6.3%
k 558
 
6.0%
s 459
 
4.9%
o 403
 
4.3%
n 376
 
4.0%
r 353
 
3.8%
Other values (40) 3246
34.6%
Common
ValueCountFrequency (%)
415
55.0%
- 212
28.1%
, 54
 
7.2%
/ 27
 
3.6%
) 17
 
2.3%
( 16
 
2.1%
+ 8
 
1.1%
. 2
 
0.3%
& 2
 
0.3%
: 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9787
96.6%
None 343
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1032
 
10.5%
t 957
 
9.8%
l 720
 
7.4%
i 684
 
7.0%
a 588
 
6.0%
k 558
 
5.7%
s 459
 
4.7%
415
 
4.2%
o 403
 
4.1%
n 376
 
3.8%
Other values (48) 3595
36.7%
None
ValueCountFrequency (%)
ä 320
93.3%
ö 23
 
6.7%

Etä- vai lähityö
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct12
Distinct (%)2.0%
Missing71
Missing (%)10.4%
Memory size5.5 KiB
Pääosin tai kokonaan etätyö
343 
Jotain siltä väliltä
185 
Pääosin tai kokonaan toimistolla
76 
Omasta tahdosta pääosin toimistolla
 
1
kerran kuussa toimistolla firman piikkiin
 
1
Omasta valinnasta 99% toimistolla
 
1
Saa tehdä työt miten haluaa, vaikka kokonaan etänä, mutta itse pidän toimistolla työskentelemisestä joten olen siellä
 
1
Toimistolle menoa ei velvoiteta, mutta käyn siellä silti lähes päivittäin
 
1
Full remote, vapaus käyttää toimistoa jos haluaa
 
1
Täysin vapaa järjestely, ei rajoituksia.
 
1
jos toimistolla käyn niin 1-2 pv viikossa
 
1
Ei paikallaolovelvoitetta, mutta yleensä kolme päivää viikosta toimistolla
 
1

Length

Max length117
Median length27
Mean length25.929853
Min length20

Characters and Unicode

Total characters15895
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.5%

Sample

1st rowJotain siltä väliltä
2nd rowPääosin tai kokonaan etätyö
3rd rowJotain siltä väliltä
4th rowJotain siltä väliltä
5th rowPääosin tai kokonaan etätyö

Common Values

ValueCountFrequency (%)
Pääosin tai kokonaan etätyö 343
50.1%
Jotain siltä väliltä 185
27.0%
Pääosin tai kokonaan toimistolla 76
 
11.1%
Omasta tahdosta pääosin toimistolla 1
 
0.1%
kerran kuussa toimistolla firman piikkiin 1
 
0.1%
Omasta valinnasta 99% toimistolla 1
 
0.1%
Saa tehdä työt miten haluaa, vaikka kokonaan etänä, mutta itse pidän toimistolla työskentelemisestä joten olen siellä 1
 
0.1%
Toimistolle menoa ei velvoiteta, mutta käyn siellä silti lähes päivittäin 1
 
0.1%
Full remote, vapaus käyttää toimistoa jos haluaa 1
 
0.1%
Täysin vapaa järjestely, ei rajoituksia. 1
 
0.1%
Other values (2) 2
 
0.3%
(Missing) 71
 
10.4%

Length

2023-09-24T18:24:38.364242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pääosin 420
18.3%
kokonaan 420
18.3%
tai 419
18.2%
etätyö 343
14.9%
jotain 185
8.1%
siltä 185
8.1%
väliltä 185
8.1%
toimistolla 82
 
3.6%
ei 3
 
0.1%
mutta 3
 
0.1%
Other values (47) 52
 
2.3%

Most occurring characters

ValueCountFrequency (%)
t 1862
11.7%
ä 1759
11.1%
1684
10.6%
o 1628
10.2%
i 1596
10.0%
a 1567
9.9%
n 1464
9.2%
k 855
5.4%
l 742
 
4.7%
s 713
 
4.5%
Other values (26) 2025
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13587
85.5%
Space Separator 1684
 
