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
Categorical14
Numeric8
Unsupported1
Boolean1

Alerts

Palvelut has a high cardinality: 52 distinct values High cardinality
Työpaikka has a high cardinality: 86 distinct values High cardinality
Rooli has a high cardinality: 263 distinct values High cardinality
Työkokemus is highly correlated with Kuukausipalkka and 2 other fieldsHigh correlation
Tuntilaskutus (ALV 0%, euroina) is highly correlated with Vuosilaskutus (ALV 0%, euroina)High correlation
Vuosilaskutus (ALV 0%, euroina) is highly correlated with Tuntilaskutus (ALV 0%, euroina)High correlation
Kuukausipalkka is highly correlated with Vuositulot and 1 other fieldsHigh correlation
Vuositulot is highly correlated with Kuukausipalkka and 1 other fieldsHigh correlation
Kk-tulot is highly correlated with Kuukausipalkka and 1 other fieldsHigh correlation
Sukupuoli has 53 (7.7%) missing values Missing
Montako vuotta olet tehnyt laskuttavaa työtä alalla? has 617 (90.2%) missing values Missing
Palvelut has 618 (90.4%) missing values Missing
Tuntilaskutus (ALV 0%, euroina) has 625 (91.4%) missing values Missing
Vuosilaskutus (ALV 0%, euroina) has 622 (90.9%) missing values Missing
Hankitko asiakkaasi itse suoraan vai käytätkö välitysfirmojen palveluita? has 616 (90.1%) missing values Missing
Mistä asiakkaat ovat? has 616 (90.1%) missing values Missing
Työpaikka has 537 (78.5%) missing values Missing
Kaupunki has 80 (11.7%) missing values Missing
Millaisessa yrityksessä työskentelet has 75 (11.0%) missing values Missing
Työaika has 72 (10.5%) missing values Missing
Rooli has 90 (13.2%) missing values Missing
Etä- vai lähityö has 71 (10.4%) missing values Missing
Kuukausipalkka has 73 (10.7%) missing values Missing
Vuositulot has 90 (13.2%) missing values Missing
Vapaa kuvaus kokonaiskompensaatiomallista has 498 (72.8%) missing values Missing
Kilpailukykyinen has 80 (11.7%) missing values Missing
Vapaa sana has 643 (94.0%) missing values Missing
Ideoita ensi vuoden kyselyyn has 653 (95.5%) missing values Missing
Etä has 80 (11.7%) missing values Missing
Kk-tulot has 90 (13.2%) missing values Missing
Vapaa sana is uniformly distributed Uniform
Ideoita ensi vuoden kyselyyn is uniformly distributed Uniform
Timestamp has unique values Unique
Vapaa kuvaus kokonaiskompensaatiomallista is an unsupported type, check if it needs cleaning or further analysis Unsupported
Työkokemus has 13 (1.9%) zeros Zeros

Reproduction

Analysis started2022-10-19 09:13:24.217389
Analysis finished2022-10-19 09:13:34.434607
Duration10.22 seconds
Software versionpandas-profiling v3.3.0
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
2022-10-19T09:13:34.492071image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:34.619996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Palkansaaja
616 
Laskuttaja
68 

Length

Max length11
Median length11
Mean length10.9005848
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 (%)
Palkansaaja616
90.1%
Laskuttaja68
 
9.9%

Length

2022-10-19T09:13:34.736796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:34.839677image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
palkansaaja616
90.1%
laskuttaja68
 
9.9%

Most occurring characters

ValueCountFrequency (%)
a3284
44.0%
k684
 
9.2%
s684
 
9.2%
j684
 
9.2%
P616
 
8.3%
l616
 
8.3%
n616
 
8.3%
t136
 
1.8%
L68
 
0.9%
u68
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6772
90.8%
Uppercase Letter684
 
9.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a3284
48.5%
k684
 
10.1%
s684
 
10.1%
j684
 
10.1%
l616
 
9.1%
n616
 
9.1%
t136
 
2.0%
u68
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
P616
90.1%
L68
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
Latin7456
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a3284
44.0%
k684
 
9.2%
s684
 
9.2%
j684
 
9.2%
P616
 
8.3%
l616
 
8.3%
n616
 
8.3%
t136
 
1.8%
L68
 
0.9%
u68
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a3284
44.0%
k684
 
9.2%
s684
 
9.2%
j684
 
9.2%
P616
 
8.3%
l616
 
8.3%
n616
 
8.3%
t136
 
1.8%
L68
 
0.9%
u68
 
0.9%

Ikä
Categorical

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

Length

Max length6
Median length2
Mean length2.005873715
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 (%)
33202
29.5%
38196
28.7%
28135
19.7%
4393
13.6%
4825
 
3.7%
2324
 
3.5%
535
 
0.7%
> 55 v1
 
0.1%
(Missing)3
 
0.4%

Length

2022-10-19T09:13:34.929542image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:35.047554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
33202
29.6%
38196
28.7%
28135
19.8%
4393
13.6%
4825
 
3.7%
2324
 
3.5%
535
 
0.7%
1
 
0.1%
551
 
0.1%
v1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3722
52.9%
8356
26.1%
2159
 
11.6%
4118
 
8.6%
57
 
0.5%
2
 
0.1%
>1
 
0.1%
v1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1362
99.7%
Space Separator2
 
0.1%
Math Symbol1
 
0.1%
Lowercase Letter1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3722
53.0%
8356
26.1%
2159
 
11.7%
4118
 
8.7%
57
 
0.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
>1
100.0%
Lowercase Letter
ValueCountFrequency (%)
v1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1365
99.9%
Latin1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3722
52.9%
8356
26.1%
2159
 
11.6%
4118
 
8.6%
57
 
0.5%
2
 
0.1%
>1
 
0.1%
Latin
ValueCountFrequency (%)
v1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3722
52.9%
8356
26.1%
2159
 
11.6%
4118
 
8.6%
57
 
0.5%
2
 
0.1%
>1
 
0.1%
v1
 
0.1%

Sukupuoli
Categorical

MISSING

Distinct3
Distinct (%)0.5%
Missing53
Missing (%)7.7%
Memory size944.0 B
mies
548 
nainen
72 
muu
 
11

Length

Max length6
Median length4
Mean length4.210776545
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 (%)
mies548
80.1%
nainen72
 
10.5%
muu11
 
1.6%
(Missing)53
 
7.7%

Length

2022-10-19T09:13:35.154091image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:35.252654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
mies548
86.8%
nainen72
 
11.4%
muu11
 
1.7%

Most occurring characters

ValueCountFrequency (%)
i620
23.3%
e620
23.3%
m559
21.0%
s548
20.6%
n216
 
8.1%
a72
 
2.7%
u22
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2657
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i620
23.3%
e620
23.3%
m559
21.0%
s548
20.6%
n216
 
8.1%
a72
 
2.7%
u22
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin2657
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i620
23.3%
e620
23.3%
m559
21.0%
s548
20.6%
n216
 
8.1%
a72
 
2.7%
u22
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i620
23.3%
e620
23.3%
m559
21.0%
s548
20.6%
n216
 
8.1%
a72
 
2.7%
u22
 
0.8%

Työkokemus
Real number (ℝ≥0)

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
2022-10-19T09:13:35.340379image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation6.165942852
Coefficient of variation (CV)0.6045042012
Kurtosis-0.2905675607
Mean10.2
Median Absolute Deviation (MAD)5
Skewness0.5327745524
Sum6936
Variance38.01885125
MonotonicityNot monotonic
2022-10-19T09:13:35.439352image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1058
 
