Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	428
Missing cells	1003
Missing cells (%)	16.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	36.6 KiB
Average record size in memory	87.5 B

Variable types

DateTime	1
Categorical	9
Numeric	3
Boolean	1

Warnings

`Rooli` has a high cardinality: 228 distinct values	High cardinality
`Työpaikka` has a high cardinality: 67 distinct values	High cardinality
`Työpaikka` is highly correlated with `Vapaa sana`	High correlation
`Vapaa sana` is highly correlated with `Työpaikka` and 1 other fields	High correlation
`Kilpailukykyinen` is highly correlated with `Vapaa sana`	High correlation
`Sukupuoli` has 32 (7.5%) missing values	Missing
`Työaika` has 16 (3.7%) missing values	Missing
`Rooli` has 10 (2.3%) missing values	Missing
`Etä` has 146 (34.1%) missing values	Missing
`Kuukausipalkka` has 38 (8.9%) missing values	Missing
`Vuositulot` has 11 (2.6%) missing values	Missing
`Kilpailukykyinen` has 14 (3.3%) missing values	Missing
`Työpaikka` has 330 (77.1%) missing values	Missing
`Vapaa sana` has 395 (92.3%) missing values	Missing
`Vapaa sana` is uniformly distributed	Uniform
`Timestamp` has unique values	Unique

Reproduction

Analysis started	2021-02-19 15:58:09.896543
Analysis finished	2021-02-19 15:58:13.907467
Duration	4.01 seconds
Software version	pandas-profiling v2.10.1
Download configuration	config.yaml

Timestamp
Date

UNIQUE

Distinct	428
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	3.5 KiB

Minimum	2021-02-15 11:57:08.316000
Maximum	2021-02-19 17:51:37.178000

Histogram

Histogram with fixed size bins (bins=50)

Kaupunki
Categorical

Distinct	25
Distinct (%)	5.9%
Missing	4
Missing (%)	0.9%
Memory size	1.3 KiB

PK-Seutu	218
Tampere	99
Turku	43
Oulu	22
Jyväskylä	17
Other values (20)	25

Length

Max length	15
Median length	8
Mean length	7.257075472
Min length	2

Characters and Unicode

Total characters	3077
Distinct characters	39
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	4.2%

Sample

1st row	PK-Seutu
2nd row	Turku
3rd row	PK-Seutu
4th row	Tampere
5th row	PK-Seutu

Value	Count	Frequency (%)
PK-Seutu	218	50.9%
Tampere	99	23.1%
Turku	43	10.0%
Oulu	22	5.1%
Jyväskylä	17	4.0%
Kuopio	5	1.2%
Pori	2	0.5%
Ruotsi	1	0.2%
Wien	1	0.2%
Viimsi	1	0.2%
Other values (15)	15	3.5%
(Missing)	4	0.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
pk-seutu	218	50.9%
tampere	99	23.1%
turku	43	10.0%
oulu	22	5.1%
jyväskylä	17	4.0%
kuopio	5	1.2%
pori	2	0.5%
lahti	1	0.2%
tallinna	1	0.2%
etänä	1	0.2%
Other values (19)	19	4.4%

Most occurring characters

Value	Count	Frequency (%)
u	578	18.8%
e	425	13.8%
K	226	7.3%
t	223	7.2%
P	221	7.2%
-	220	7.1%
S	220	7.1%
r	148	4.8%
T	143	4.6%
a	116	3.8%
Other values (29)	557	18.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1987	64.6%
Uppercase Letter	865	28.1%
Dash Punctuation	220	7.1%
Space Separator	4	0.1%
Other Punctuation	1	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
u	578	29.1%
e	425	21.4%
t	223	11.2%
r	148	7.4%
a	116	5.8%
p	105	5.3%
m	103	5.2%
k	61	3.1%
l	47	2.4%
ä	41	2.1%
Other values (10)	140	7.0%

Value	Count	Frequency (%)
K	226	26.1%
P	221	25.5%
S	220	25.4%
T	143	16.5%
O	22	2.5%
J	18	2.1%
E	3	0.3%
L	3	0.3%
V	2	0.2%
W	1	0.1%
Other values (6)	6	0.7%

Value	Count	Frequency (%)
-	220	100.0%

Value	Count	Frequency (%)
	4	100.0%

Value	Count	Frequency (%)
,	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2852	92.7%
Common	225	7.3%

Most frequent character per script

Value	Count	Frequency (%)
u	578	20.3%
e	425	14.9%
K	226	7.9%
t	223	7.8%
P	221	7.7%
S	220	7.7%
r	148	5.2%
T	143	5.0%
a	116	4.1%
p	105	3.7%
Other values (26)	447	15.7%

Value	Count	Frequency (%)
-	220	97.8%
	4	1.8%
,	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3036	98.7%
None	41	1.3%

