In [1]:
import pandas as pd
In [2]:
df = pd.read_csv("data/eu_revolving_loans.csv")
In [3]:
df.shape
Out[3]:
(198, 1)
In [4]:
df.head(7)
Out[4]:
Data Source in SDW: null
NaN
MIR.M.AT.B.A2Z.A.R.A.2250.EUR.N
MIR.M.BE.B.A2Z.A.R.A.2250.EUR.N
MIR.M.CY.B.A2Z.A.R.A.2250.EUR.N
MIR.M.DE.B.A2Z.A.R.A.2250.EUR.N
MIR.M.EE.B.A2Z.A.R.A.2250.EUR.N
MIR.M.ES.B.A2Z.A.R.A.2250.EUR.N
MIR.M.FI.B.A2Z.A.R.A.2250.EUR.N
MIR.M.FR.B.A2Z.A.R.A.2250.EUR.N
MIR.M.GR.B.A2Z.A.R.A.2250.EUR.N
MIR.M.IE.B.A2Z.A.R.A.2250.EUR.N
MIR.M.IT.B.A2Z.A.R.A.2250.EUR.N
MIR.M.LT.B.A2Z.A.R.A.2250.EUR.N
MIR.M.LU.B.A2Z.A.R.A.2250.EUR.N
MIR.M.LV.B.A2Z.A.R.A.2250.EUR.N
MIR.M.MT.B.A2Z.A.R.A.2250.EUR.N
MIR.M.NL.B.A2Z.A.R.A.2250.EUR.N
MIR.M.PT.B.A2Z.A.R.A.2250.EUR.N
MIR.M.SI.B.A2Z.A.R.A.2250.EUR.N
MIR.M.SK.B.A2Z.A.R.A.2250.EUR.N
MIR.M.U2.B.A2Z.A.R.A.2250.EUR.N
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Collection:
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
Average of observations through period (A)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
2016Feb
4.20
8.09
6.13
8.85
16.38
11.03
6.41
6.00
8.18
10.40
6.07
9.60
7.24
21.58
6.79
5.83
15.28
6.80
13.86
7.36
2016Jan
4.17
8.05
6.13
8.83
16.41
10.85
6.44
6.10
8.19
9.91
6.07
9.58
7.10
21.51
6.82
5.81
15.41
6.79
13.97
7.35
2015Dec
3.99
8.21
6.16
8.69
16.32
10.49
6.40
5.86
8.22
10.37
5.91
9.45
6.96
21.59
6.84
5.88
15.16
6.65
13.72
7.23
In [5]:
df = df[2:]
In [6]:
df.head(7)
Out[6]:
Data Source in SDW: null
Collection:
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
Average of observations through period (A)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
2016Feb
4.20
8.09
6.13
8.85
16.38
11.03
6.41
6.00
8.18
10.40
6.07
9.60
7.24
21.58
6.79
5.83
15.28
6.80
13.86
7.36
2016Jan
4.17
8.05
6.13
8.83
16.41
10.85
6.44
6.10
8.19
9.91
6.07
9.58
7.10
21.51
6.82
5.81
15.41
6.79
13.97
7.35
2015Dec
3.99
8.21
6.16
8.69
16.32
10.49
6.40
5.86
8.22
10.37
5.91
9.45
6.96
21.59
6.84
5.88
15.16
6.65
13.72
7.23
2015Nov
4.09
8.20
6.15
8.82
16.37
10.73
6.49
6.18
8.30
9.11
6.12
9.53
6.88
21.67
6.78
5.97
15.32
6.79
14.10
7.37
2015Oct
4.10
8.40
6.16
8.89
16.42
10.86
6.52
6.15
8.34
9.29
6.11
9.40
7.08
21.74
6.78
5.93
15.55
6.74
14.12
7.41
In [42]:
df = pd.read_csv("data/eu_revolving_loans.csv",
header=[1,2,3], index_col=0, skiprows=1, na_values=['-'])
In [43]:
df.head(7)
Out[43]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Collection:
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
Average of observations through period (A)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
2016Feb
4.20
8.09
6.13
8.85
16.38
11.03
6.41
6.00
8.18
10.40
6.07
9.60
7.24
21.58
6.79
5.83
15.28
6.80
13.86
7.36
2016Jan
4.17
8.05
6.13
8.83
16.41
10.85
6.44
6.10
8.19
9.91
6.07
9.58
7.10
21.51
6.82
5.81
15.41
6.79
13.97
7.35
2015Dec
3.99
8.21
6.16
8.69
16.32
10.49
6.40
5.86
8.22
10.37
5.91
9.45
6.96
21.59
6.84
5.88
15.16
6.65
13.72
7.23
2015Nov
4.09
8.20
6.15
8.82
16.37
10.73
6.49
6.18
8.30
9.11
6.12
9.53
6.88
21.67
6.78
5.97
15.32
6.79