10.6%
Uppercase Letter 611
 
3.8%
Other Punctuation 8
 
0.1%
Decimal Number 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1862
13.7%
ä 1759
12.9%
o 1628
12.0%
i 1596
11.7%
a 1567
11.5%
n 1464
10.8%
k 855
6.3%
l 742
 
5.5%
s 713
 
5.2%
e 372
 
2.7%
Other values (11) 1029
7.6%
Uppercase Letter
ValueCountFrequency (%)
P 419
68.6%
J 185
30.3%
O 2
 
0.3%
T 2
 
0.3%
S 1
 
0.2%
F 1
 
0.2%
E 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
% 1
 
12.5%
. 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
9 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
1684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14198
89.3%
Common 1697
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1862
13.1%
ä 1759
12.4%
o 1628
11.5%
i 1596
11.2%
a 1567
11.0%
n 1464
10.3%
k 855
6.0%
l 742
 
5.2%
s 713
 
5.0%
P 419
 
3.0%
Other values (18) 1593
11.2%
Common
ValueCountFrequency (%)
1684
99.2%
, 6
 
0.4%
9 2
 
0.1%
% 1
 
0.1%
. 1
 
0.1%
1 1
 
0.1%
- 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13791
86.8%
None 2104
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1862
13.5%
1684
12.2%
o 1628
11.8%
i 1596
11.6%
a 1567
11.4%
n 1464
10.6%
k 855
6.2%
l 742
 
5.4%
s 713
 
5.2%
P 419
 
3.0%
Other values (24) 1261
9.1%
None
ValueCountFrequency (%)
ä 1759
83.6%
ö 345
 
16.4%

Kuukausipalkka
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct201
Distinct (%)32.9%
Missing73
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean5324.4896
Minimum1080
Maximum22500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:38.514905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1080
5-th percentile3000
Q14300
median5100
Q36100
95-th percentile8000
Maximum22500
Range21420
Interquartile range (IQR)1800

Descriptive statistics

Standard deviation1821.1273
Coefficient of variation (CV)0.34202852
Kurtosis15.063813
Mean5324.4896
Median Absolute Deviation (MAD)900
Skewness2.3151591
Sum3253263.2
Variance3316504.6
MonotonicityNot monotonic
2023-09-24T18:24:38.664376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 29
 
4.2%
5500 25
 
3.7%
4500 23
 
3.4%
6000 20
 
2.9%
6500 16
 
2.3%
4800 15
 
2.2%
4600 15
 
2.2%
4000 15
 
2.2%
5200 14
 
2.0%
5400 13
 
1.9%
Other values (191) 426
62.3%
(Missing) 73
 
10.7%
ValueCountFrequency (%)
1080 1
 
0.1%
1200 1
 
0.1%
1660 1
 
0.1%
1760 1
 
0.1%
1880 1
 
0.1%
1903 1
 
0.1%
2000 3
0.4%
2200 1
 
0.1%
2300 2
0.3%
2341 1
 
0.1%
ValueCountFrequency (%)
22500 1
 
0.1%
14000 1
 
0.1%
13333 1
 
0.1%
13000 1
 
0.1%
12900 1
 
0.1%
12500 1
 
0.1%
11250 1
 
0.1%
11200 1
 
0.1%
10500 2
 
0.3%
10000 5
0.7%

Vuositulot
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct233
Distinct (%)39.2%
Missing90
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean69049.033
Minimum0
Maximum350000
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:38.812437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33312.5
Q153812.5
median65000
Q380000
95-th percentile110875
Maximum350000
Range350000
Interquartile range (IQR)26187.5

Descriptive statistics

Standard deviation30445.37
Coefficient of variation (CV)0.44092391
Kurtosis19.3054
Mean69049.033
Median Absolute Deviation (MAD)12556
Skewness2.9099344
Sum41015125
Variance9.2692053 × 108
MonotonicityNot monotonic
2023-09-24T18:24:38.973148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 23
 