Most frequent character per block

Value	Count	Frequency (%)
u	578	19.0%
e	425	14.0%
K	226	7.4%
t	223	7.3%
P	221	7.3%
-	220	7.2%
S	220	7.2%
r	148	4.9%
T	143	4.7%
a	116	3.8%
Other values (28)	516	17.0%

Value	Count	Frequency (%)
ä	41	100.0%

Ikä
Categorical

Distinct	7
Distinct (%)	1.6%
Missing	2
Missing (%)	0.5%
Memory size	912.0 B

31-35 v	142
26-30 v	104
36-40 v	94
41-45 v	47
21-25 v	27
Other values (2)	12

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	2982
Distinct characters	10
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	31-35 v
2nd row	31-35 v
3rd row	26-30 v
4th row	31-35 v
5th row	26-30 v

Value	Count	Frequency (%)
31-35 v	142	33.2%
26-30 v	104	24.3%
36-40 v	94	22.0%
41-45 v	47	11.0%
21-25 v	27	6.3%
46-50 v	7	1.6%
51-55 v	5	1.2%
(Missing)	2	0.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
v	426	50.0%
31-35	142	16.7%
26-30	104	12.2%
36-40	94	11.0%
41-45	47	5.5%
21-25	27	3.2%
46-50	7	0.8%
51-55	5	0.6%

Most occurring characters

Value	Count	Frequency (%)
3	482	16.2%
-	426	14.3%
	426	14.3%
v	426	14.3%
5	238	8.0%
1	221	7.4%
6	205	6.9%
0	205	6.9%
4	195	6.5%
2	158	5.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1704	57.1%
Dash Punctuation	426	14.3%
Space Separator	426	14.3%
Lowercase Letter	426	14.3%

Most frequent character per category

Value	Count	Frequency (%)
3	482	28.3%
5	238	14.0%
1	221	13.0%
6	205	12.0%
0	205	12.0%
4	195	11.4%
2	158	9.3%

Value	Count	Frequency (%)
-	426	100.0%

Value	Count	Frequency (%)
	426	100.0%

Value	Count	Frequency (%)
v	426	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2556	85.7%
Latin	426	14.3%

Most frequent character per script

Value	Count	Frequency (%)
3	482	18.9%
-	426	16.7%
	426	16.7%
5	238	9.3%
1	221	8.6%
6	205	8.0%
0	205	8.0%
4	195	7.6%
2	158	6.2%

Value	Count	Frequency (%)
v	426	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2982	100.0%

Most frequent character per block

Value	Count	Frequency (%)
3	482	16.2%
-	426	14.3%
	426	14.3%
v	426	14.3%
5	238	8.0%
1	221	7.4%
6	205	6.9%
0	205	6.9%
4	195	6.5%
2	158	5.3%

Sukupuoli
Categorical

MISSING

Distinct	3
Distinct (%)	0.8%
Missing	32
Missing (%)	7.5%
Memory size	688.0 B

mies	359
nainen	29
muu	8

Length

Max length	6
Median length	4
Mean length	4.126262626
Min length	3

Characters and Unicode

Total characters	1634
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	mies
2nd row	mies
3rd row	mies
4th row	mies
5th row	mies

Value	Count	Frequency (%)
mies	359	83.9%
nainen	29	6.8%
muu	8	1.9%
(Missing)	32	7.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
mies	359	90.7%
nainen	29	7.3%
muu	8	2.0%

Most occurring characters

Value	Count	Frequency (%)
i	388	23.7%
e	388	23.7%
m	367	22.5%
s	359	22.0%
n	87	5.3%
a	29	1.8%
u	16	1.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1634	100.0%

Most frequent character per category

Value	Count	Frequency (%)
i	388	23.7%
e	388	23.7%
m	367	22.5%
s	359	22.0%
n	87	5.3%
a	29	1.8%
u	16	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1634	100.0%

Most frequent character per script

Value	Count	Frequency (%)
i	388	23.7%
e	388	23.7%
m	367	22.5%
s	359	22.0%
n	87	5.3%
a	29	1.8%
u	16	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1634	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	388	23.7%
e	388	23.7%
m	367	22.5%
s	359	22.0%
n	87	5.3%
a	29	1.8%
u	16	1.0%

Työkokemus
Real number (ℝ_≥0)

Distinct	27
Distinct (%)	6.4%
Missing	4
Missing (%)	0.9%
Infinite	0
Infinite (%)	0.0%

Mean	9.636792453
Minimum	0
Maximum	30
Zeros	3
Zeros (%)	0.7%
Memory size	3.5 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	5
median	9
Q3	13
95-th percentile	21
Maximum	30
Range	30
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	6.058045866
Coefficient of variation (CV)	0.6286371628
Kurtosis	-0.03943807906
Mean	9.636792453
Median Absolute Deviation (MAD)	4
Skewness	0.7090849042
Sum	4086
Variance	36.69991971
Monotocity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
5	44	10.3%
10	34	7.9%
4	29	6.8%
7	26	6.1%
15	25	5.8%
20	25	5.8%
3	24	5.6%
13	23	5.4%
2	22	5.1%
11	22	5.1%
Other values (17)	150	35.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	0.7%
1	15	3.5%
2	22	5.1%
3	24	5.6%
4	29	6.8%