14.10
7.37
2015Oct
4.10
8.40
6.16
8.89
16.42
10.86
6.52
6.15
8.34
9.29
6.11
9.40
7.08
21.74
6.78
5.93
15.55
6.74
14.12
7.41
2015Sep
4.32
8.58
6.17
8.95
16.44
10.87
6.52
6.41
8.53
9.38
6.14
9.33
7.07
21.75
6.79
5.97
15.51
6.81
14.21
7.53
2015Aug
4.28
8.27
6.36
8.91
16.40
10.81
6.47
6.39
8.59
8.91
6.12
9.39
7.13
21.80
6.60
6.05
15.21
6.79
14.26
7.49
In [44]:
df.tail(5)
Out[44]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Collection:
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
Average of observations through period (A)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
2000May
9.06
11.55
NaN
10.25
NaN
13.02
10.83
11.03
19.35
13.08
9.36
NaN
NaN
NaN
NaN
8.93
9.4
NaN
NaN
10.44
2000Apr
8.99
10.82
NaN
10.21
NaN
13.01
10.54
11.03
20.46
13.08
9.18
NaN
NaN
NaN
NaN
8.44
9.2
NaN
NaN
10.33
2000Mar
8.90
10.48
NaN
10.02
NaN
12.96
10.49
10.92
20.87
12.84
9.05
NaN
NaN
NaN
NaN
8.44
9.1
NaN
NaN
10.16
2000Feb
8.93
10.14
NaN
9.96
NaN
12.95
10.35
10.91
21.22
12.53
8.97
NaN
NaN
NaN
NaN
7.94
9.1
NaN
NaN
10.09
2000Jan
8.83
10.01
NaN
9.81
NaN
12.96
10.28
10.91
21.62
12.53
8.88
NaN
NaN
NaN
NaN
7.44
9.0
NaN
NaN
9.98
In [45]:
df.shape
Out[45]:
(194, 20)
In [46]:
df.describe()
Out[46]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Collection:
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
End of period (E)
Average of observations through period (A)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
count
194.000000
142.000000
159.000000
194.00000
156.000000
194.000000
194.000000
194.000000
194.000000
194.000000
194.000000
132.000000
158.000000
146.000000
104.000000
194.000000
194.000000
125.000000
98.000000
194.000000
mean
6.660000
10.143028
7.226038
10.46799
11.182051
11.848763
8.899742
9.957835
13.086443
11.723763
8.090722
6.043636
5.992025
10.660274
6.826538
6.991856
11.905464
7.878720
13.237449
9.497526
std
1.555478
1.316609
0.493942
0.78234
4.477234
1.453811
1.853112
1.749429
2.871678
2.178378
1.094160
1.865785
1.120911
5.262896
0.383246
1.227009
2.331037
1.876324
2.099137
1.118740
min
3.990000
7.670000
6.130000
8.69000
5.940000
8.070000
6.400000
5.860000
8.180000
7.340000
5.910000
3.480000
3.100000
4.450000
6.000000
5.620000
7.900000
4.180000
5.830000
7.230000
25%
5.317500
9.150000
6.840000
10.12750
7.182500
10.730000
6.880000
8.745000
10.982500
9.992500
7.150000
4.137500
5.320000
7.697500
6.707500
6.282500
10.127500
6.950000
13.667500
8.622500
50%
6.855000
10.160000
7.250000
10.40000
8.370000
12.425000
9.150000
10.650000
13.795000
12.840000
8.395000
6.410000
5.815000
8.740000
6.790000
6.615000
11.430000
7.500000
13.860000
9.750000
75%
7.920000
11.220000
7.685000
10.96000
16.372500
13.020000
10.332500
11.227500
14.507500
13.217500
8.902500
7.207500
7.015000
10.070000
6.852500
7.327500
13.272500
8.740000
14.170000
10.447500
max
9.120000
12.630000
8.020000
12.01000
16.900000
14.090000
12.460000
12.290000
21.620000
14.410000
10.230000
9.640000
8.680000
21.920000
8.010000
10.920000
16.040000
11.130000
14.700000
11.390000