3.4%
70000 18
 
2.6%
62500 15
 
2.2%
50000 15
 
2.2%
80000 13
 
1.9%
65000 13
 
1.9%
100000 13
 
1.9%
75000 12
 
1.8%
90000 10
 
1.5%
57500 10
 
1.5%
Other values (223) 452
66.1%
(Missing) 90
 
13.2%
ValueCountFrequency (%)
0 1
0.1%
500 1
0.1%
1000 1
0.1%
2000 1
0.1%
2500 1
0.1%
4000 1
0.1%
4800 1
0.1%
5000 1
0.1%
5062 1
0.1%
11250 1
0.1%
ValueCountFrequency (%)
350000 1
0.1%
290000 1
0.1%
220000 1
0.1%
210000 1
0.1%
200000 2
0.3%
188000 1
0.1%
170000 1
0.1%
160000 2
0.3%
156000 1
0.1%
150000 2
0.3%

Vapaa kuvaus kokonaiskompensaatiomallista
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing498
Missing (%)72.8%
Memory size5.5 KiB

Kilpailukykyinen
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.3%
Missing80
Missing (%)11.7%
Memory size5.5 KiB
True
443 
False
161 
(Missing)
80 
ValueCountFrequency (%)
True 443
64.8%
False 161
 
23.5%
(Missing) 80
 
11.7%
2023-09-24T18:24:39.107380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Vapaa sana
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing643
Missing (%)94.0%
Memory size5.5 KiB
2023-09-24T18:24:39.376104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length323
Median length98
Mean length111.56098
Min length2

Characters and Unicode

Total characters4574
Distinct characters68
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st rowLykkyä tykö vapaakenttien normalisointiin!
2nd rowLaskutan palkan firmani kautta
3rd rowVastasin kyselyyn ns. päätyönantajani mukaan. Omaani vastaavissa tehtävissä suhteellisen usein saatetaan kuitenkin keikkailla startupeissa tms. osa-aikaisesti päätyön lisäksi. Kahden työpaikan ujuttaminen vastauksiin ei onnistunut.
4th rowKunta TES == 38 kokonaista päivää vuodessa, työaika 7h15min/päivä
5th rowOlen tosiaan poikkeus siinä, että kirjoitan koodia töissä erittäin harvoin. Välillä jotain devops-tyylistä tulee harrastettu, mutta toistaiseksi harvemmin.
ValueCountFrequency (%)
on 15
 
2.6%
ja 12
 
2.1%
mutta 9
 
1.6%
ei 7
 
1.2%
myös 6
 
1.1%
enemmän 6
 
1.1%
palkkaa 6
 
1.1%
palkka 5
 
0.9%
että 5
 
0.9%
5
 
0.9%
Other values (405) 495
86.7%
2023-09-24T18:24:39.866719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 551
12.0%
534
11.7%
i 369
 
8.1%
t 365
 
8.0%
n 314
 
6.9%
s 294
 
6.4%
e 263
 
5.7%
k 242
 
5.3%
l 220
 
4.8%
o 213
 
4.7%
Other values (58) 1209
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3824
83.6%
Space Separator 534
 
11.7%
Other Punctuation 95
 
2.1%
Uppercase Letter 68
 
1.5%
Decimal Number 29
 
0.6%
Dash Punctuation 11
 
0.2%
Math Symbol 5
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 3
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 551
14.4%
i 369
9.6%
t 365
9.5%
n 314
 
8.2%
s 294
 
7.7%
e 263
 
6.9%
k 242
 
6.3%
l 220
 
5.8%
o 213
 
5.6%
u 174
 
4.6%
Other values (15) 819
21.4%
Uppercase Letter
ValueCountFrequency (%)
K 8
11.8%
S 7
10.3%
V 7
10.3%
P 7
10.3%
O 6
8.8%
E 6
8.8%
T 6
8.8%
Y 4
 
5.9%
L 3
 
4.4%
J 2
 
2.9%
Other values (8) 12
17.6%
Other Punctuation
ValueCountFrequency (%)
. 41
43.2%
, 40
42.1%
% 4
 
4.2%
/ 3
 
3.2%
" 2
 
2.1%
: 2
 
2.1%
! 2
 
2.1%
* 1
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 8
27.6%
1 5
17.2%
3 4
13.8%
2 4
13.8%
8 3
 