Value	Count	Frequency (%)
30	2	0.5%
25	5	1.2%
24	2	0.5%
23	4	0.9%
22	4	0.9%

Työsuhteen luonne
Categorical

Distinct	3
Distinct (%)	0.7%
Missing	1
Missing (%)	0.2%
Memory size	3.5 KiB

Työntekijä / palkollinen	382
Freelancer	23
Yrittäjä	22

Length

Max length	24
Median length	24
Mean length	22.42154567
Min length	8

Characters and Unicode

Total characters	9574
Distinct characters	20
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Työntekijä / palkollinen
2nd row	Työntekijä / palkollinen
3rd row	Työntekijä / palkollinen
4th row	Yrittäjä
5th row	Työntekijä / palkollinen

Value	Count	Frequency (%)
Työntekijä / palkollinen	382	89.3%
Freelancer	23	5.4%
Yrittäjä	22	5.1%
(Missing)	1	0.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
	382	32.1%
palkollinen	382	32.1%
työntekijä	382	32.1%
freelancer	23	1.9%
yrittäjä	22	1.8%

Most occurring characters

Value	Count	Frequency (%)
n	1169	12.2%
l	1169	12.2%
e	833	8.7%
i	786	8.2%
k	764	8.0%
	764	8.0%
t	426	4.4%
ä	426	4.4%
a	405	4.2%
j	404	4.2%
Other values (10)	2428	25.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8001	83.6%
Space Separator	764	8.0%
Uppercase Letter	427	4.5%
Other Punctuation	382	4.0%

Most frequent character per category

Value	Count	Frequency (%)
n	1169	14.6%
l	1169	14.6%
e	833	10.4%
i	786	9.8%
k	764	9.5%
t	426	5.3%
ä	426	5.3%
a	405	5.1%
j	404	5.0%
y	382	4.8%
Other values (5)	1237	15.5%

Value	Count	Frequency (%)
T	382	89.5%
F	23	5.4%
Y	22	5.2%

Value	Count	Frequency (%)
	764	100.0%

Value	Count	Frequency (%)
/	382	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8428	88.0%
Common	1146	12.0%

Most frequent character per script

Value	Count	Frequency (%)
n	1169	13.9%
l	1169	13.9%
e	833	9.9%
i	786	9.3%
k	764	9.1%
t	426	5.1%
ä	426	5.1%
a	405	4.8%
j	404	4.8%
T	382	4.5%
Other values (8)	1664	19.7%

Value	Count	Frequency (%)
	764	66.7%
/	382	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8766	91.6%
None	808	8.4%

Most frequent character per block

Value	Count	Frequency (%)
n	1169	13.3%
l	1169	13.3%
e	833	9.5%
i	786	9.0%
k	764	8.7%
	764	8.7%
t	426	4.9%
a	405	4.6%
j	404	4.6%
T	382	4.4%
Other values (8)	1664	19.0%

Value	Count	Frequency (%)
ä	426	52.7%
ö	382	47.3%

Työaika
Categorical

MISSING

Distinct	5
Distinct (%)	1.2%
Missing	16
Missing (%)	3.7%
Memory size	3.5 KiB

1.0	388
0.8	20
0.5	2
0.6	1
0.7	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1236
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.5%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Value	Count	Frequency (%)
1.0	388	90.7%
0.8	20	4.7%
0.5	2	0.5%
0.6	1	0.2%
0.7	1	0.2%
(Missing)	16	3.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
1.0	388	94.2%
0.8	20	4.9%
0.5	2	0.5%
0.6	1	0.2%
0.7	1	0.2%

Most occurring characters

Value	Count	Frequency (%)
.	412	33.3%
0	412	33.3%
1	388	31.4%
8	20	1.6%
5	2	0.2%
7	1	0.1%
6	1	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	824	66.7%
Other Punctuation	412	33.3%

Most frequent character per category

Value	Count	Frequency (%)
0	412	50.0%
1	388	47.1%
8	20	2.4%
5	2	0.2%
7	1	0.1%
6	1	0.1%

Value	Count	Frequency (%)
.	412	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1236	100.0%

Most frequent character per script

Value	Count	Frequency (%)
.	412	33.3%
0	412	33.3%
1	388	31.4%
8	20	1.6%
5	2	0.2%
7	1	0.1%
6	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1236	100.0%

Most frequent character per block

Value	Count	Frequency (%)
.	412	33.3%
0	412	33.3%
1	388	31.4%
8	20	1.6%
5	2	0.2%
7	1	0.1%
6	1	0.1%

Rooli
Categorical

HIGH CARDINALITY
MISSING

Distinct	228
Distinct (%)	54.5%
Missing	10
Missing (%)	2.3%
Memory size	3.5 KiB

Ohjelmistokehittäjä	33
full-stack	30
Full-stack	21
Arkkitehti	15
ohjelmistokehittäjä	15
Other values (223)	304