In [47]:
%pylab inline
df.plot(legend=False)
Populating the interactive namespace from numpy and matplotlib
Out[47]:
<matplotlib.axes._subplots.AxesSubplot at 0x110823410>
In [48]:
df = df.iloc[::-1]
df.plot(legend=False, title="EU Countries Revolving Loan Trend from 2000 - 2016")
Out[48]:
<matplotlib.axes._subplots.AxesSubplot at 0x1108386d0>
In [49]:
df.columns = df.columns.droplevel(1)
df.head()
Out[49]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Period\Unit:
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
[Percent per annum ]
2000Jan
8.83
10.01
NaN
9.81
NaN
12.96
10.28
10.91
21.62
12.53
8.88
NaN
NaN
NaN
NaN
7.44
9.0
NaN
NaN
9.98
2000Feb
8.93
10.14
NaN
9.96
NaN
12.95
10.35
10.91
21.22
12.53
8.97
NaN
NaN
NaN
NaN
7.94
9.1
NaN
NaN
10.09
2000Mar
8.90
10.48
NaN
10.02
NaN
12.96
10.49
10.92
20.87
12.84
9.05
NaN
NaN
NaN
NaN
8.44
9.1
NaN
NaN
10.16
2000Apr
8.99
10.82
NaN
10.21
NaN
13.01
10.54
11.03
20.46
13.08
9.18
NaN
NaN
NaN
NaN
8.44
9.2
NaN
NaN
10.33
2000May
9.06
11.55
NaN
10.25
NaN
13.02
10.83
11.03
19.35
13.08
9.36
NaN
NaN
NaN
NaN
8.93
9.4
NaN
NaN
10.44
In [50]:
df.columns = df.columns.droplevel(1)
df.head()
Out[50]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
2000Jan
8.83
10.01
NaN
9.81
NaN
12.96
10.28
10.91
21.62
12.53
8.88
NaN
NaN
NaN
NaN
7.44
9.0
NaN
NaN
9.98
2000Feb
8.93
10.14
NaN
9.96
NaN
12.95
10.35
10.91
21.22
12.53
8.97
NaN
NaN
NaN
NaN
7.94
9.1
NaN
NaN
10.09
2000Mar
8.90
10.48
NaN
10.02
NaN
12.96
10.49
10.92
20.87
12.84
9.05
NaN
NaN
NaN
NaN
8.44
9.1
NaN
NaN
10.16
2000Apr
8.99
10.82
NaN
10.21
NaN
13.01
10.54
11.03
20.46
13.08
9.18
NaN
NaN
NaN
NaN
8.44
9.2
NaN
NaN
10.33
2000May
9.06
11.55
NaN
10.25
NaN
13.02
10.83
11.03
19.35
13.08
9.36
NaN
NaN
NaN
NaN
8.93
9.4
NaN
NaN
10.44
In [52]:
# default to Pearson Correlation:
df.corr()
Out[52]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Austria
1.000000
0.933296
-0.158893
0.767335
-0.779483
0.812410
0.903886
0.935643
0.936635
0.878040
0.928940
0.346137
-0.643426
-0.589684
0.349041
0.728811
-0.851445
0.506641
-0.699131
0.971953
Belgium
0.933296
1.000000
0.091032
0.840900
-0.816134
0.767005
0.878510
0.934225
0.863154
0.885750
0.904793
0.196706
-0.724829
-0.668038
0.275887
0.839943
-0.798902
0.797719
-0.593504
0.963826
Cyprus
-0.158893
0.091032
1.000000
-0.026293
0.210236
-0.460870
-0.285169
-0.022965
-0.057134
-0.222016
-0.042734
-0.741061
0.084047
-0.364128
-0.104222
0.069418
0.094653
0.108693
0.193465
-0.099245
Germany
0.767335
0.840900
-0.026293
1.000000
-0.713350
0.662287
0.878585
0.848756
0.693189
0.808686
0.737979
0.211564
-0.629488
-0.574756
0.370332
0.514504
-0.612874
0.603209
-0.677940
0.871138
Estonia
-0.779483
-0.816134
0.210236
-0.713350
1.000000
-0.675819
-0.762952
-0.855953
-0.857996
-0.864777
-0.617540
-0.414964
0.782377
0.547214
-0.066872
-0.381090
0.831245
-0.286466
0.396512
-0.800245
Spain
0.812410
0.767005
-0.460870
0.662287
-0.675819
1.000000
0.874300
0.735147
0.731535
0.762828
0.747915
0.577643
-0.635261
-0.196498
0.290660