10.3%
5 3
 
10.3%
7 1
 
3.4%
9 1
 
3.4%
Math Symbol
ValueCountFrequency (%)
= 2
40.0%
~ 1
20.0%
< 1
20.0%
+ 1
20.0%
Space Separator
ValueCountFrequency (%)
534
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3892
85.1%
Common 682
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 551
14.2%
i 369
9.5%
t 365
9.4%
n 314
 
8.1%
s 294
 
7.6%
e 263
 
6.8%
k 242
 
6.2%
l 220
 
5.7%
o 213
 
5.5%
u 174
 
4.5%
Other values (33) 887
22.8%
Common
ValueCountFrequency (%)
534
78.3%
. 41
 
6.0%
, 40
 
5.9%
- 11
 
1.6%
0 8
 
1.2%
1 5
 
0.7%
% 4
 
0.6%
3 4
 
0.6%
2 4
 
0.6%
) 4
 
0.6%
Other values (15) 27
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4392
96.0%
None 182
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 551
12.5%
534
12.2%
i 369
 
8.4%
t 365
 
8.3%
n 314
 
7.1%
s 294
 
6.7%
e 263
 
6.0%
k 242
 
5.5%
l 220
 
5.0%
o 213
 
4.8%
Other values (56) 1027
23.4%
None
ValueCountFrequency (%)
ä 146
80.2%
ö 36
 
19.8%

Ideoita ensi vuoden kyselyyn
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing653
Missing (%)95.5%
Memory size5.5 KiB
2023-09-24T18:24:40.151370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length558
Median length89
Mean length96.806452
Min length13

Characters and Unicode

Total characters3001
Distinct characters54
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st rowTämä oli mukavan lyhyt ja ytimekäs
2nd row5/5 hyvää duunia
3rd rowKiinnostaisi tietää mitä kautta ihmiset löysivät työnsä.
4th rowEhkä voisi huomioida olennaiset semi-satunnaiset sivuduunit palkkaduunarin ja yrittäjän välimaastossa olevilla.
5th rowLuontaisedut, autoedun arvo yms. voisi olla mukana kyselyssä
ValueCountFrequency (%)
voisi 11
 
3.0%
on 8
 
2.2%
ja 7
 
1.9%
mitä 7
 
1.9%
jos 5
 
1.4%
onko 5
 
1.4%
kysyä 5
 
1.4%
myös 5
 
1.4%
se 4
 
1.1%
ehkä 4
 
1.1%
Other values (267) 304
83.3%
2023-09-24T18:24:40.589170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
338
11.3%
a 323
10.8%
t 262
 
8.7%
i 254
 
8.5%
s 220
 
7.3%
o 178
 
5.9%
e 164
 
5.5%
l 163
 
5.4%
k 153
 
5.1%
n 147
 
4.9%
Other values (44) 799
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2517
83.9%
Space Separator 338
 
11.3%
Other Punctuation 81
 
2.7%
Uppercase Letter 44
 
1.5%
Dash Punctuation 8
 
0.3%
Decimal Number 4
 
0.1%
Close Punctuation 3
 
0.1%
Control 2
 
0.1%
Open Punctuation 2
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 323
12.8%
t 262
10.4%
i 254
10.1%
s 220
8.7%
o 178
 
7.1%
e 164
 
6.5%
l 163
 
6.5%
k 153
 
6.1%
n 147
 
5.8%
u 126
 
5.0%
Other values (14) 527
20.9%
Uppercase Letter
ValueCountFrequency (%)
T 9
20.5%
M 7
15.9%
K 6
13.6%
O 5
11.4%
E 4
9.1%
V 3
 
6.8%
P 2
 
4.5%
J 2
 
4.5%
S 1
 
2.3%
F 1
 
2.3%
Other values (4) 4
9.1%
Other Punctuation
ValueCountFrequency (%)
. 32
39.5%
, 23
28.4%
? 13
16.0%
" 6
 
7.4%
/ 3
 
3.7%
! 3
 
3.7%
: 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
5 3
75.0%
1 1
 
25.0%
Other Symbol
ValueCountFrequency (%)
😍 1
50.0%
😄 1
50.0%
Space Separator
ValueCountFrequency (%)
338
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2561
85.3%
Common 440
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 323
12.6%
t 262
10.2%
i 254
9.9%
s 220
 