Length

Max length	67
Median length	18
Mean length	19.18660287
Min length	2

Characters and Unicode

Total characters	8020
Distinct characters	57
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	184 ?
Unique (%)	44.0%

Sample

1st row	Arkkitehti
2nd row	full-stack
3rd row	Full-stack ohjelmistokehittäjä
4th row	web-arkkitehti
5th row	Ohjelmistokehittäjä

Value	Count	Frequency (%)
Ohjelmistokehittäjä	33	7.7%
full-stack	30	7.0%
Full-stack	21	4.9%
Arkkitehti	15	3.5%
ohjelmistokehittäjä	15	3.5%
Full-stack ohjelmistokehittäjä	8	1.9%
full-stack ohjelmistokehittäjä	6	1.4%
arkkitehti	6	1.4%
Full-stack kehittäjä	5	1.2%
DevOps	5	1.2%
Other values (218)	274	64.0%
(Missing)	10	2.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
full-stack	127	16.5%
ohjelmistokehittäjä	100	13.0%
developer	52	6.8%
arkkitehti	34	4.4%
	30	3.9%
lead	28	3.6%
frontend	24	3.1%
senior	18	2.3%
kehittäjä	15	2.0%
backend	14	1.8%
Other values (165)	327	42.5%

Most occurring characters

Value	Count	Frequency (%)
t	840	10.5%
e	735	9.2%
i	590	7.4%
l	585	7.3%
k	451	5.6%
o	419	5.2%
s	383	4.8%
a	382	4.8%
	356	4.4%
h	322	4.0%
Other values (47)	2957	36.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6972	86.9%
Uppercase Letter	396	4.9%
Space Separator	357	4.5%
Dash Punctuation	153	1.9%
Other Punctuation	86	1.1%
Open Punctuation	24	0.3%
Close Punctuation	24	0.3%
Math Symbol	8	0.1%

Most frequent character per category

Value	Count	Frequency (%)
t	840	12.0%
e	735	10.5%
i	590	8.5%
l	585	8.4%
k	451	6.5%
o	419	6.0%
s	383	5.5%
a	382	5.5%
h	322	4.6%
j	301	4.3%
Other values (16)	1964	28.2%

Value	Count	Frequency (%)
F	90	22.7%
O	80	20.2%
S	45	11.4%
D	39	9.8%
A	24	6.1%
T	20	5.1%
L	17	4.3%
C	13	3.3%
E	11	2.8%
P	10	2.5%
Other values (11)	47	11.9%

Value	Count	Frequency (%)
,	50	58.1%
/	32	37.2%
&	3	3.5%
.	1	1.2%

Value	Count	Frequency (%)
	356	99.7%
	1	0.3%

Value	Count	Frequency (%)
-	153	100.0%

Value	Count	Frequency (%)
(	24	100.0%

Value	Count	Frequency (%)
)	24	100.0%

Value	Count	Frequency (%)
+	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7368	91.9%
Common	652	8.1%

Most frequent character per script

Value	Count	Frequency (%)
t	840	11.4%
e	735	10.0%
i	590	8.0%
l	585	7.9%
k	451	6.1%
o	419	5.7%
s	383	5.2%
a	382	5.2%
h	322	4.4%
j	301	4.1%
Other values (37)	2360	32.0%

Value	Count	Frequency (%)
	356	54.6%
-	153	23.5%
,	50	7.7%
/	32	4.9%
(	24	3.7%
)	24	3.7%
+	8	1.2%
&	3	0.5%
.	1	0.2%
	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7716	96.2%
None	304	3.8%

Most frequent character per block

Value	Count	Frequency (%)
t	840	10.9%
e	735	9.5%
i	590	7.6%
l	585	7.6%
k	451	5.8%
o	419	5.4%
s	383	5.0%
a	382	5.0%
	356	4.6%
h	322	4.2%
Other values (44)	2653	34.4%

Value	Count	Frequency (%)
ä	288	94.7%
ö	15	4.9%
	1	0.3%

Etä
Categorical

MISSING

Distinct	2
Distinct (%)	0.7%
Missing	146
Missing (%)	34.1%
Memory size	680.0 B

Etä	180
50/50	102

Length

Max length	5
Median length	3
Mean length	3.723404255
Min length	3

Characters and Unicode

Total characters	1050
Distinct characters	6
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	50/50
2nd row	Etä
3rd row	Etä
4th row	Etä
5th row	Etä

Value	Count	Frequency (%)
Etä	180	42.1%
50/50	102	23.8%
(Missing)	146	34.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
etä	180	63.8%
50/50	102	36.2%

Most occurring characters

Value	Count	Frequency (%)
5	204	19.4%
0	204	19.4%
E	180	17.1%
t	180	17.1%
ä	180	17.1%
/	102	9.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	408	38.9%
Lowercase Letter	360	34.3%
Uppercase Letter	180	17.1%
Other Punctuation	102	9.7%