0.484302
-0.615433
0.438563
-0.682231
0.807865
Finland
0.903886
0.878510
-0.285169
0.878585
-0.762952
0.874300
1.000000
0.858658
0.831995
0.868378
0.881585
0.443685
-0.599308
-0.383452
0.479796
0.667566
-0.686999
0.530942
-0.850394
0.940608
France
0.935643
0.934225
-0.022965
0.848756
-0.855953
0.735147
0.858658
1.000000
0.890779
0.916316
0.842324
0.212757
-0.737581
-0.713534
0.156894
0.597432
-0.892937
0.434010
-0.460562
0.959292
Greece (GR)
0.936635
0.863154
-0.057134
0.693189
-0.857996
0.731535
0.831995
0.890779
1.000000
0.854965
0.816312
0.307985
-0.817328
-0.688367
0.162721
0.689301
-0.832680
0.500846
-0.490263
0.893096
Ireland
0.878040
0.885750
-0.222016
0.808686
-0.864777
0.762828
0.868378
0.916316
0.854965
1.000000
0.764243
0.499445
-0.760592
-0.605204
0.206695
0.548385
-0.868070
0.387349
-0.489360
0.898830
Italy
0.928940
0.904793
-0.042734
0.737979
-0.617540
0.747915
0.881585
0.842324
0.816312
0.764243
1.000000
0.126948
-0.406044
-0.532614
0.569316
0.808319
-0.712177
0.370174
-0.803785
0.941492
Lithuania
0.346137
0.196706
-0.741061
0.211564
-0.414964
0.577643
0.443685
0.212757
0.307985
0.499445
0.126948
1.000000
-0.305057
0.207314
0.121146
0.102826
-0.301238
0.159917
-0.263597
0.283624
Luxembourg
-0.643426
-0.724829
0.084047
-0.629488
0.782377
-0.635261
-0.599308
-0.737581
-0.817328
-0.760592
-0.406044
-0.305057
1.000000
0.591442
0.140274
-0.203444
0.646547
-0.416776
0.206214
-0.663332
Latvia
-0.589684
-0.668038
-0.364128
-0.574756
0.547214
-0.196498
-0.383452
-0.713534
-0.688367
-0.605204
-0.532614
0.207314
0.591442
1.000000
-0.014712
-0.336862
0.689702
-0.127818
0.062097
-0.613611
Malta
0.349041
0.275887
-0.104222
0.370332
-0.066872
0.290660
0.479796
0.156894
0.162721
0.206695
0.569316
0.121146
0.140274
-0.014712
1.000000
0.598059
-0.003573
0.348854
-0.829734
0.365031
Netherlands
0.728811
0.839943
0.069418
0.514504
-0.381090
0.484302
0.667566
0.597432
0.689301
0.548385
0.808319
0.102826
-0.203444
-0.336862
0.598059
1.000000
-0.447009
0.578807
-0.773962
0.740492
Portugal
-0.851445
-0.798902
0.094653
-0.612874
0.831245
-0.615433
-0.686999
-0.892937
-0.832680
-0.868070
-0.712177
-0.301238
0.646547
0.689702
-0.003573
-0.447009
1.000000
-0.158221
0.219427
-0.811654
Slovenia
0.506641
0.797719
0.108693
0.603209
-0.286466
0.438563
0.530942
0.434010
0.500846
0.387349
0.370174
0.159917
-0.416776
-0.127818
0.348854
0.578807
-0.158221
1.000000
-0.737147
0.507534
Slovakia
-0.699131
-0.593504
0.193465
-0.677940
0.396512
-0.682231
-0.850394
-0.460562
-0.490263
-0.489360
-0.803785
-0.263597
0.206214
0.062097
-0.829734
-0.773962
0.219427
-0.737147
1.000000
-0.694345
Euro area (changing composition)
0.971953
0.963826
-0.099245
0.871138
-0.800245
0.807865
0.940608
0.959292
0.893096
0.898830
0.941492
0.283624
-0.663332
-0.613611
0.365031
0.740492
-0.811654
0.507534
-0.694345
1.000000
In [53]:
eu_corr = df.corr()
In [56]:
eu_corr[(eu_corr.abs() > 0.5) & (eu_corr < 1)]
Out[56]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Austria