8.6%
o 178
 
7.0%
e 164
 
6.4%
l 163
 
6.4%
k 153
 
6.0%
n 147
 
5.7%
u 126
 
4.9%
Other values (28) 571
22.3%
Common
ValueCountFrequency (%)
338
76.8%
. 32
 
7.3%
, 23
 
5.2%
? 13
 
3.0%
- 8
 
1.8%
" 6
 
1.4%
) 3
 
0.7%
5 3
 
0.7%
/ 3
 
0.7%
! 3
 
0.7%
Other values (6) 8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2882
96.0%
None 117
 
3.9%
Emoticons 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338
11.7%
a 323
11.2%
t 262
 
9.1%
i 254
 
8.8%
s 220
 
7.6%
o 178
 
6.2%
e 164
 
5.7%
l 163
 
5.7%
k 153
 
5.3%
n 147
 
5.1%
Other values (40) 680
23.6%
None
ValueCountFrequency (%)
ä 94
80.3%
ö 23
 
19.7%
Emoticons
ValueCountFrequency (%)
😍 1
50.0%
😄 1
50.0%

Etä
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)0.5%
Missing80
Missing (%)11.7%
Memory size948.0 B
Etä
343 
50/50
185 
Toimisto
76 

Length

Max length8
Median length3
Mean length4.2417219
Min length3

Characters and Unicode

Total characters2562
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row50/50
2nd rowEtä
3rd row50/50
4th row50/50
5th rowEtä

Common Values

ValueCountFrequency (%)
Etä 343
50.1%
50/50 185
27.0%
Toimisto 76
 
11.1%
(Missing) 80
 
11.7%

Length

2023-09-24T18:24:40.756996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-24T18:24:40.878679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
etä 343
56.8%
50/50 185
30.6%
toimisto 76
 
12.6%

Most occurring characters

ValueCountFrequency (%)
t 419
16.4%
5 370
14.4%
0 370
14.4%
E 343
13.4%
ä 343
13.4%
/ 185
7.2%
o 152
 
5.9%
i 152
 
5.9%
T 76
 
3.0%
m 76
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1218
47.5%
Decimal Number 740
28.9%
Uppercase Letter 419
 
16.4%
Other Punctuation 185
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 419
34.4%
ä 343
28.2%
o 152
 
12.5%
i 152
 
12.5%
m 76
 
6.2%
s 76
 
6.2%
Decimal Number
ValueCountFrequency (%)
5 370
50.0%
0 370
50.0%
Uppercase Letter
ValueCountFrequency (%)
E 343
81.9%
T 76
 
18.1%
Other Punctuation
ValueCountFrequency (%)
/ 185
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1637
63.9%
Common 925
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 419
25.6%
E 343
21.0%
ä 343
21.0%
o 152
 
9.3%
i 152
 
9.3%
T 76
 
4.6%
m 76
 
4.6%
s 76
 
4.6%
Common
ValueCountFrequency (%)
5 370
40.0%
0 370
40.0%
/ 185
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2219
86.6%
None 343
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 419
18.9%
5 370
16.7%
0 370
16.7%
E 343
15.5%
/ 185
8.3%
o 152
 
6.8%
i 152
 
6.8%
T 76
 
3.4%
m 76
 
3.4%
s 76
 
3.4%
None
ValueCountFrequency (%)
ä 343
100.0%

Kk-tulot
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct233
Distinct (%)39.2%
Missing90
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean5754.086
Minimum0
Maximum29166.667
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-09-24T18:24:41.014188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2776.0417
Q14484.375
median5416.6667
Q36666.6667
95-th percentile9239.5833
Maximum29166.667
Range29166.667
Interquartile range (IQR)2182.2917

Descriptive statistics

Standard deviation2537.1141
Coefficient of variation (CV)0.44092391
Kurtosis19.3054
Mean5754.086
Median Absolute Deviation (MAD)1046.3333
Skewness2.9099344
Sum3417927.1
Variance6436948.1
MonotonicityNot monotonic
2023-09-24T18:24:41.175159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 23
 