Most frequent character per category

Value	Count	Frequency (%)
5	204	50.0%
0	204	50.0%

Value	Count	Frequency (%)
t	180	50.0%
ä	180	50.0%

Value	Count	Frequency (%)
/	102	100.0%

Value	Count	Frequency (%)
E	180	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	540	51.4%
Common	510	48.6%

Most frequent character per script

Value	Count	Frequency (%)
5	204	40.0%
0	204	40.0%
/	102	20.0%

Value	Count	Frequency (%)
E	180	33.3%
t	180	33.3%
ä	180	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	870	82.9%
None	180	17.1%

Most frequent character per block

Value	Count	Frequency (%)
5	204	23.4%
0	204	23.4%
E	180	20.7%
t	180	20.7%
/	102	11.7%

Value	Count	Frequency (%)
ä	180	100.0%

Kuukausipalkka
Real number (ℝ_≥0)

MISSING

Distinct	117
Distinct (%)	30.0%
Missing	38
Missing (%)	8.9%
Infinite	0
Infinite (%)	0.0%

Mean	4676.174359
Minimum	1666
Maximum	15000
Zeros	0
Zeros (%)	0.0%
Memory size	3.5 KiB

Quantile statistics

Minimum	1666
5-th percentile	2809
Q1	3862.5
median	4500
Q3	5500
95-th percentile	7000
Maximum	15000
Range	13334
Interquartile range (IQR)	1637.5

Descriptive statistics

Standard deviation	1320.016661
Coefficient of variation (CV)	0.2822855949
Kurtosis	8.947538524
Mean	4676.174359
Median Absolute Deviation (MAD)	753
Skewness	1.480402915
Sum	1823708
Variance	1742443.985
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4000	23	5.4%
4500	20	4.7%
6000	16	3.7%
5500	15	3.5%
5000	15	3.5%
4800	11	2.6%
7000	11	2.6%
4300	11	2.6%
4200	10	2.3%
4100	9	2.1%
Other values (107)	249	58.2%
(Missing)	38	8.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1666	1	0.2%
1700	1	0.2%
1800	1	0.2%
2100	1	0.2%
2275	1	0.2%

Value	Count	Frequency (%)
15000	1	0.2%
8500	1	0.2%
8000	5	1.2%
7500	2	0.5%
7200	1	0.2%

Vuositulot
Real number (ℝ_≥0)

MISSING

Distinct	168
Distinct (%)	40.3%
Missing	11
Missing (%)	2.6%
Infinite	0
Infinite (%)	0.0%

Mean	65316.10671
Minimum	0
Maximum	250000
Zeros	2
Zeros (%)	0.5%
Memory size	3.5 KiB

Quantile statistics

Minimum	0
5-th percentile	35000
Q1	50000
median	60000
Q3	75000
95-th percentile	120000
Maximum	250000
Range	250000
Interquartile range (IQR)	25000

Descriptive statistics

Standard deviation	28626.85746
Coefficient of variation (CV)	0.4382817485
Kurtosis	8.41775568
Mean	65316.10671
Median Absolute Deviation (MAD)	12000
Skewness	2.170441848
Sum	27236816.5
Variance	819496967.9
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
55000	17	4.0%
75000	15	3.5%
50000	14	3.3%
60000	14	3.3%
65000	10	2.3%
85000	9	2.1%
62500	9	2.1%
80000	9	2.1%
70000	8	1.9%
54000	8	1.9%
Other values (158)	304	71.0%
(Missing)	11	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.5%
4000	1	0.2%
6100	1	0.2%
7500	1	0.2%
20000	1	0.2%

Value	Count	Frequency (%)
250000	1	0.2%
200000	3	0.7%
190000	1	0.2%
180000	1	0.2%
155000	1	0.2%

Kilpailukykyinen
Boolean

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.5%
Missing	14
Missing (%)	3.3%
Memory size	3.5 KiB

True	291
False	123
(Missing)	14

Common Values
Chart

Value	Count	Frequency (%)
True	291	68.0%
False	123	28.7%
(Missing)	14	3.3%

Työpaikka
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct	67
Distinct (%)	68.4%
Missing	330
Missing (%)	77.1%
Memory size	3.5 KiB

Gofore	11
Vincit	6
Fraktio	4
Futurice	4
Arado	3
Other values (62)	70

Length

Max length	132
Median length	7
Mean length	10.59183673
Min length	2

Characters and Unicode

Total characters	1038
Distinct characters	53
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	56 ?
Unique (%)	57.1%

Sample

1st row	Questrade
2nd row	Digia Oyj
3rd row	Gofore
4th row	Oura Health
5th row	Wirepas