NaN
0.933296
NaN
0.767335
-0.779483
0.812410
0.903886
0.935643
0.936635
0.878040
0.928940
NaN
-0.643426
-0.589684
NaN
0.728811
-0.851445
0.506641
-0.699131
0.971953
Belgium
0.933296
NaN
NaN
0.840900
-0.816134
0.767005
0.878510
0.934225
0.863154
0.885750
0.904793
NaN
-0.724829
-0.668038
NaN
0.839943
-0.798902
0.797719
-0.593504
0.963826
Cyprus
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
-0.741061
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Germany
0.767335
0.840900
NaN
NaN
-0.713350
0.662287
0.878585
0.848756
0.693189
0.808686
0.737979
NaN
-0.629488
-0.574756
NaN
0.514504
-0.612874
0.603209
-0.677940
0.871138
Estonia
-0.779483
-0.816134
NaN
-0.713350
NaN
-0.675819
-0.762952
-0.855953
-0.857996
-0.864777
-0.617540
NaN
0.782377
0.547214
NaN
NaN
0.831245
NaN
NaN
-0.800245
Spain
0.812410
0.767005
NaN
0.662287
-0.675819
NaN
0.874300
0.735147
0.731535
0.762828
0.747915
0.577643
-0.635261
NaN
NaN
NaN
-0.615433
NaN
-0.682231
0.807865
Finland
0.903886
0.878510
NaN
0.878585
-0.762952
0.874300
NaN
0.858658
0.831995
0.868378
0.881585
NaN
-0.599308
NaN
NaN
0.667566
-0.686999
0.530942
-0.850394
0.940608
France
0.935643
0.934225
NaN
0.848756
-0.855953
0.735147
0.858658
NaN
0.890779
0.916316
0.842324
NaN
-0.737581
-0.713534
NaN
0.597432
-0.892937
NaN
NaN
0.959292
Greece (GR)
0.936635
0.863154
NaN
0.693189
-0.857996
0.731535
0.831995
0.890779
NaN
0.854965
0.816312
NaN
-0.817328
-0.688367
NaN
0.689301
-0.832680
0.500846
NaN
0.893096
Ireland
0.878040
0.885750
NaN
0.808686
-0.864777
0.762828
0.868378
0.916316
0.854965
NaN
0.764243
NaN
-0.760592
-0.605204
NaN
0.548385
-0.868070
NaN
NaN
0.898830
Italy
0.928940
0.904793
NaN
0.737979
-0.617540
0.747915
0.881585
0.842324
0.816312
0.764243
NaN
NaN
NaN
-0.532614
0.569316
0.808319
-0.712177
NaN
-0.803785
0.941492
Lithuania
NaN
NaN
-0.741061
NaN
NaN
0.577643
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
Luxembourg
-0.643426
-0.724829
NaN
-0.629488
0.782377
-0.635261
-0.599308
-0.737581
-0.817328
-0.760592
NaN
NaN
NaN
0.591442
NaN
NaN
0.646547
NaN
NaN
-0.663332
Latvia
-0.589684
-0.668038
NaN
-0.574756
0.547214
NaN
NaN
-0.713534
-0.688367
-0.605204
-0.532614
NaN
0.591442
NaN
NaN
NaN
0.689702
NaN
NaN
-0.613611
Malta
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.569316
NaN
NaN
NaN
NaN
0.598059
NaN
NaN
-0.829734
NaN
Netherlands
0.728811
0.839943
NaN
0.514504
NaN
NaN
0.667566
0.597432
0.689301
0.548385
0.808319
NaN
NaN
NaN
0.598059
NaN
NaN
0.578807
-0.773962
0.740492
Portugal
-0.851445
-0.798902
NaN
-0.612874
0.831245
-0.615433
-0.686999
-0.892937
-0.832680
-0.868070
-0.712177
NaN
0.646547
0.689702
NaN
NaN
NaN
NaN
NaN
-0.811654
Slovenia
0.506641
0.797719
NaN
0.603209
NaN
NaN
0.530942
NaN
0.500846
NaN
NaN
NaN
NaN
NaN
NaN
0.578807
NaN
NaN
-0.737147
0.507534
Slovakia
-0.699131
-0.593504
NaN
-0.677940
NaN
-0.682231
-0.850394
NaN
NaN
NaN
-0.803785
NaN
NaN
NaN
-0.829734
-0.773962
NaN
-0.737147
NaN
-0.694345
Euro area (changing composition)
0.971953
0.963826
NaN
0.871138