8.5%
554
 
7.9%
1249
 
7.2%
1549
 
7.2%
847
 
6.9%
743
 
6.3%
441
 
6.0%
635
 
5.1%
229
 
4.2%
1426
 
3.8%
Other values (20)249
36.4%
ValueCountFrequency (%)
013
 
1.9%
123
3.4%
229
4.2%
324
3.5%
441
6.0%
554
7.9%
635
5.1%
743
6.3%
847
6.9%
922
3.2%
ValueCountFrequency (%)
311
 
0.1%
281
 
0.1%
271
 
0.1%
262
 
0.3%
258
1.2%
245
 
0.7%
239
1.3%
2217
2.5%
214
 
0.6%
2019
2.8%
Distinct18
Distinct (%)26.9%
Missing617
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean3.582089552
Minimum0
Maximum16
Zeros3
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:35.538613image/svg+xmlMatplotlib v3.5.3, 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 deviation3.704621413
Coefficient of variation (CV)1.034206811
Kurtosis2.474208291
Mean3.582089552
Median Absolute Deviation (MAD)1
Skewness1.731398046
Sum240
Variance13.72421981
MonotonicityNot monotonic
2022-10-19T09:13:35.632879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
118
 
2.6%
211
 
1.6%
47
 
1.0%
36
 
0.9%
54
 
0.6%
03
 
0.4%
1.53
 
0.4%
83
 
0.4%
0.52
 
0.3%
102
 
0.3%
Other values (8)8
 
1.2%
(Missing)617
90.2%
ValueCountFrequency (%)
03
 
0.4%
0.52
 
0.3%
118
2.6%
1.53
 
0.4%
211
1.6%
2.51
 
0.1%
36
 
0.9%
47
 
1.0%
54
 
0.6%
61
 
0.1%
ValueCountFrequency (%)
161
 
0.1%
151
 
0.1%
131
 
0.1%
121
 
0.1%
111
 
0.1%
102
0.3%
91
 
0.1%
83
0.4%
61
 
0.1%
54
0.6%

Palvelut
Categorical

HIGH CARDINALITY
MISSING

Distinct52
Distinct (%)78.8%
Missing618
Missing (%)90.4%
Memory size5.5 KiB
Full stack
14 
Softadevausta
 
2
Arkkitehti/projektipäällikkö
 
1
Softadevaus, data engineering
 
1
Backend devops
 
1
Full stack web-ohjelmointia
 
1
Full-stack, lead developer
 
1
Frontend, full stack
 
1
Team Lead, projekti- ja tuotekonsultointi
 
1
Full stack web ja mobiili
 
1
Full stack dev / teknologia konsultointia, arkkitehtuuria
 
1
Softadevaus fullstack + cloud, arkkitehtuuri, devops
 
1
Full stack, arkkitehtuuria
 
1
Softan kehitystä, arkkitehtuuria
 
1
Full stack dev
 
1
Web3 full stack
 
1
Backend
 
1
Backend, frontend, full stack, arkkitehtuuri
 
1
Arkkitehtuuria
 
1
Softadevausta (full stack, fokus backend ja devops), arkkitehtuuria ja projektinvetoa, ja joskus koulutusta
 
1
Other values (32)
32 

Length

Max length130
Median length50
Mean length27.60606061
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

Common Values

ValueCountFrequency (%)
Full stack14
 
2.0%
Softadevausta2
 
0.3%
Arkkitehti/projektipäällikkö1
 
0.1%
Softadevaus, data engineering1
 
0.1%
Backend devops1
 
0.1%
Full stack web-ohjelmointia1
 
0.1%
Full-stack, lead developer1
 
0.1%
Frontend, full stack1
 
0.1%
Team Lead, projekti- ja tuotekonsultointi1
 
0.1%
Full stack web ja mobiili1
 
0.1%
Other values (42)42
 
6.1%
(Missing)618
90.4%

Length

2022-10-19T09:13:35.760745image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
full37
 
16.3%
stack37
 
16.3%
ja13
 
5.7%
devops9
 
4.0%
backend7
 
3.1%
arkkitehtuuria6
 
2.6%
6
 
2.6%
frontend5
 
2.2%
softadevausta5
 
2.2%
arkkitehtuuri5
 
2.2%
Other values (73)97
42.7%

Most occurring characters

ValueCountFrequency (%)
a175
 
9.6%
t167
 
9.2%
162
 
8.9%
l127
 
7.0%
e116
 
6.4%
k109
 
6.0%
u106
 
5.8%
s100
 
5.5%
i97
 
5.3%
o67
 
3.7%
Other values (43)596
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1502
82.4%
Space Separator162
 
8.9%
Uppercase Letter88
 
4.8%
Other Punctuation58
 
3.2%
Dash Punctuation8
 
0.4%
Decimal Number1
 
0.1%
Open Punctuation1
 
0.1%
Close Punctuation1
 
0.1%
Math Symbol1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a175
11.7%
t167
11.1%
l127
 
8.5%
e116
 
7.7%
k109
 
7.3%
u106
 
7.1%
s100
 
6.7%
i97
 
6.5%
o67
 
4.5%
n65
 
4.3%
Other values (17)373
24.8%
Uppercase Letter
ValueCountFrequency (%)
F37
42.0%
S10
 
11.4%
D8
 
9.1%
B6
 
6.8%
A4
 
4.5%
C4
 
4.5%
E3
 
3.4%
O3
 
3.4%
W3
 
3.4%
T3
 
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 (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1590
87.3%
Common232
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a175
 
11.0%
t167
 
10.5%
l127
 
8.0%
e116
 
7.3%
k109
 
6.9%
u106
 
6.7%
s100
 
6.3%
i97
 
6.1%
o67
 
4.2%
n65
 
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%
31
 
0.4%
(1
 
0.4%
)1
 
0.4%
+1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1799
98.7%
None23
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a175
 
9.7%
t167
 
9.3%
162
 
9.0%
l127
 
7.1%
e116
 
6.4%
k109
 
6.1%
u106
 
5.9%
s100
 
5.6%
i97
 
5.4%
o67
 
3.7%
Other values (41)573
31.9%
None
ValueCountFrequency (%)
ä20
87.0%
ö3
 
13.0%

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

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
2022-10-19T09:13:35.871184image/svg+xmlMatplotlib v3.5.3, 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 deviation21.63908501
Coefficient of variation (CV)0.2314340643
Kurtosis2.634267697
Mean93.5
Median Absolute Deviation (MAD)10
Skewness1.312304188
Sum5516.5
Variance468.25
MonotonicityNot monotonic
2022-10-19T09:13:35.971413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8011
 
1.6%
9010
 
1.5%
856
 
0.9%
1205
 
0.7%
953
 
0.4%
1052
 
0.3%
882
 
0.3%
1502
 
0.3%
652
 
0.3%
981
 
0.1%
Other values (15)15
 
2.2%
(Missing)625
91.4%
ValueCountFrequency (%)
501
 
0.1%
601
 
0.1%
652
 
0.3%
701
 
0.1%
721
 
0.1%
761
 
0.1%
8011
1.6%
841
 
0.1%
856
0.9%
861
 
0.1%
ValueCountFrequency (%)
1701
 
0.1%
1502
 
0.3%
1301
 
0.1%
1205
0.7%
1161
 
0.1%
1101
 
0.1%
107.51
 
0.1%
1052
 
0.3%
1001
 
0.1%
991
 
0.1%

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

HIGH CORRELATION
MISSING

Distinct34
Distinct (%)54.8%
Missing622
Missing (%)90.9%
Infinite0
Infinite (%)0.0%
Mean134460.1613
Minimum0
Maximum300000
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:36.075537image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation51161.92272
Coefficient of variation (CV)0.3804987457
Kurtosis2.057827297
Mean134460.1613
Median Absolute Deviation (MAD)22000
Skewness-0.066051067
Sum8336530
Variance2617542336
MonotonicityNot monotonic
2022-10-19T09:13:36.178416image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1500005
 