Value	Count	Frequency (%)
Gofore	11	2.6%
Vincit	6	1.4%
Fraktio	4	0.9%
Futurice	4	0.9%
Arado	3	0.7%
Mavericks	3	0.7%
Pankki	3	0.7%
KVTES-alainen kunnan omistama oy	2	0.5%
Qvik	2	0.5%
Gofore Oyj	2	0.5%
Other values (57)	58	13.6%
(Missing)	330	77.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
gofore	13	8.4%
oy	9	5.8%
vincit	6	3.9%
fraktio	4	2.6%
mavericks	4	2.6%
oyj	4	2.6%
futurice	4	2.6%
pankki	3	1.9%
siili	3	1.9%
arado	3	1.9%
Other values (89)	102	65.8%

Most occurring characters

Value	Count	Frequency (%)
i	104	10.0%
a	82	7.9%
o	79	7.6%
e	73	7.0%
t	71	6.8%
	60	5.8%
r	57	5.5%
n	50	4.8%
l	41	3.9%
u	40	3.9%
Other values (43)	381	36.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	842	81.1%
Uppercase Letter	130	12.5%
Space Separator	60	5.8%
Other Punctuation	3	0.3%
Dash Punctuation	3	0.3%

Most frequent character per category

Value	Count	Frequency (%)
G	14	10.8%
O	13	10.0%
V	12	9.2%
S	11	8.5%
F	9	6.9%
A	7	5.4%
K	7	5.4%
C	6	4.6%
P	6	4.6%
E	5	3.8%
Other values (15)	40	30.8%

Value	Count	Frequency (%)
i	104	12.4%
a	82	9.7%
o	79	9.4%
e	73	8.7%
t	71	8.4%
r	57	6.8%
n	50	5.9%
l	41	4.9%
u	40	4.8%
k	40	4.8%
Other values (15)	205	24.3%

Value	Count	Frequency (%)
	60	100.0%

Value	Count	Frequency (%)
.	3	100.0%

Value	Count	Frequency (%)
-	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	972	93.6%
Common	66	6.4%

Most frequent character per script

Value	Count	Frequency (%)
i	104	10.7%
a	82	8.4%
o	79	8.1%
e	73	7.5%
t	71	7.3%
r	57	5.9%
n	50	5.1%
l	41	4.2%
u	40	4.1%
k	40	4.1%
Other values (40)	335	34.5%

Value	Count	Frequency (%)
	60	90.9%
.	3	4.5%
-	3	4.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1026	98.8%
None	12	1.2%

Most frequent character per block

Value	Count	Frequency (%)
i	104	10.1%
a	82	8.0%
o	79	7.7%
e	73	7.1%
t	71	6.9%
	60	5.8%
r	57	5.6%
n	50	4.9%
l	41	4.0%
u	40	3.9%
Other values (41)	369	36.0%

Value	Count	Frequency (%)
ä	11	91.7%
ö	1	8.3%

Vapaa sana
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct	32
Distinct (%)	97.0%
Missing	395
Missing (%)	92.3%
Memory size	3.5 KiB

palkan lisänä lounas- ja virkistysetu	2
Työskentelen opintojen ohella, ensimmäisessä frontend devaajan työssä. Olen opiskellut reilu 2 vuotta yliopistossa. Palkkani on mielestäni nyt ihan ok, mutta tarkoituksena nostaa sitä 3000e /kk loppukesään mennessä.	1
Vuositulot pitää sisällään myös sivutoimisena tehtyä pientä laskutusta.	1
Ihan OK. Edut myös kovat.	1
saispa lisää liksaa	1
Other values (27)	27

Length

Max length	286
Median length	71
Mean length	95.54545455
Min length	7

Characters and Unicode

Total characters	3153
Distinct characters	55
Distinct categories	9 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	31 ?
Unique (%)	93.9%

Sample

1st row	Kuukausipalkkaan tulossa ihan juuri firman laajuinen pieni (muistaakseni 50 e) yleiskorotus + palkka nousee ainakin 2800 e/kk, kunhan valmistuisi.
2nd row	Työskentelen toimistolla, koska täällä ei ole ketään muita. Työnantajan puolesta voisin työskennellä myös kotoa.
3rd row	palkan lisäksi kompensaatioon kuuluu varsin runsas ja suomen it-alalla uniikki etupaketti. pelkkä palkka ei välttämättä ole kilpailukykyinen, mutta koko kompensaatio yleisesti työstäni on ehdottomasti kilpailukykyinen.
4th row	Rahapalkan päälle tulee vielä kohtuullinen optiopotti, mutta se toki on lähinnä arpalippu
5th row	Osittain laskutukseen perustuva palkka joten vaihtelee.