-0.800245
0.807865
0.940608
0.959292
0.893096
0.898830
0.941492
NaN
-0.663332
-0.613611
NaN
0.740492
-0.811654
0.507534
-0.694345
NaN
In [58]:
eu_corr[(eu_corr.abs() > 0.5) & (eu_corr < 1)].dropna(thresh=4)
Out[58]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Austria
NaN
0.933296
NaN
0.767335
-0.779483
0.812410
0.903886
0.935643
0.936635
0.878040
0.928940
NaN
-0.643426
-0.589684
NaN
0.728811
-0.851445
0.506641
-0.699131
0.971953
Belgium
0.933296
NaN
NaN
0.840900
-0.816134
0.767005
0.878510
0.934225
0.863154
0.885750
0.904793
NaN
-0.724829
-0.668038
NaN
0.839943
-0.798902
0.797719
-0.593504
0.963826
Germany
0.767335
0.840900
NaN
NaN
-0.713350
0.662287
0.878585
0.848756
0.693189
0.808686
0.737979
NaN
-0.629488
-0.574756
NaN
0.514504
-0.612874
0.603209
-0.677940
0.871138
Estonia
-0.779483
-0.816134
NaN
-0.713350
NaN
-0.675819
-0.762952
-0.855953
-0.857996
-0.864777
-0.617540
NaN
0.782377
0.547214
NaN
NaN
0.831245
NaN
NaN
-0.800245
Spain
0.812410
0.767005
NaN
0.662287
-0.675819
NaN
0.874300
0.735147
0.731535
0.762828
0.747915
0.577643
-0.635261
NaN
NaN
NaN
-0.615433
NaN
-0.682231
0.807865
Finland
0.903886
0.878510
NaN
0.878585
-0.762952
0.874300
NaN
0.858658
0.831995
0.868378
0.881585
NaN
-0.599308
NaN
NaN
0.667566
-0.686999
0.530942
-0.850394
0.940608
France
0.935643
0.934225
NaN
0.848756
-0.855953
0.735147
0.858658
NaN
0.890779
0.916316
0.842324
NaN
-0.737581
-0.713534
NaN
0.597432
-0.892937
NaN
NaN
0.959292
Greece (GR)
0.936635
0.863154
NaN
0.693189
-0.857996
0.731535
0.831995
0.890779
NaN
0.854965
0.816312
NaN
-0.817328
-0.688367
NaN
0.689301
-0.832680
0.500846
NaN
0.893096
Ireland
0.878040
0.885750
NaN
0.808686
-0.864777
0.762828
0.868378
0.916316
0.854965
NaN
0.764243
NaN
-0.760592
-0.605204
NaN
0.548385
-0.868070
NaN
NaN
0.898830
Italy
0.928940
0.904793
NaN
0.737979
-0.617540
0.747915
0.881585
0.842324
0.816312
0.764243
NaN
NaN
NaN
-0.532614
0.569316
0.808319
-0.712177
NaN
-0.803785
0.941492
Luxembourg
-0.643426
-0.724829
NaN
-0.629488
0.782377
-0.635261
-0.599308
-0.737581
-0.817328
-0.760592
NaN
NaN
NaN
0.591442
NaN
NaN
0.646547
NaN
NaN
-0.663332
Latvia
-0.589684
-0.668038
NaN
-0.574756
0.547214
NaN
NaN
-0.713534
-0.688367
-0.605204
-0.532614
NaN
0.591442
NaN
NaN
NaN
0.689702
NaN
NaN
-0.613611
Netherlands
0.728811
0.839943
NaN
0.514504
NaN
NaN
0.667566
0.597432
0.689301
0.548385
0.808319
NaN
NaN
NaN
0.598059
NaN
NaN
0.578807
-0.773962
0.740492
Portugal
-0.851445
-0.798902
NaN
-0.612874
0.831245
-0.615433
-0.686999
-0.892937
-0.832680
-0.868070
-0.712177
NaN
0.646547
0.689702
NaN
NaN
NaN
NaN
NaN
-0.811654
Slovenia
0.506641
0.797719
NaN
0.603209
NaN
NaN
0.530942
NaN
0.500846
NaN
NaN
NaN
NaN
NaN
NaN
0.578807
NaN
NaN
-0.737147
0.507534
Slovakia
-0.699131
-0.593504
NaN
-0.677940
NaN
-0.682231
-0.850394
NaN
NaN
NaN
-0.803785
NaN
NaN
NaN
-0.829734
-0.773962
NaN
-0.737147
NaN
-0.694345
Euro area (changing composition)
0.971953
0.963826
NaN
0.871138
-0.800245
0.807865
0.940608
0.959292
0.893096
0.898830
0.941492
NaN