0.7%
1400005
 
0.7%
1250004
 
0.6%
1200004
 
0.6%
1600004
 
0.6%
1350004
 
0.6%
1800003
 
0.4%
1000002
 
0.3%
2000002
 
0.3%
1450002
 
0.3%
Other values (24)27
 
3.9%
(Missing)622
90.9%
ValueCountFrequency (%)
01
0.1%
301
0.1%
295001
0.1%
300001
0.1%
700001
0.1%
750001
0.1%
800002
0.3%
840001
0.1%
930001
0.1%
950001
0.1%
ValueCountFrequency (%)
3000001
 
0.1%
2360001
 
0.1%
2300001
 
0.1%
2000002
0.3%
1900002
0.3%
1800003
0.4%
1700002
0.3%
1660001
 
0.1%
1600004
0.6%
1550001
 
0.1%
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 length16.51470588
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 välitysfirmoja27
 
3.9%
Itse26
 
3.8%
Itse, Käytän välitysfirmoja13
 
1.9%
Itse, Verkosto1
 
0.1%
Käytän välitysfirmoja, LinkedIn:istä tullut suoraan monta kyselyä, nykyinenkin projekti1
 
0.1%
(Missing)616
90.1%

Length

2022-10-19T09:13:36.285366image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:36.505575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
käytän41
31.5%
välitysfirmoja41
31.5%
itse40
30.8%
verkosto1
 
0.8%
linkedin:istä1
 
0.8%
tullut1
 
0.8%
suoraan1
 
0.8%
monta1
 
0.8%
kyselyä1
 
0.8%
nykyinenkin1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
t128
 
11.4%
ä125
 
11.1%
i87
 
7.7%
y86
 
7.7%
s85
 
7.6%
62
 
5.5%
n49
 
4.4%
o46
 
4.1%
e45
 
4.0%
a44
 
3.9%
Other values (16)366
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter960
85.5%
Uppercase Letter84
 
7.5%
Space Separator62
 
5.5%
Other Punctuation17
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t128
13.3%
ä125
13.0%
i87
 
9.1%
y86
 
9.0%
s85
 
8.9%
n49
 
5.1%
o46
 
4.8%
e45
 
4.7%
a44
 
4.6%
l44
 
4.6%
Other values (9)221
23.0%
Uppercase Letter
ValueCountFrequency (%)
I41
48.8%
K41
48.8%
V1
 
1.2%
L1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
,16
94.1%
:1
 
5.9%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1044
93.0%
Common79
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t128
12.3%
ä125
12.0%
i87
 
8.3%
y86
 
8.2%
s85
 
8.1%
n49
 
4.7%
o46
 
4.4%
e45
 
4.3%
a44
 
4.2%
l44
 
4.2%
Other values (13)305
29.2%
Common
ValueCountFrequency (%)
62
78.5%
,16
 
20.3%
:1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII998
88.9%
None125
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t128
 
12.8%
i87
 
8.7%
y86
 
8.6%
s85
 
8.5%
62
 
6.2%
n49
 
4.9%
o46
 
4.6%
e45
 
4.5%
a44
 
4.4%
l44
 
4.4%
Other values (15)322
32.3%
None
ValueCountFrequency (%)
ä125
100.0%

Mistä asiakkaat ovat?
Categorical

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 length10.44117647
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 (%)
Suomesta45
 
6.6%
Suomesta, Ulkomailta12
 
1.8%
Ulkomailta11
 
1.6%
(Missing)616
90.1%

Length

2022-10-19T09:13:36.612148image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:36.711995image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
suomesta57
71.2%
ulkomailta23
28.7%

Most occurring characters

ValueCountFrequency (%)
a103
14.5%
o80
11.3%
m80
11.3%
t80
11.3%
S57
8.0%
u57
8.0%
e57
8.0%
s57
8.0%
l46
6.5%
U23
 
3.2%
Other values (4)70
9.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter606
85.4%
Uppercase Letter80
 
11.3%
Other Punctuation12
 
1.7%
Space Separator12
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a103
17.0%
o80
13.2%
m80
13.2%
t80
13.2%
u57
9.4%
e57
9.4%
s57
9.4%
l46
7.6%
k23
 
3.8%
i23
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
S57
71.2%
U23
28.7%
Other Punctuation
ValueCountFrequency (%)
,12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin686
96.6%
Common24
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a103
15.0%
o80
11.7%
m80
11.7%
t80
11.7%
S57
8.3%
u57
8.3%
e57
8.3%
s57
8.3%
l46
6.7%
U23
 
3.4%
Other values (2)46
6.7%
Common
ValueCountFrequency (%)
,12
50.0%
12
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a103
14.5%
o80
11.3%
m80
11.3%
t80
11.3%
S57
8.0%
u57
8.0%
e57
8.0%
s57
8.0%
l46
6.5%
U23
 
3.2%
Other values (4)70
9.9%

Työpaikka
Categorical

HIGH CARDINALITY
MISSING

Distinct86
Distinct (%)58.5%
Missing537
Missing (%)78.5%
Memory size5.5 KiB
Reaktor
13 
Vincit
10 
Mavericks
Gofore
 
6
Siili
 
5
Futurice
 
4
Wolt
 
4
Fraktio
 
4
Mehiläinen
 
4
Compile
 
3
Visma
 
3
Wunderdog
 
3
Exove
 
3
UpCloud
 
2
Mapbox
 
2
Arado
 
2
Solita
 
2
academic work
 
1
Leanware
 
1
nexi
 
1
Other values (66)
66 

Length

Max length43
Median length29
Mean length9.034013605
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

Common Values

ValueCountFrequency (%)
Reaktor13
 
1.9%
Vincit10
 
1.5%
Mavericks8
 
1.2%
Gofore6
 
0.9%
Siili5
 
0.7%
Futurice4
 
0.6%
Wolt4
 
0.6%
Fraktio4
 
0.6%
Mehiläinen4
 
0.6%
Compile3
 
0.4%
Other values (76)86
 
12.6%
(Missing)537
78.5%

Length

2022-10-19T09:13:36.810965image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
reaktor13
 
7.1%
vincit10
 
5.4%
mavericks9
 
4.9%
siili7
 
3.8%
gofore6
 
3.3%
futurice5
 
2.7%
wolt4
 
2.2%
fraktio4
 
2.2%
mehiläinen4
 
2.2%
compile3
 
1.6%
Other values (107)119
64.7%

Most occurring characters

ValueCountFrequency (%)
i148
 
11.1%
e113
 
8.5%
o103
 
7.8%
t94
 
7.1%
a88
 
6.6%
r73
 
5.5%
n70
 
5.3%
l63
 
4.7%
u48
 
3.6%
k47
 
3.5%
Other values (47)481
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1100
82.8%
Uppercase Letter180
 
13.6%
Space Separator39
 
2.9%
Dash Punctuation4
 
0.3%
Other Punctuation3
 
0.2%
Decimal Number2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i148
13.5%
e113
10.3%
o103
9.4%
t94
 
8.5%
a88
 
8.0%
r73
 
6.6%
n70
 
6.4%
l63
 
5.7%
u48
 
4.4%
k47
 
4.3%
Other values (18)253
23.0%
Uppercase Letter
ValueCountFrequency (%)
S24
13.3%
M20
11.1%
V17
9.4%
F16
 
