0
AD
AND
1
AE
ARE
2
AF
AFG
3
AG
ATG
4
AI
AIA
AND
Andorra
468
ARE
United Arab Emirates
82880
AFG
Afghanistan
647500
ATG
Antigua and Barbuda
443
AIA
Anguilla
102
ALB
Albania
28748
ARM
Armenia
29800
ANT
960
AGO
Angola
1246700
ATA
Antarctica
14000000
ABW
nan
AFE
920792331528
AFG
20116137326
AFW
784587603323
AGO
58375976293
ALB
14887629268
AND
nan
ARB
2447584445276
ARE
358868765175
ARG
389288056265
ABW
5049
46
AFG
49273
1971
AGO
16188
371
AIA
10
0
ALB
48530
1003
AND
7338
79
ARE
184949
617
ARG
1498160
40766
ARM
148682
2503
ATG
148
4
0
Andorra
468
1
United Arab Emirates
82880
2
Afghanistan
647500
3
Antigua and Barbuda
443
4
Anguilla
102
5
Albania
28748
6
Armenia
29800
7
960
8
Angola
1246700
9
Antarctica
14000000
0
United Arab Emirates
82880
1
Afghanistan
647500
2
Antigua and Barbuda
443
3
Albania
28748
4
Armenia
29800
Unable to deserialize response: 'Attribute' object has no attribute 'alias'
{
"head" : {
"vars" : [ "countryLabel", "population", "gdp", "area" ]
},
"results" : {
"bindings" : [ {
"countryLabel" : {
"xml:lang" : "en",
"type" : "literal",
"value" : "Finland"
},
"area" : {
"datatype" : "http://www.w3.org/2001/XMLSchema#decimal",
"type" : "literal",
"value" : "390905420000"
},
"population" : {
"datatype" : "http://www.w3.org/2001/XMLSchema#decimal",
"type" : "literal",
"value" : "5608218"
},
"gdp" : {
"datatype" : "http://www.w3.org/2001/XMLSchema#decimal",
"type" : "literal",
"value" : "251884887972.766"
}
}, {
"countryLabel" : {
"xml:lang" : "en",
"type" : "literal",
"value" : "Croatia"
},
"area" : {
"datatype" : "http://www.w3.org/2001/XMLSchema#decimal",
"type" : "literal",
"value" : "56594000000"
},
"population" : {
0
Finland
390905420000
1
Croatia
56594000000
2
Romania
238397000000
3
Sweden
528861060000
4
Malta
316000000
5
Republic of Ireland
69797000000
6
Estonia
45339000000
7
Austria
83878990000
8
Czech Republic
78866000000
9
Hungary
93036000000
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 26 entries, 0 to 25
Data columns (total 4 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 country 26 non-null object
1 area 26 non-null object
2 population 26 non-null object
3 gdp 26 non-null object
dtypes: object(4)
memory usage: 960.0+ bytes
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 26 entries, 0 to 25
Data columns (total 4 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 country 26 non-null object
1 area 26 non-null int64
2 population 26 non-null int64
3 gdp 26 non-null float64
dtypes: float64(1), int64(2), object(1)
memory usage: 960.0+ bytes
dwellings without basic facilities
1
-0.489839459
housing expenditure
-0.489839459
1
rooms per person
-0.5670415212
0.1081159094
household net adjusted disposable income
-0.5933208225
0.03818512651
household net financial wealth
-0.3882053112
0.07593112825
employment rate
-0.2873319494
-0.0871326234
job security
-0.1233920124
0.1731886451
long-term unemployment rate
-0.1660196279
0.2664336877
personal earnings
-0.6290899838
0.03175170034
quality of support network
-0.4244156075
0.06419716074
0
dwellings without basic facilities
dwellings without basic facilities
1
housing expenditure
dwellings without basic facilities
2
rooms per person
dwellings without basic facilities
3
household net adjusted disposable income
dwellings without basic facilities
4
household net financial wealth
dwellings without basic facilities
5
employment rate
dwellings without basic facilities
6
job security
dwellings without basic facilities
7
long-term unemployment rate
dwellings without basic facilities
8
personal earnings
dwellings without basic facilities
9
quality of support network
dwellings without basic facilities