-0.663332
-0.613611
NaN
0.740492
-0.811654
0.507534
-0.694345
NaN
In [59]:
df.cov()
Out[59]:
Austria
Belgium
Cyprus
Germany
Estonia
Spain
Finland
France
Greece (GR)
Ireland
Italy
Lithuania
Luxembourg
Latvia
Malta
Netherlands
Portugal
Slovenia
Slovakia
Euro area (changing composition)
Austria
2.419511
2.117914
-0.103836
0.933779
-4.537638
1.837161
2.605430
2.546069
4.183789
2.975167
1.581002
0.792435
-0.948666
-3.854001
0.163653
1.390998
-3.087235
1.181801
-1.689152
1.691368
Belgium
2.117914
1.733458
0.049440
1.002935
-3.956379
1.473269
2.424479
2.411744
3.744800
2.797553
1.460503
0.416091
-0.995070
-4.010365
0.115879
1.547613
-2.601993
1.373334
-1.336453
1.610461
Cyprus
-0.103836
0.049440
0.243979
-0.010626
0.469122
-0.334862
-0.253941
-0.019056
-0.063483
-0.240351
-0.019208
-0.700008
0.046658
-0.971472
-0.020438
0.015821
0.102699
0.104461
0.206691
-0.048723
Germany
0.933779
1.002935
-0.010626
0.612056
-2.631286
0.753268
1.273740
1.161649
1.557338
1.378188
0.631714
0.352959
-0.578313
-2.571430
0.132814
0.493892
-1.117675
1.040043
-1.251074
0.762450
Estonia
-4.537638
-3.956379
0.469122
-2.631286
20.045624
-4.452756
-6.187331
-6.400211
-8.625996
-8.536770
-2.488495
-3.633100
3.950162
13.288814
-0.114851
-0.789547
8.094346
-2.534875
3.665488
-3.540396
Spain
1.837161
1.473269
-0.334862
0.753268
-4.452756
2.113566
2.355431
1.869728
3.054069
2.415838
1.189709
1.640827
-1.047819
-1.521189
0.171538
0.863916
-2.085632
1.265243
-2.108673
1.313941
Finland
2.605430
2.424479
-0.253941
1.273740
-6.187331
2.355431
3.434025
2.783674
4.427495
3.505449
1.787502
1.602446
-1.212779
-3.745060
0.356414
1.517902
-2.967614
1.972751
-3.155825
1.950022
France
2.546069
2.411744
-0.019056
1.161649
-6.400211
1.869728
2.783674
3.060503
4.475095
3.492007
1.612340
0.672821
-1.386407
-6.245393
0.102598
1.282427
-3.641384
1.402943
-1.614758
1.877485
Greece (GR)
4.183789
3.744800
-0.063483
1.557338
-8.625996
3.054069
4.427495
4.475095
8.246534
5.348316
2.564915
1.311169
-2.060430
-8.129378
0.147866
2.428802
-5.573948
2.176516
-2.401811
2.869212
Ireland
2.975167
2.797553
-0.240351
1.378188
-8.536770
2.415838
3.505449
3.492007
5.348316
4.745330
1.821568
2.116274
-1.871640
-7.158215
0.175517
1.465772
-4.407956
1.656375
-2.200670
2.190482
Italy
1.581002
1.460503
-0.019208
0.631714
-2.488495
1.189709
1.787502
1.612340
2.564915
1.821568
1.197186
0.209933
-0.412498
-2.498610
0.185392
1.085204
-1.816427
0.618364
-1.334718
1.152461
Lithuania
0.792435
0.416091
-0.700008
0.352959
-3.633100
1.640827
1.602446
0.672821
1.311169
2.116274
0.209933
3.481155
-0.689817
2.104141
0.093534
0.094881
-1.172571
0.568251
-1.134336
0.535213
Luxembourg
-0.948666
-0.995070
0.046658
-0.578313
3.950162
-1.047819
-1.212779
-1.386407
-2.060430
-1.871640
-0.412498
-0.689817
1.256440
3.624038
0.070076
-0.105255
1.577011
-0.966070
0.571645
-0.737019
Latvia
-3.854001
-4.010365
-0.971472
-2.571430
13.288814
-1.521189
-3.745060
-6.245393
-8.129378
-7.158215
-2.498610
2.104141
3.624038
27.698076