3.4%
5833.333333 18
 
2.6%
5208.333333 15
 
2.2%
4166.666667 15
 
2.2%
6666.666667 13
 
1.9%
5416.666667 13
 
1.9%
8333.333333 13
 
1.9%
6250 12
 
1.8%
7500 10
 
1.5%
4791.666667 10
 
1.5%
Other values (223) 452
66.1%
(Missing) 90
 
13.2%
ValueCountFrequency (%)
0 1
0.1%
41.66666667 1
0.1%
83.33333333 1
0.1%
166.6666667 1
0.1%
208.3333333 1
0.1%
333.3333333 1
0.1%
400 1
0.1%
416.6666667 1
0.1%
421.8333333 1
0.1%
937.5 1
0.1%
ValueCountFrequency (%)
29166.66667 1
0.1%
24166.66667 1
0.1%
18333.33333 1
0.1%
17500 1
0.1%
16666.66667 2
0.3%
15666.66667 1
0.1%
14166.66667 1
0.1%
13333.33333 2
0.3%
13000 1
0.1%
12500 2
0.3%

Interactions

2023-09-24T18:24:30.473181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:24.845750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.680402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.559457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.325367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.075973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.895295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.663749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.576558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:24.959594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.786000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.655312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.426177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.179048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.997101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.771855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.665083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.067033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.899455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.761363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.532711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.266930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.085689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.859491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.751742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.162605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.001980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.852895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.628831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.351759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.172804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.947850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.839206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.261497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.122690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.950429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.727858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.437979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.260374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.032816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.948453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.369559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.212423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.035039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.815981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.545998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.365299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.146336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:31.044719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.464913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.383656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.120890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.902360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.643207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.456551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.246813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:31.156476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:25.575992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:26.470884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.215665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:27.988351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:28.786152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:29.563394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-09-24T18:24:30.363776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-09-24T18:24:41.304063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
TyökokemusMontako vuotta olet tehnyt laskuttavaa työtä alalla?Tuntilaskutus (ALV 0%, euroina)Vuosilaskutus (ALV 0%, euroina)TyöaikaKuukausipalkkaVuositulotKk-tulotOletko palkansaaja vai laskuttaja?IkäSukupuoliHankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita?Mistä asiakkaat ovat?KaupunkiMillaisessa yrityksessä työskenteletEtä- vai lähityöKilpailukykyinenEtä
Työkokemus1.0000.3530.1840.045-0.0090.5900.5670.5670.0960.4910.2370.0000.2800.1220.0000.0000.1750.000
Montako vuotta olet tehnyt laskuttavaa työtä alalla?0.3531.0000.041-0.024NaNNaNNaNNaN1.0000.0000.2130.0000.1320.0000.0000.0000.0000.000
Tuntilaskutus (ALV 0%, euroina)0.1840.0411.0000.623NaNNaNNaNNaN1.0000.1770.5930.1130.3450.0000.0000.0000.0000.000
Vuosilaskutus (ALV 0%, euroina)0.045-0.0240.6231.000NaNNaNNaNNaN1.0000.0000.3470.0000.1520.0000.0000.0000.0000.000
Työaika-0.009NaNNaNNaN1.0000.1620.1050.1051.0000.1080.2080.0000.0000.0000.4450.0000.0170.080
Kuukausipalkka0.590NaNNaNNaN0.1621.0000.9250.9251.0000.1150.1460.0000.0000.6010.0000.0000.3060.080
Vuositulot0.567NaNNaNNaN0.1050.9251.0001.0001.0000.1210.1160.0000.0000.6590.0000.0000.2880.091
Kk-tulot0.567NaNNaNNaN0.1050.9251.0001.0001.0000.1210.1160.0000.0000.6590.0000.0000.2880.091
Oletko palkansaaja vai laskuttaja?0.0961.0001.0001.0001.0001.0001.0001.0001.0000.0000.1081.0001.0001.0001.0001.0001.0001.000
Ikä0.4910.0000.1770.0000.1080.1150.1210.1210.0001.0000.1140.2010.3810.1520.0730.0000.0650.056
Sukupuoli0.2370.2130.5930.3470.2080.1460.1160.1160.1080.1141.0000.0000.2150.0000.2160.2180.0760.077
Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita?0.0000.0000.1130.0000.0000.0000.0000.0001.0000.2010.0001.0000.3570.0000.0000.0000.0000.000
Mistä asiakkaat ovat?0.2800.1320.3450.1520.0000.0000.0000.0001.0000.3810.2150.3571.0000.0000.0000.0000.0000.000
Kaupunki0.1220.0000.0000.0000.0000.6010.6590.6591.0000.1520.0000.0000.0001.0000.0000.2260.0350.000
Millaisessa yrityksessä työskentelet0.0000.0000.0000.0000.4450.0000.0000.0001.0000.0730.2160.0000.0000.0001.0000.2830.0990.093
Etä- vai lähityö0.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.2180.0000.0000.2260.2831.0000.0001.000
Kilpailukykyinen0.1750.0000.0000.0000.0170.3060.2880.2881.0000.0650.0760.0000.0000.0350.0990.0001.0000.000
Etä0.0000.0000.0000.0000.0800.0800.0910.0911.0000.0560.0770.0000.0000.0000.0931.0000.0001.000