8.9%
R15
 
8.3%
G11
 
6.1%
A11
 
6.1%
C10
 
5.6%
W8
 
4.4%
H6
 
3.3%
Other values (13)42
23.3%
Other Punctuation
ValueCountFrequency (%)
.2
66.7%
,1
33.3%
Decimal Number
ValueCountFrequency (%)
11
50.0%
21
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1280
96.4%
Common48
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i148
 
11.6%
e113
 
8.8%
o103
 
8.0%
t94
 
7.3%
a88
 
6.9%
r73
 
5.7%
n70
 
5.5%
l63
 
4.9%
u48
 
3.8%
k47
 
3.7%
Other values (41)433
33.8%
Common
ValueCountFrequency (%)
39
81.2%
-4
 
8.3%
.2
 
4.2%
,1
 
2.1%
11
 
2.1%
21
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1320
99.4%
None8
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i148
 
11.2%
e113
 
8.6%
o103
 
7.8%
t94
 
7.1%
a88
 
6.7%
r73
 
5.5%
n70
 
5.3%
l63
 
4.8%
u48
 
3.6%
k47
 
3.6%
Other values (45)473
35.8%
None
ValueCountFrequency (%)
ä5
62.5%
ö3
37.5%

Kaupunki
Categorical

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 length7.364238411
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-Seutu321
46.9%
Tampere122
 
17.8%
Turku67
 
9.8%
Oulu33
 
4.8%
Jyväskylä14
 
2.0%
Vaasa7
 
1.0%
Kuopio4
 
0.6%
Pori4
 
0.6%
Joensuu3
 
0.4%
Lappeenranta3
 
0.4%
Other values (24)26
 
3.8%
(Missing)80
 
11.7%

Length

2022-10-19T09:13:36.919365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pk-seutu321
52.1%
tampere122
 
19.8%
turku67
 
10.9%
oulu33
 
5.4%
jyväskylä14
 
2.3%
vaasa7
 
1.1%
kuopio4
 
0.6%
pori4
 
0.6%
lappeenranta3
 
0.5%
joensuu3
 
0.5%
Other values (35)38
 
6.2%

Most occurring characters

ValueCountFrequency (%)
u860
19.3%
e592
13.3%
t341
 
7.7%
K331
 
7.4%
P325
 
7.3%
S325
 
7.3%
-323
 
7.3%
r205
 
4.6%
T190
 
4.3%
a184
 
4.1%
Other values (34)772
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2850
64.1%
Uppercase Letter1258
28.3%
Dash Punctuation323
 
7.3%
Space Separator12
 
0.3%
Other Punctuation5
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u860
30.2%
e592
20.8%
t341
 
12.0%
r205
 
7.2%
a184
 
6.5%
p139
 
4.9%
m131
 
4.6%
k89
 
3.1%
l58
 
2.0%
ä43
 
1.5%
Other values (14)208
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
K331
26.3%
P325
25.8%
S325
25.8%
T190
15.1%
O33
 
2.6%
J20
 
1.6%
V8
 
0.6%
L7
 
0.6%
E4
 
0.3%
H3
 
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 (%)
Latin4108
92.4%
Common340
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
u860
20.9%
e592
14.4%
t341
 
8.3%
K331
 
8.1%
P325
 
7.9%
S325
 
7.9%
r205
 
5.0%
T190
 
4.6%
a184
 
4.5%
p139
 
3.4%
Other values (31)616
15.0%
Common
ValueCountFrequency (%)
-323
95.0%
12
 
3.5%
,5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4401
98.9%
None47
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u860
19.5%
e592
13.5%
t341
 
7.7%
K331
 
7.5%
P325
 
7.4%
S325
 
7.4%
-323
 
7.3%
r205
 
4.7%
T190
 
4.3%
a184
 
4.2%
Other values (31)725
16.5%
None
ValueCountFrequency (%)
ä43
91.5%
ü2
 
4.3%
ö2
 
4.3%
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 (%)
Konsulttitalossa290
42.4%
Tuotetalossa, jonka core-bisnes on softa178
26.0%
Yrityksessä, jossa softa on tukeva toiminto (esim pankit, terveysala, yms)109
 
15.9%
Julkinen tai kolmas sektori23
 
3.4%
Konsultointia ja omaa softaa1
 
0.1%
Mainos/digitoimisto1
 
0.1%
Konsulttitalossa ops-puolella 1
 
0.1%
Infrastruktuuri-/kapasiteettipalvelut1
 
0.1%
Konsultointi + tuote hybridifirmassa1
 
0.1%
Tuotetalo, core-bisnes fyysisissä tuotteissa1
 
0.1%
Other values (3)3
 
0.4%
(Missing)75
 
11.0%

Length

2022-10-19T09:13:37.037451image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
konsulttitalossa291
12.2%
on287
12.0%
softa287
12.0%
core-bisnes179
 
7.5%
jonka178
 
7.5%
tuotetalossa178
 
7.5%
esim109
 
4.6%
terveysala109
 
4.6%
pankit109
 
4.6%
yms109
 
4.6%
Other values (27)547
23.0%

Most occurring characters

ValueCountFrequency (%)
s2815
13.6%
o2261
10.9%
t2240
10.8%
a2016
9.7%
1775
 
8.6%
n1206
 
5.8%
e1143
 
5.5%
i1107
 
5.3%
l925
 
4.5%
u613
 
3.0%
Other values (30)4605
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17412
84.1%
Space Separator1775
 
8.6%
Uppercase Letter609
 
2.9%
Other Punctuation509
 
2.5%
Dash Punctuation182
 
0.9%
Close Punctuation109
 
0.5%
Open Punctuation109
 
0.5%
Math Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s2815
16.2%
o2261
13.0%
t2240
12.9%
a2016
11.6%
n1206
6.9%
e1143
6.6%
i1107
 
6.4%
l925
 
5.3%
u613
 
3.5%
k579
 
3.3%
Other values (13)2507
14.4%
Uppercase Letter
ValueCountFrequency (%)
K293
48.1%
T179
29.4%
Y109
 
17.9%
J23
 
3.8%
M1
 
0.2%
I1
 
0.2%
U1
 
0.2%
W1
 
0.2%
P1
 
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 (%)
Latin18021
87.0%
Common2685
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s2815
15.6%
o2261
12.5%
t2240
12.4%
a2016
11.2%
n1206
 
6.7%
e1143
 
6.3%
i1107
 
6.1%
l925
 
5.1%
u613
 
3.4%
k579
 
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 (%)
ASCII20595
99.5%
None111
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s2815
13.7%
o2261
11.0%
t2240
10.9%
a2016
9.8%
1775
 
8.6%
n1206
 
5.9%
e1143
 
5.5%
i1107
 
5.4%
l925
 
4.5%
u613
 
3.0%
Other values (29)4494
21.8%
None
ValueCountFrequency (%)
ä111
100.0%

Työaika
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)1.0%
Missing72
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean0.985130719
Minimum0.4
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:37.128667image/svg+xmlMatplotlib v3.5.3, 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 deviation0.0654168247
Coefficient of variation (CV)0.06640420752
Kurtosis34.06705282
Mean0.985130719
Median Absolute Deviation (MAD)0
Skewness-5.398413318
Sum602.9
Variance0.004279360953
MonotonicityNot monotonic
2022-10-19T09:13:37.206893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1575
84.1%
0.828
 
4.1%
0.64
 
0.6%
0.42
 
0.3%
0.92
 
0.3%
0.51
 
0.1%
(Missing)72
 
10.5%
ValueCountFrequency (%)
0.42
 
0.3%
0.51
 
0.1%
0.64
 
0.6%
0.828
 
4.1%
0.92
 
0.3%
1575
84.1%
ValueCountFrequency (%)
1575
84.1%
0.92
 
0.3%
0.828
 
4.1%
0.64
 
0.6%
0.51
 
0.1%
0.42
 
0.3%

Rooli
Categorical

HIGH CARDINALITY
MISSING

Distinct263
Distinct (%)44.3%
Missing90
Missing (%)13.2%
Memory size5.5 KiB
Full-stack
134 
Ohjelmistokehittäjä
61 
Arkkitehti
28 
Backend
 
12
Lead developer
 
12
Frontend
 
9
CTO
 
6
Team Lead
 
5
Software Engineer
 
5
Frontend developer
 
5
Senior Software Engineer
 
5
Projektipäällikkö
 
5
DevOps
 
5
Data scientist
 
4
Software developer
 
4
Data Engineer
 
4
Data engineer
 
3
Ohjelmistokehittäjä (backend)
 
3
Pilviarkkitehti
 
3
Data Scientist
 
3
Other values (243)
278 

Length

Max length98
Median length68
Mean length17.05387205
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

Common Values

ValueCountFrequency (%)
Full-stack134
19.6%
Ohjelmistokehittäjä61
 
8.9%
Arkkitehti28
 
4.1%
Backend12
 
1.8%
Lead developer12
 
1.8%
Frontend9
 
1.3%
CTO6
 
0.9%
Team Lead5
 
0.7%
Software Engineer5
 
0.7%
Frontend developer5
 
0.7%
Other values (253)317
46.3%
(Missing)90
 
13.2%

Length

2022-10-19T09:13:37.330209image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
full-stack169
 
16.9%
ohjelmistokehittäjä98
 
9.8%
developer64
 
6.4%
engineer47
 
4.7%
lead39
 
3.9%
arkkitehti37
 
3.7%
backend36
 
3.6%
senior34
 
3.4%
software28
 
2.8%
frontend25
 
2.5%
Other values (200)424
42.4%

Most occurring characters

ValueCountFrequency (%)
e1032
 
10.2%
t957
 
9.4%
l720
 
7.1%
i684
 
6.8%
a588
 
5.8%
k558
 
5.5%
s459
 
4.5%
415
 
4.1%
o403
 
4.0%
n376
 
3.7%
Other values (50)3938
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8586
84.8%
Uppercase Letter790
 
7.8%
Space Separator415
 
4.1%
Dash Punctuation212
 
2.1%
Other Punctuation86
 
0.8%
Close Punctuation17
 
0.2%
Open Punctuation16
 
0.2%
Math Symbol8
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1032
12.0%
t957
 
11.1%
l720
 
8.4%
i684
 
8.0%
a588
 
6.8%
k558
 
6.5%
s459
 
5.3%
o403
 
4.7%
n376
 
4.4%
r353
 
4.1%
Other values (17)2456
28.6%
Uppercase Letter
ValueCountFrequency (%)
F207
26.2%
O129
16.3%
S100
12.7%
D71
 
9.0%
A44
 
5.6%
E44
 
5.6%
L38
 
4.8%
T32
 
4.1%
B27
 
3.4%
P23
 
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 (%)
Latin9376
92.6%
Common754
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1032
 
11.0%
t957
 
10.2%
l720
 
7.7%
i684
 
7.3%
a588
 
6.3%
k558
 
6.0%
s459
 
4.9%
o403
 
4.3%
n376
 
4.0%
r353
 
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 (%)
ASCII9787
96.6%
None343
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e1032
 
10.5%
t957
 
9.8%
l720
 
7.4%
i684
 
7.0%
a588
 
6.0%
k558
 
5.7%
s459
 
4.7%
415
 
4.2%
o403
 
4.1%
n376
 
3.8%
Other values (48)3595
36.7%
None
ValueCountFrequency (%)
ä320
93.3%
ö23
 
6.7%

Etä- vai lähityö
Categorical

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 length25.92985318
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 etätyö343
50.1%
Jotain siltä väliltä185
27.0%
Pääosin tai kokonaan toimistolla76
 
11.1%
Omasta tahdosta pääosin toimistolla1
 
0.1%
kerran kuussa toimistolla firman piikkiin1
 
0.1%
Omasta valinnasta 99% toimistolla1
 
0.1%
Saa tehdä työt miten haluaa, vaikka kokonaan etänä, mutta itse pidän toimistolla työskentelemisestä joten olen siellä1
 
0.1%
Toimistolle menoa ei velvoiteta, mutta käyn siellä silti lähes päivittäin1
 
0.1%
Full remote, vapaus käyttää toimistoa jos haluaa1
 
0.1%
Täysin vapaa järjestely, ei rajoituksia.1
 
0.1%
Other values (2)2
 
0.3%
(Missing)71
 
10.4%

Length

2022-10-19T09:13:37.448601image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pääosin420
18.3%
kokonaan420
18.3%
tai419
18.2%
etätyö343
14.9%
jotain185
8.1%
siltä185
8.1%
väliltä185
8.1%
toimistolla82
 
3.6%
ei3
 
0.1%
mutta3
 
0.1%
Other values (47)52
 
2.3%

Most occurring characters

ValueCountFrequency (%)
t1862
11.7%
ä1759
11.1%
1684
10.6%
o1628
10.2%
i1596
10.0%
a1567
9.9%
n1464
9.2%
k855
5.4%
l742
 
4.7%
s713
 
4.5%
Other values (26)2025
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter13587
85.5%
Space Separator1684
 
10.6%
Uppercase Letter611
 
3.8%
Other Punctuation8
 
0.1%
Decimal Number4
 
< 0.1%
Dash Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t1862
13.7%
ä1759
12.9%
o1628
12.0%
i1596
11.7%
a1567
11.5%
n1464
10.8%
k855
6.3%
l742
 
5.5%
s713
 
5.2%
e372
 
2.7%
Other values (11)1029
7.6%
Uppercase Letter
ValueCountFrequency (%)
P419
68.6%
J185
30.3%
O2
 
0.3%
T2
 
0.3%
S1
 
0.2%
F1
 
0.2%
E1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
,6
75.0%
%1
 
12.5%
.1
 
12.5%
Decimal Number
ValueCountFrequency (%)
92
50.0%
11
25.0%
21
25.0%
Space Separator
ValueCountFrequency (%)
1684
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14198
89.3%
Common1697
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t1862
13.1%
ä1759
12.4%
o1628
11.5%
i1596
11.2%
a1567
11.0%
n1464
10.3%
k855
6.0%
l742
 
5.2%
s713
 
5.0%
P419
 
3.0%
Other values (18)1593
11.2%
Common
ValueCountFrequency (%)
1684
99.2%
,6
 
0.4%
92
 
0.1%
%1
 
0.1%
.1
 
0.1%
11
 
0.1%
-1
 
0.1%
21
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII13791
86.8%
None2104
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t1862
13.5%
1684
12.2%
o1628
11.8%
i1596
11.6%
a1567
11.4%
n1464
10.6%
k855
6.2%
l742
 
5.4%
s713
 
5.2%
P419
 
3.0%
Other values (24)1261
9.1%
None
ValueCountFrequency (%)
ä1759
83.6%
ö345
 
16.4%

Kuukausipalkka
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct201
Distinct (%)32.9%
Missing73
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean5324.48964
Minimum1080
Maximum22500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:37.558091image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1821.127289
Coefficient of variation (CV)0.3420285159
Kurtosis15.0638134
Mean5324.48964
Median Absolute Deviation (MAD)900
Skewness2.315159103
Sum3253263.17
Variance3316504.604
MonotonicityNot monotonic
2022-10-19T09:13:37.674382image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500029
 