Value	Count	Frequency (%)
palkan lisänä lounas- ja virkistysetu	2	0.5%
Työskentelen opintojen ohella, ensimmäisessä frontend devaajan työssä. Olen opiskellut reilu 2 vuotta yliopistossa. Palkkani on mielestäni nyt ihan ok, mutta tarkoituksena nostaa sitä 3000e /kk loppukesään mennessä.	1	0.2%
Vuositulot pitää sisällään myös sivutoimisena tehtyä pientä laskutusta.	1	0.2%
Ihan OK. Edut myös kovat.	1	0.2%
saispa lisää liksaa	1	0.2%
Sijainti Pori, mutta etätöitä 100%. Varsinainen positio Tampere - Helsinki. Edut aika huonot, perusjutut. Työ itsessään aika masentavaa. Seuraavaksi varmaan freelance/yrittäjyys.	1	0.2%
Startup	1	0.2%
palkan lisäksi kompensaatioon kuuluu varsin runsas ja suomen it-alalla uniikki etupaketti. pelkkä palkka ei välttämättä ole kilpailukykyinen, mutta koko kompensaatio yleisesti työstäni on ehdottomasti kilpailukykyinen.	1	0.2%
Vaikka merkitsin, että palkkani ei ole mielestäni kilpailukykyinen, se ei tarkoita ettenkö olisi siihen tyytyväinen. Tilanne yrittäjillä ei yleensä vastaa samaa kuin palkansaajilla, joten palkka ei ole yrittäjille monestikaan niin mustavalkoinen asia vaan kysymys on isommasta kuviosta.	1	0.2%
Vaikea vastata henkilönä joka tekee yrityksen kautta yhdelle ulkomaalaiselle yritykselle töitä (jolla ei ole entiteettiä suomessa). Vastasin nyt ikään kuin olisin yrittäjä vaikka käytännössä tämä on sama kuin olisin palkkaduunissa.	1	0.2%
Other values (22)	22	5.1%
(Missing)	395	92.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
ei	10	2.5%
palkka	9	2.3%
on	8	2.0%
mutta	6	1.5%
ole	6	1.5%
ja	6	1.5%
nyt	4	1.0%
firman	4	1.0%
joten	4	1.0%
palkan	4	1.0%
Other values (281)	334	84.6%

Most occurring characters

Value	Count	Frequency (%)
	365	11.6%
a	331	10.5%
i	271	8.6%
t	247	7.8%
n	216	6.9%
s	205	6.5%
e	203	6.4%
k	185	5.9%
l	161	5.1%
o	146	4.6%
Other values (45)	823	26.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2625	83.3%
Space Separator	365	11.6%
Other Punctuation	74	2.3%
Uppercase Letter	47	1.5%
Decimal Number	27	0.9%
Dash Punctuation	6	0.2%
Open Punctuation	3	0.1%
Close Punctuation	3	0.1%
Math Symbol	3	0.1%

Most frequent character per category

Value	Count	Frequency (%)
a	331	12.6%
i	271	10.3%
t	247	9.4%
n	216	8.2%
s	205	7.8%
e	203	7.7%
k	185	7.0%
l	161	6.1%
o	146	5.6%
u	118	4.5%
Other values (14)	542	20.6%

Value	Count	Frequency (%)
T	7	14.9%
P	7	14.9%
O	6	12.8%
E	6	12.8%
V	6	12.8%
S	4	8.5%
K	3	6.4%
I	2	4.3%
H	2	4.3%
R	1	2.1%
Other values (3)	3	6.4%

Value	Count	Frequency (%)
0	15	55.6%
1	3	11.1%
5	2	7.4%
2	2	7.4%
8	2	7.4%
6	2	7.4%
3	1	3.7%

Value	Count	Frequency (%)
.	38	51.4%
,	23	31.1%
/	5	6.8%
%	4	5.4%
"	2	2.7%
?	2	2.7%

Value	Count	Frequency (%)
	365	100.0%

Value	Count	Frequency (%)
(	3	100.0%

Value	Count	Frequency (%)
)	3	100.0%

Value	Count	Frequency (%)
+	3	100.0%

Value	Count	Frequency (%)
-	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2672	84.7%
Common	481	15.3%

Most frequent character per script

Value	Count	Frequency (%)
a	331	12.4%
i	271	10.1%
t	247	9.2%
n	216	8.1%
s	205	7.7%
e	203	7.6%
k	185	6.9%
l	161	6.0%
o	146	5.5%
u	118	4.4%
Other values (27)	589	22.0%

Value	Count	Frequency (%)
	365	75.9%
.	38	7.9%
,	23	4.8%
0	15	3.1%
-	6	1.2%
/	5	1.0%
%	4	0.8%
(	3	0.6%
)	3	0.6%
+	3	0.6%
Other values (8)	16	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3017	95.7%
None	136	4.3%

Most frequent character per block

Value	Count	Frequency (%)
	365	12.1%
a	331	11.0%
i	271	9.0%
t	247	8.2%
n	216	7.2%
s	205	6.8%
e	203	6.7%
k	185	6.1%
l	161	5.3%
o	146	4.8%
Other values (43)	687	22.8%

Value	Count	Frequency (%)
ä	112	82.4%
ö	24	17.6%

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.

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.