Missing values

2023-09-24T18:24:31.342569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-09-24T18:24:31.826299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-09-24T18:24:32.206031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

TimestampOletko palkansaaja vai laskuttaja?IkäSukupuoliTyökokemusMontako vuotta olet tehnyt laskuttavaa työtä alalla?PalvelutTuntilaskutus (ALV 0%, euroina)Vuosilaskutus (ALV 0%, euroina)Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita?Mistä asiakkaat ovat?TyöpaikkaKaupunkiMillaisessa yrityksessä työskenteletTyöaikaRooliEtä- vai lähityöKuukausipalkkaVuositulotVapaa kuvaus kokonaiskompensaatiomallistaKilpailukykyinenVapaa sanaIdeoita ensi vuoden kyselyynEtäKk-tulot
02022-09-26 16:35:50.002Palkansaaja33mies12.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuKonsulttitalossa1.0TeknologiajohtajaJotain siltä väliltä6500.081250.0NaNTrueNaNNaN50/506770.833333
12022-09-26 16:37:21.049Palkansaaja33mies16.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuTuotetalossa, jonka core-bisnes on softa1.0OhjelmistokehittäjäPääosin tai kokonaan etätyö9000.0117000.0NaNTrueNaNNaNEtä9750.000000
22022-09-26 16:38:47.396Palkansaaja33mies16.0NaNNaNNaNNaNNaNNaNNaNTurkuTuotetalossa, jonka core-bisnes on softa1.0Full-stack-ohjelmistokehittäjäJotain siltä väliltä5000.062500.0NaNFalseNaNNaN50/505208.333333
32022-09-26 16:39:47.534Palkansaaja38mies13.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuKonsulttitalossa1.0DevaajaJotain siltä väliltä5100.063750.0NaNFalseNaNNaN50/505312.500000
42022-09-26 16:41:09.685Laskuttaja28mies6.01.0Data-analytiikka, Arkkitehtuuri, Data Engineering,90.0160000.0Käytän välitysfirmojaSuomestaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52022-09-26 16:43:39.266Laskuttaja28mies6.010.0Fullstack80.0100000.0ItseSuomesta, UlkomailtaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNLykkyä tykö vapaakenttien normalisointiin!Tämä oli mukavan lyhyt ja ytimekäsNaNNaN
62022-09-26 16:44:27.744Palkansaaja38mies12.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuKonsulttitalossa1.0Full-stackPääosin tai kokonaan etätyö7500.090000.0NaNTrueNaNNaNEtä7500.000000
72022-09-26 16:44:49.112Palkansaaja33mies12.0NaNNaNNaNNaNNaNNaNNaNVaasaTuotetalossa, jonka core-bisnes on softa1.0Ohjelmistokehittäjä full-stack, laitteistokehitys, tekoäly/koneoppiminenPääosin tai kokonaan etätyö3700.048000.0Kuukausipalkka + vaihtelevan kokoinen joulubonusTrueNaNNaNEtä4000.000000
82022-09-26 16:45:12.422Palkansaaja33mies4.0NaNNaNNaNNaNNaNNaNVismaTampereKonsulttitalossa1.0Full-stackPääosin tai kokonaan etätyö4600.057500.0NaNTrueNaNNaNEtä4791.666667
92022-09-26 16:45:44.793Palkansaaja38mies14.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuYrityksessä, jossa softa on tukeva toiminto (esim pankit, terveysala, yms)1.0NaNJotain siltä väliltä4300.055000.0NaNFalseNaNNaN50/504583.333333