4.2%
550025
 
3.7%
450023
 
3.4%
600020
 
2.9%
650016
 
2.3%
480015
 
2.2%
460015
 
2.2%
400015
 
2.2%
520014
 
2.0%
540013
 
1.9%
Other values (191)426
62.3%
(Missing)73
 
10.7%
ValueCountFrequency (%)
10801
 
0.1%
12001
 
0.1%
16601
 
0.1%
17601
 
0.1%
18801
 
0.1%
19031
 
0.1%
20003
0.4%
22001
 
0.1%
23002
0.3%
23411
 
0.1%
ValueCountFrequency (%)
225001
 
0.1%
140001
 
0.1%
133331
 
0.1%
130001
 
0.1%
129001
 
0.1%
125001
 
0.1%
112501
 
0.1%
112001
 
0.1%
105002
 
0.3%
100005
0.7%

Vuositulot
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct233
Distinct (%)39.2%
Missing90
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean69049.03254
Minimum0
Maximum350000
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:37.795633image/svg+xmlMatplotlib v3.5.3, 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 deviation30445.36959
Coefficient of variation (CV)0.4409239127
Kurtosis19.30540031
Mean69049.03254
Median Absolute Deviation (MAD)12556
Skewness2.909934441
Sum41015125.33
Variance926920529.7
MonotonicityNot monotonic
2022-10-19T09:13:37.913861image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6000023
 
3.4%
7000018
 
2.6%
6250015
 
2.2%
5000015
 
2.2%
8000013
 
1.9%
6500013
 
1.9%
10000013
 
1.9%
7500012
 
1.8%
9000010
 
1.5%
5750010
 
1.5%
Other values (223)452
66.1%
(Missing)90
 
13.2%
ValueCountFrequency (%)
01
0.1%
5001
0.1%
10001
0.1%
20001
0.1%
25001
0.1%
40001
0.1%
48001
0.1%
50001
0.1%
50621
0.1%
112501
0.1%
ValueCountFrequency (%)
3500001
0.1%
2900001
0.1%
2200001
0.1%
2100001
0.1%
2000002
0.3%
1880001
0.1%
1700001
0.1%
1600002
0.3%
1560001
0.1%
1500002
0.3%

Vapaa kuvaus kokonaiskompensaatiomallista
Unsupported

MISSING
REJECTED
UNSUPPORTED

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

Kilpailukykyinen
Boolean

MISSING

Distinct2
Distinct (%)0.3%
Missing80
Missing (%)11.7%
Memory size5.5 KiB
True
443 
False
161 
(Missing)
80 
ValueCountFrequency (%)
True443
64.8%
False161
 
23.5%
(Missing)80
 
11.7%
2022-10-19T09:13:38.030594image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Vapaa sana
Categorical

MISSING
UNIFORM

Distinct41
Distinct (%)100.0%
Missing643
Missing (%)94.0%
Memory size5.5 KiB
Työsuhteessa ulkomaalaiseen firmaan, ainoastaan palkanmaksu menee oman firman kautta
 
1
kokemusta jo kolme viikkoa it alalta
 
1
Laskuttavan työn lisäksi teen tuotekehitystä omaan b2c SaaS-palveluun, josta maksan itselleni myös palkkaa.
 
1
tietyn palkkatason jälkeen työntekijät alkavat ottamaan enemmän lomaa ja vapaa-aika. Se on eri asia kuin 100% allokaatio työtä tehdessä ja vaikuttaa vuosituloihin. Pääomatulot työnantajan osakkeilla taas voivat usein olla kerta luontoisia, mutta tuoda paljonkin lisätuloja
 
1
Tällä hetkellä sopparit tehdään 1v kerrallaan. Firman muoto OY.
 
1
Yrittäjähenkisessä työskentelyssä ei usein lasketa työtunteja. Siten esim. 90% työaika on aika näennäinen. Välillä tehdään kovempaa ja välillä rauhallisemmin.
 
1
En oo ihan varma miten muut toisissa vastaavan kokoluokan yrityksissä saa palkkaa vastaavasta roolista.
 
1
Koulu vielä kesken ja se vaikuttaa palkkaan
 
1
Palkka ei ole kilpailukykyinen, jos mietin paljonko pyytäisin vastaavasta positiosta palkkaa muissa yrityksissä, mutta varsin tarpeeksi nykyisessä yrityksessä.
 
1
Yritys Yhdysvalloista, kuten suurin osa tiimiäkin. Presenssi myös Suomessa
 
1
Lykkyä tykö vapaakenttien normalisointiin!
 
1
Työnantaja maksaa etätoimiston vuokran ja nettiyhteyteni, näitä en laskenut vuosiansioihin mukaan.
 
1
Erittäin osaava, 20 vuotta harrastanut koodari, jolla on työkokemukseen nähden suuremmat kyvyt kuin useilla muilla. AMK-koulutus
 
1
Kiitos vaivannäöstä tämän kyselyn järjestämiseksi!
 
1
Relevantti työkokemukseni voisi olla vähän enemmänkin, ei kuitenkaan kahta vuotta.
 
1
Hyvinvointietu 500e/vuosi + henkilökohtainen opiskelubudgetti
 
1
Ulkomailla.
 
1
Olen alanvaihtaja, joten varsinaista työkokemusta devaajana on vähän, mutta domain-osaamista aiemman uran kautta paljon, joka vaikuttaa hieman palkkaan.
 
1
Vastasin nyt yhden työnantajan mukaan, jolle teen 80% työaikaa. Teen myös 20% työaikaa eri työnantajalle ja sektorille mutta en huomioinut sitä vastauksissa koska menisi sekavaksi.
 
1
Experis Academy(yritys, jossa olen palkkalistoilla) on kansainvälinen yritys, joka on tarkoitettu uran alkuvaiheessa oleville koodareille, jonka tarkoituksena on kouluttaa konsultteja 3kk intensiivijakson aikana. Palkka hieman parempi kuin junior-koodareilla, mutta toisaalta myös voidaan vaatiakin hieman enemmän osaamista
 
1
Other values (21)
21 

Length

Max length323
Median length98
Mean length111.5609756
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.

Common Values

ValueCountFrequency (%)
Työsuhteessa ulkomaalaiseen firmaan, ainoastaan palkanmaksu menee oman firman kautta1
 
0.1%
kokemusta jo kolme viikkoa it alalta1
 
0.1%
Laskuttavan työn lisäksi teen tuotekehitystä omaan b2c SaaS-palveluun, josta maksan itselleni myös palkkaa.1
 
0.1%
tietyn palkkatason jälkeen työntekijät alkavat ottamaan enemmän lomaa ja vapaa-aika. Se on eri asia kuin 100% allokaatio työtä tehdessä ja vaikuttaa vuosituloihin. Pääomatulot työnantajan osakkeilla taas voivat usein olla kerta luontoisia, mutta tuoda paljonkin lisätuloja 1
 
0.1%
Tällä hetkellä sopparit tehdään 1v kerrallaan. Firman muoto OY.1
 
0.1%
Yrittäjähenkisessä työskentelyssä ei usein lasketa työtunteja. Siten esim. 90% työaika on aika näennäinen. Välillä tehdään kovempaa ja välillä rauhallisemmin.1
 
0.1%
En oo ihan varma miten muut toisissa vastaavan kokoluokan yrityksissä saa palkkaa vastaavasta roolista.1
 
0.1%
Koulu vielä kesken ja se vaikuttaa palkkaan1
 
0.1%
Palkka ei ole kilpailukykyinen, jos mietin paljonko pyytäisin vastaavasta positiosta palkkaa muissa yrityksissä, mutta varsin tarpeeksi nykyisessä yrityksessä.1
 
0.1%
Yritys Yhdysvalloista, kuten suurin osa tiimiäkin. Presenssi myös Suomessa1
 
0.1%
Other values (31)31
 
4.5%
(Missing)643
94.0%

Length

2022-10-19T09:13:38.131585image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
on15
 
2.6%
ja12
 
2.1%
mutta9
 
1.6%
ei7
 
1.2%
myös6
 
1.1%
enemmän6
 
1.1%
palkkaa6
 
1.1%
palkka5
 
0.9%
että5
 
0.9%
5
 
0.9%
Other values (405)495
86.7%

Most occurring characters

ValueCountFrequency (%)
a551
12.0%
534
11.7%
i369
 
8.1%
t365
 
8.0%
n314
 
6.9%
s294
 
6.4%
e263
 
5.7%
k242
 
5.3%
l220
 
4.8%
o213
 
4.7%
Other values (58)1209
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3824
83.6%
Space Separator534
 
11.7%
Other Punctuation95
 
2.1%
Uppercase Letter68
 
1.5%
Decimal Number29
 
0.6%
Dash Punctuation11
 
0.2%
Math Symbol5
 
0.1%
Close Punctuation4
 
0.1%
Open Punctuation3
 
0.1%
Control1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a551
14.4%
i369
9.6%
t365
9.5%
n314
 
8.2%
s294
 
7.7%
e263
 
6.9%
k242
 
6.3%
l220
 
5.8%
o213
 
5.6%
u174
 
4.6%
Other values (15)819
21.4%
Uppercase Letter
ValueCountFrequency (%)
K8
11.8%
S7
10.3%
V7
10.3%
P7
10.3%
O6
8.8%
E6
8.8%
T6
8.8%
Y4
 
5.9%
L3
 
4.4%
J2
 
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 (%)
08
27.6%
15
17.2%
34
13.8%
24
13.8%
83
 
10.3%
53
 
10.3%
71
 
3.4%
91
 
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 (%)
Latin3892
85.1%
Common682
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a551
14.2%
i369
9.5%
t365
9.4%
n314
 
8.1%
s294
 
7.6%
e263
 
6.8%
k242
 
6.2%
l220
 
5.7%
o213
 
5.5%
u174
 
4.5%
Other values (33)887
22.8%
Common
ValueCountFrequency (%)
534
78.3%
.41
 
6.0%
,40
 
5.9%
-11
 
1.6%
08
 
1.2%
15
 
0.7%
%4
 
0.6%
34
 
0.6%
24
 
0.6%
)4
 
0.6%
Other values (15)27
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4392
96.0%
None182
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a551
12.5%
534
12.2%
i369
 
8.4%
t365
 
8.3%
n314
 
7.1%
s294
 
6.7%
e263
 
6.0%
k242
 
5.5%
l220
 
5.0%
o213
 
4.8%
Other values (56)1027
23.4%
None
ValueCountFrequency (%)
ä146
80.2%
ö36
 
19.8%

Ideoita ensi vuoden kyselyyn
Categorical

MISSING
UNIFORM

Distinct31
Distinct (%)100.0%
Missing653
Missing (%)95.5%
Memory size5.5 KiB
Tämä oli mukavan lyhyt ja ytimekäs
 
1
mietityttää, olisiko kuitenkin koulutustausta relevantti tieto?
 
1
Kyselyn voisi toteuttaa myös englanniksi, sillä suomessa työskentelee paljon suomea taitamattomia :)
 
1
Aikanaan, kun toteutin laajan palkkatutkimuksen ohjelmistoalalle, sisällytin mukaan monia kysymyksiä työntekijöiden rooleista, arvoista, koulutustasosta ja tehtävänimikkeistä. Näistä sai sitten todella mielenkiintoista tietoa yhdistettynä palkkatietoihin. Vuosilaskutus on sellainen tapa kysyä palkkaa, että se johtaa helposti harhaan. Mitä jos on korkea laskutus, mutta päättää tehdä kuusituntista viikkoa? Mitä jos on vanhempainvapaalla puolet vuodesta? Tällaisella yhdellä vuosilaskutusta koskevalla kysymyksellä saa helposti harhaanjohtavia vastauksia.
 
1
Millä kielillä koodaa? Millä alustoilla?
 
1
Palkan kilpailukykyisyyttä voisi arvioida skaalalla 1-5 eikä vain kyllä/ei....
 
1
Voisi kysellä kuinka paljon työajasta voi käyttää itseopiskeluun tai muuhun ei suoraan tuottavaan työhön.
 
1
Työsuhde-edut ois kiva olla erillisenä kysymyksenä.
 
1
Työsuhde-edut
 
1
Ehkä joku työsuhde-edut rahallisesti osuus myös?
 
1
Kompensaatioon sitomaton omistus, esim. founder yms. roolit.
 
1
Koulutusta voisi kysyä ja onko se vielä kesken
 
1
Olisko siistiä vertailla palkkoja kans teknologiakohtaisest kyselemällä vaikkapa tärkeimmät teknologiat työssäsi?
 
1
Pizza-alennuskoodia mukaan!!!
 
1
Ehkä laskuttajilta vois kysyy firman muotoa (vai onko OY niin de facto ettei kannata?). Toinen mitä voisi kysyä on se, että kuinka isoa palkkaa itselleen maksaa, jos maksaa.
 
1
Mitä työsuhde-etuja (työmatkaetu, lounasetu, jne.) saat? Koulutustausta? Onko sinulla sertifikaatioita, ja jos on, mitä? Teetkö sivukeikkoja, ja jos teet , mitä?
 
1
Ehkä se koulutus liittyy myös tähän palkkaan
 
1
voisi lisätä ohjelmointikielet - saisi samalla kerättyä tietoa mihin suuntaan markkina on menossa.
 
1
Kyselyn voisi toteuttaa myös englanniksi?
 
1
Olisi mielenkiintoista tietää, paljonko pitää lomaa/vapaata päivinä tai viikkoina vuodessa
 
1
Other values (11)
11 

Length

Max length558
Median length89
Mean length96.80645161
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

Common Values

ValueCountFrequency (%)
Tämä oli mukavan lyhyt ja ytimekäs1
 
0.1%
mietityttää, olisiko kuitenkin koulutustausta relevantti tieto?1
 
0.1%
Kyselyn voisi toteuttaa myös englanniksi, sillä suomessa työskentelee paljon suomea taitamattomia :)1
 
0.1%
Aikanaan, kun toteutin laajan palkkatutkimuksen ohjelmistoalalle, sisällytin mukaan monia kysymyksiä työntekijöiden rooleista, arvoista, koulutustasosta ja tehtävänimikkeistä. Näistä sai sitten todella mielenkiintoista tietoa yhdistettynä palkkatietoihin. Vuosilaskutus on sellainen tapa kysyä palkkaa, että se johtaa helposti harhaan. Mitä jos on korkea laskutus, mutta päättää tehdä kuusituntista viikkoa? Mitä jos on vanhempainvapaalla puolet vuodesta? Tällaisella yhdellä vuosilaskutusta koskevalla kysymyksellä saa helposti harhaanjohtavia vastauksia.1
 
0.1%
Millä kielillä koodaa? Millä alustoilla?1
 
0.1%
Palkan kilpailukykyisyyttä voisi arvioida skaalalla 1-5 eikä vain kyllä/ei....1
 
0.1%
Voisi kysellä kuinka paljon työajasta voi käyttää itseopiskeluun tai muuhun ei suoraan tuottavaan työhön.1
 
0.1%
Työsuhde-edut ois kiva olla erillisenä kysymyksenä.1
 
0.1%
Työsuhde-edut1
 
0.1%
Ehkä joku työsuhde-edut rahallisesti osuus myös?1
 
0.1%
Other values (21)21
 
3.1%
(Missing)653
95.5%

Length

2022-10-19T09:13:38.257351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
voisi11
 
3.0%
on8
 
2.2%
ja7
 
1.9%
mitä7
 
1.9%
jos5
 
1.4%
onko5
 
1.4%
kysyä5
 
1.4%
myös5
 
1.4%
se4
 
1.1%
ehkä4
 
1.1%
Other values (267)304
83.3%

Most occurring characters

ValueCountFrequency (%)
338
11.3%
a323
10.8%
t262
 
8.7%
i254
 
8.5%
s220
 
7.3%
o178
 
5.9%
e164
 
5.5%
l163
 
5.4%
k153
 
5.1%
n147
 
4.9%
Other values (44)799
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2517
83.9%
Space Separator338
 
11.3%
Other Punctuation81
 
2.7%
Uppercase Letter44
 
1.5%
Dash Punctuation8
 
0.3%
Decimal Number4
 
0.1%
Close Punctuation3
 
0.1%
Control2
 
0.1%
Open Punctuation2
 
0.1%
Other Symbol2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a323
12.8%
t262
10.4%
i254
10.1%
s220
8.7%
o178
 
7.1%
e164
 
6.5%
l163
 
6.5%
k153
 
6.1%
n147
 
5.8%
u126
 
5.0%
Other values (14)527
20.9%
Uppercase Letter
ValueCountFrequency (%)
T9
20.5%
M7
15.9%
K6
13.6%
O5
11.4%
E4
9.1%
V3
 
6.8%
P2
 
4.5%
J2
 
4.5%
S1
 
2.3%
F1
 
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 (%)
53
75.0%
11
 
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 (%)
Latin2561
85.3%
Common440
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a323
12.6%
t262
10.2%
i254
9.9%
s220
 
8.6%
o178
 
7.0%
e164
 
6.4%
l163
 
6.4%
k153
 
6.0%
n147
 
5.7%
u126
 
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%
53
 
0.7%
/3
 
0.7%
!3
 
0.7%
Other values (6)8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2882
96.0%
None117
 
3.9%
Emoticons2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338
11.7%
a323
11.2%
t262
 
9.1%
i254
 
8.8%
s220
 
7.6%
o178
 
6.2%
e164
 
5.7%
l163
 
5.7%
k153
 
5.3%
n147
 
5.1%
Other values (40)680
23.6%
None
ValueCountFrequency (%)
ä94
80.3%
ö23
 
19.7%
Emoticons
ValueCountFrequency (%)
😍1
50.0%
😄1
50.0%

Etä
Categorical

MISSING

Distinct3
Distinct (%)0.5%
Missing80
Missing (%)11.7%
Memory size944.0 B
Etä
343 
50/50
185 
Toimisto
76 

Length

Max length8
Median length3
Mean length4.241721854
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 (%)
Etä343
50.1%
50/50185
27.0%
Toimisto76
 
11.1%
(Missing)80
 
11.7%

Length

2022-10-19T09:13:38.366107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-19T09:13:38.571818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
etä343
56.8%
50/50185
30.6%
toimisto76
 
12.6%

Most occurring characters

ValueCountFrequency (%)
t419
16.4%
5370
14.4%
0370
14.4%
E343
13.4%
ä343
13.4%
/185
7.2%
o152
 
5.9%
i152
 
5.9%
T76
 
3.0%
m76
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1218
47.5%
Decimal Number740
28.9%
Uppercase Letter419
 
16.4%
Other Punctuation185
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t419
34.4%
ä343
28.2%
o152
 
12.5%
i152
 
12.5%
m76
 
6.2%
s76
 
6.2%
Decimal Number
ValueCountFrequency (%)
5370
50.0%
0370
50.0%
Uppercase Letter
ValueCountFrequency (%)
E343
81.9%
T76
 
18.1%
Other Punctuation
ValueCountFrequency (%)
/185
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1637
63.9%
Common925
36.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t419
25.6%
E343
21.0%
ä343
21.0%
o152
 
9.3%
i152
 
9.3%
T76
 
4.6%
m76
 
4.6%
s76
 
4.6%
Common
ValueCountFrequency (%)
5370
40.0%
0370
40.0%
/185
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2219
86.6%
None343
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t419
18.9%
5370
16.7%
0370
16.7%
E343
15.5%
/185
8.3%
o152
 
6.8%
i152
 
6.8%
T76
 
3.4%
m76
 
3.4%
s76
 
3.4%
None
ValueCountFrequency (%)
ä343
100.0%

Kk-tulot
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct233
Distinct (%)39.2%
Missing90
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean5754.086045
Minimum0
Maximum29166.66667
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2022-10-19T09:13:38.673069image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2776.041667
Q14484.375
median5416.666667
Q36666.666667
95-th percentile9239.583333
Maximum29166.66667
Range29166.66667
Interquartile range (IQR)2182.291667

Descriptive statistics

Standard deviation2537.114133
Coefficient of variation (CV)0.4409239127
Kurtosis19.30540031
Mean5754.086045
Median Absolute Deviation (MAD)1046.333333
Skewness2.909934441
Sum3417927.111
Variance6436948.123
MonotonicityNot monotonic
2022-10-19T09:13:38.790074image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500023
 
3.4%
5833.33333318
 
2.6%
5208.33333315
 
2.2%
4166.66666715
 
2.2%
6666.66666713
 
1.9%
5416.66666713
 
1.9%
8333.33333313
 
1.9%
625012
 
1.8%
750010
 
1.5%
4791.66666710
 
1.5%
Other values (223)452
66.1%
(Missing)90
 
13.2%
ValueCountFrequency (%)
01
0.1%
41.666666671
0.1%
83.333333331
0.1%
166.66666671
0.1%
208.33333331
0.1%
333.33333331
0.1%
4001
0.1%
416.66666671
0.1%
421.83333331
0.1%
937.51
0.1%
ValueCountFrequency (%)
29166.666671
0.1%
24166.666671
0.1%
18333.333331
0.1%
175001
0.1%
16666.666672
0.3%
15666.666671
0.1%
14166.666671
0.1%
13333.333332
0.3%
130001
0.1%
125002
0.3%

Interactions

2022-10-19T09:13:31.909799image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:26.593070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.458695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.174545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.849140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.632773image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.359625image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.061338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.005710image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:26.702212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.553482image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.262952image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.938719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.729670image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.450894image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.160179image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.084840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:26.891243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.656811image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.357433image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.143737image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.808853image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.530543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.243183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.162041image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:26.977328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.748860image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.443722image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.230424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.886560image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.608815image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.427395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.239207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.067425image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.846570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.531264image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.321339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.963886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.688008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.504925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.340169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.167737image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.928766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.610374image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.399027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.064765image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.783643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.608280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.431183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.257875image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.011483image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.690984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.477233image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.156571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.869414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.702302image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:32.534544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:27.360214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.093162image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:28.770573image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:29.555230image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.259975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:30.967137image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-10-19T09:13:31.807778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-10-19T09:13:38.897243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-10-19T09:13:39.063131image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-10-19T09:13:39.220767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Missing values

2022-10-19T09:13:32.728380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-10-19T09:13:33.359013image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-10-19T09:13:33.846294image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-10-19T09:13:34.290800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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

Last rows

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