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.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Timestamp	Kaupunki	Ikä	Sukupuoli	Työkokemus	Työsuhteen luonne	Työaika	Rooli	Etä	Kuukausipalkka	Vuositulot	Kilpailukykyinen	Työpaikka	Vapaa sana
0	2021-02-15 11:57:08.316	PK-Seutu	31-35 v	NaN	10.0	Työntekijä / palkollinen	1.0	Arkkitehti	50/50	6500.0	83000.0	True	NaN	NaN
1	2021-02-15 11:57:19.676	Turku	31-35 v	mies	14.0	Työntekijä / palkollinen	1.0	full-stack	Etä	5000.0	62500.0	True	NaN	NaN
2	2021-02-15 11:58:03.592	PK-Seutu	26-30 v	mies	2.0	Työntekijä / palkollinen	1.0	Full-stack ohjelmistokehittäjä	Etä	2475.0	30000.0	False	NaN	NaN
3	2021-02-15 11:58:15.261	Tampere	31-35 v	mies	22.0	Yrittäjä	1.0	web-arkkitehti	Etä	4300.0	100000.0	True	NaN	NaN
4	2021-02-15 11:58:16.983	PK-Seutu	26-30 v	mies	2.0	Työntekijä / palkollinen	1.0	Ohjelmistokehittäjä	Etä	3000.0	37500.0	False	NaN	NaN
5	2021-02-15 11:58:49.454	PK-Seutu	41-45 v	mies	23.0	Työntekijä / palkollinen	1.0	Ohjelmistokehittäjä	NaN	8000.0	100000.0	True	NaN	NaN
6	2021-02-15 12:00:03.771	PK-Seutu	31-35 v	mies	10.0	Freelancer	1.0	Ohjelmistokehittäjä	Etä	6000.0	140000.0	True	NaN	NaN
7	2021-02-15 12:00:04.655	Tampere	31-35 v	NaN	10.0	Työntekijä / palkollinen	1.0	Ohjelmistokehittäjä	NaN	4250.0	54000.0	True	NaN	NaN
8	2021-02-15 12:01:00.769	Tampere	31-35 v	mies	6.0	Työntekijä / palkollinen	1.0	Lead developer	NaN	4000.0	50000.0	False	NaN	NaN
9	2021-02-15 12:02:03.577	Tallinna	31-35 v	mies	12.0	Freelancer	1.0	NaN	Etä	NaN	200000.0	True	Questrade	NaN

Last rows

	Timestamp	Kaupunki	Ikä	Sukupuoli	Työkokemus	Työsuhteen luonne	Työaika	Rooli	Etä	Kuukausipalkka	Vuositulot	Kilpailukykyinen	Työpaikka	Vapaa sana
418	2021-02-19 16:26:32.700	PK-Seutu	36-40 v	mies	16.0	Työntekijä / palkollinen	1.0	Mobile SW	Etä	8000.0	95000.0	True	Mavericks	NaN
419	2021-02-19 16:33:27.762	PK-Seutu	31-35 v	mies	11.0	Työntekijä / palkollinen	1.0	Full stack	50/50	7000.0	87500.0	True	Mavericks	NaN
420	2021-02-19 16:34:07.545	PK-Seutu	31-35 v	mies	12.0	Työntekijä / palkollinen	1.0	full-stack	Etä	8000.0	95000.0	True	Mavericks	NaN
421	2021-02-19 16:36:55.938	Tampere	41-45 v	mies	22.0	Työntekijä / palkollinen	0.8	ohjelmistokehittäjä (backend) / arkkitehti	Etä	4700.0	58750.0	False	NaN	NaN
422	2021-02-19 16:38:41.403	PK-Seutu	36-40 v	mies	2.0	Työntekijä / palkollinen	1.0	WordPress-kehittäjä	50/50	3000.0	37500.0	False	NaN	NaN
423	2021-02-19 16:39:14.831	Tampere	31-35 v	mies	5.0	Työntekijä / palkollinen	1.0	Data scientist	Etä	4300.0	53750.0	NaN	Wapice	NaN
424	2021-02-19 16:48:04.696	PK-Seutu	41-45 v	mies	15.0	Työntekijä / palkollinen	1.0	ohjelmistokehittäjä	50/50	NaN	100000.0	True	NaN	NaN
425	2021-02-19 16:54:30.691	Turku	36-40 v	mies	13.0	Työntekijä / palkollinen	1.0	Lead Software Engineer	NaN	5500.0	75000.0	True	NaN	NaN
426	2021-02-19 17:13:18.923	PK-Seutu	36-40 v	mies	15.0	Työntekijä / palkollinen	1.0	full-stack	Etä	6000.0	76000.0	True	NaN	NaN
427	2021-02-19 17:51:37.178	PK-Seutu	21-25 v	nainen	4.0	Työntekijä / palkollinen	1.0	Frontend ohjelmistokehittäjä	Etä	4000.0	55000.0	True	NaN	NaN

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Cramér's V (φc)

Missing values

Sample

First rows

Last rows