-0.032079
-0.843912
7.800204
-1.316909
0.760400
-3.192018
Malta
0.163653
0.115879
-0.020438
0.132814
-0.114851
0.171538
0.356414
0.102598
0.147866
0.175517
0.185392
0.093534
0.070076
-0.032079
0.146877
0.122156
-0.002563
0.194226
-0.632835
0.141194
Netherlands
1.390998
1.547613
0.015821
0.493892
-0.789547
0.863916
1.517902
1.282427
2.428802
1.465772
1.085204
0.094881
-0.105255
-0.843912
0.122156
1.505550
-1.278538
0.551202
-0.821616
1.016476
Portugal
-3.087235
-2.601993
0.102699
-1.117675
8.094346
-2.085632
-2.967614
-3.641384
-5.573948
-4.407956
-1.816427
-1.172571
1.577011
7.800204
-0.002563
-1.278538
5.433735
-0.597043
0.859804
-2.116652
Slovenia
1.181801
1.373334
0.104461
1.040043
-2.534875
1.265243
1.972751
1.402943
2.176516
1.656375
0.618364
0.568251
-0.966070
-1.316909
0.194226
0.551202
-0.597043
3.520594
-2.073396
0.980974
Slovakia
-1.689152
-1.336453
0.206691
-1.251074
3.665488
-2.108673
-3.155825
-1.614758
-2.401811
-2.200670
-1.334718
-1.134336
0.571645
0.760400
-0.632835
-0.821616
0.859804
-2.073396
4.406376
-1.382989
Euro area (changing composition)
1.691368
1.610461
-0.048723
0.762450
-3.540396
1.313941
1.950022
1.877485
2.869212
2.190482
1.152461
0.535213
-0.737019
-3.192018
0.141194
1.016476
-2.116652
0.980974
-1.382989
1.251578
In [60]:
df.cov().min()
Out[60]:
Austria -4.537638
Belgium -4.010365
Cyprus -0.971472
Germany -2.631286
Estonia -8.625996
Spain -4.452756
Finland -6.187331
France -6.400211
Greece (GR) -8.625996
Ireland -8.536770
Italy -2.498610
Lithuania -3.633100
Luxembourg -2.060430
Latvia -8.129378
Malta -0.632835
Netherlands -1.278538
Portugal -5.573948
Slovenia -2.534875
Slovakia -3.155825
Euro area (changing composition) -3.540396
dtype: float64
In [62]:
df.cov().max()
Out[62]:
Austria 4.183789
Belgium 3.744800
Cyprus 0.469122
Germany 1.557338
Estonia 20.045624
Spain 3.054069
Finland 4.427495
France 4.475095
Greece (GR) 8.246534
Ireland 5.348316
Italy 2.564915
Lithuania 3.481155
Luxembourg 3.950162
Latvia 27.698076
Malta 0.356414
Netherlands 2.428802
Portugal 8.094346
Slovenia 3.520594
Slovakia 4.406376
Euro area (changing composition) 2.869212
dtype: float64
In [63]:
%pylab inline
df[['Latvia', 'Estonia', 'Greece (GR)', 'Ireland']].plot()
Populating the interactive namespace from numpy and matplotlib
Out[63]:
<matplotlib.axes._subplots.AxesSubplot at 0x110819d50>
In [65]:
df.index
Out[65]:
Index([u'2000Jan', u'2000Feb', u'2000Mar', u'2000Apr', u'2000May', u'2000Jun',
u'2000Jul', u'2000Aug', u'2000Sep', u'2000Oct',
...
u'2015May', u'2015Jun', u'2015Jul', u'2015Aug', u'2015Sep', u'2015Oct',
u'2015Nov', u'2015Dec', u'2016Jan', u'2016Feb'],
dtype='object', length=194)
In [67]:
df.index = df.index.map(lambda x: datetime.datetime.strptime(x, '%Y%b').date())
In [68]:
df[['Latvia', 'Estonia', 'Greece (GR)', 'Ireland']].plot()
Out[68]:
<matplotlib.axes._subplots.AxesSubplot at 0x110fb4610>
In [ ]:
Content source: philmui/datascience2016fall
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