TimestampOletko palkansaaja vai laskuttaja?IkäSukupuoliTyökokemusMontako vuotta olet tehnyt laskuttavaa työtä alalla?PalvelutTuntilaskutus (ALV 0%, euroina)Vuosilaskutus (ALV 0%, euroina)Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita?Mistä asiakkaat ovat?TyöpaikkaKaupunkiMillaisessa yrityksessä työskenteletTyöaikaRooliEtä- vai lähityöKuukausipalkkaVuositulotVapaa kuvaus kokonaiskompensaatiomallistaKilpailukykyinenVapaa sanaIdeoita ensi vuoden kyselyynEtäKk-tulot
6742022-10-09 18:56:30.713Palkansaaja38mies20.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuKonsulttitalossa1.0Web-analyytikkoPääosin tai kokonaan etätyö7300.090000.0NaNFalseNaNNaNEtä7500.000000
6752022-10-09 19:31:27.704Laskuttaja28mies4.01.0Full stack86.0125000.0Käytän välitysfirmojaSuomestaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6762022-10-09 20:54:49.686Palkansaaja33nainen0.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuTuotetalossa, jonka core-bisnes on softa1.0Junior frontend devPääosin tai kokonaan etätyö3750.047000.0Palkkamalliin kuului osakkeita n. 17t € arvosta, vestautumisaika 4 vuotta, kertyvät asteittain.TrueNaNTyökokemusvuosien vaihtoehdoissa voisi olla kokonaislukujen sijaan mahdollista valita myös esim. "alle vuosi". Mun relevantti kokemus alalta on puoli vuotta, joten en haluais millään vastata "nolla vuotta" 😄Etä3916.666667
6772022-10-09 21:34:52.664Palkansaaja33mies6.0NaNNaNNaNNaNNaNNaNNaNLappeenrantaKonsulttitalossa0.8NaNJotain siltä väliltä4200.052500.0NaNNaNNaNNaN50/504375.000000
6782022-10-09 22:07:02.512Palkansaaja33NaN5.0NaNNaNNaNNaNNaNNaNNaNTampereTuotetalossa, jonka core-bisnes on softa1.0Team leaderJotain siltä väliltä5100.0NaNNaNFalseNaNNaN50/50NaN
6792022-10-09 22:29:23.021Palkansaaja33mies6.0NaNNaNNaNNaNNaNNaNNaNPK-SeutuKonsulttitalossa1.0OhjelmistokehittäjäPääosin tai kokonaan toimistolla4730.061000.0Kiinteä kuukausipalkka + vuosibonus yrityksen tuloksen mukaanFalseNaNNaNToimisto5083.333333
6802022-10-10 06:26:34.080Laskuttaja33mies12.0NaNNaN170.0NaNItseSuomesta, UlkomailtaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6812022-10-10 06:52:45.143Palkansaaja28mies2.0NaNNaNNaNNaNNaNNaNHelsingin KaupunkiPK-SeutuJulkinen tai kolmas sektori1.0Backend, devops, projektipäällikköPääosin tai kokonaan toimistolla2300.028750.0NaNFalseNaNNaNToimisto2395.833333
6822022-10-10 07:46:57.646Palkansaaja33NaN7.0NaNNaNNaNNaNNaNNaNFraktioPK-SeutuKonsulttitalossa1.0SuunnittelijaJotain siltä väliltä4900.061250.0NaNTrueNaNNaN50/505104.166667
6832022-10-10 07:49:49.204Laskuttaja23mies7.04.0Backend, systems120.0135000.0ItseUlkomailtaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN