varimax_spss_example

https://momalcy.tistory.com/38

해당 페이지에서 만든 함수를 활용한 예시 있입니다. !! 

In [1]:

from IPython.core.display import display, HTML
display(HTML("<style>.container{width:90%!important;}</style>"))

In [1]:

filepath = 'http://bestelon.com/pca/lipset.csv'
df = pd.read_csv(filepath)
x = df.iloc[:, 1:10]

In [2]:

import varimaxspss

In [3]:

result = varimaxspss.PcaVarimax(x)

In [4]:

result.pca()

  PC# Eigenvalue % of Varian Exp Cumulative %
0   1      2.384          26.486      26.486%
1   2      2.015          22.393      48.879%
2   3      1.341          14.898      63.777%
3   4      1.127          12.526      76.303%
4   5      0.168           1.865      78.169%
5   6      0.732           8.136      86.305%
6   7      0.320           3.551      89.855%
7   8      0.401           4.459      94.315%
8   9      0.512           5.685     100.000%

In [5]:

result.loadings(3)

      PC1    PC2    PC3
v1 -0.481  0.607  0.228
v2 -0.501  0.392  0.542
v3  0.388  0.667 -0.265
v4  0.416  0.725  0.171
v5 -0.525 -0.600  0.289
v6  0.691 -0.107  0.591
v7  0.711 -0.182  0.386
v8 -0.565  0.320  0.234
v9 -0.027  0.128 -0.509

Out[5]:

	0	1	2
0	1.55125	0.92806	-0.85854
1	-0.57445	0.23950	-0.46792
2	-0.66767	-1.45335	-0.29508
3	1.42814	0.00750	-0.73250
4	0.57579	-1.00634	1.29582
5	0.00663	0.80832	2.62408
6	-1.41590	-1.37589	-0.11324
7	-0.87942	-0.97312	-0.35451
8	0.69958	0.25283	-1.32997
9	-1.19380	-1.88593	-0.16561
10	-0.61448	-0.55620	1.24278
11	0.07490	0.42855	-0.43482
12	0.14665	1.71191	0.91821
13	-0.13053	-0.14639	-0.45345
14	-1.70857	-0.01774	-0.88892
15	0.84757	-2.44266	0.83012
16	0.59860	-0.30917	-0.61264
17	0.90505	-0.17584	-0.07480
18	1.29767	0.56920	-0.86673
19	0.23102	-0.81776	-0.44978
20	-0.82187	1.94456	-0.19179
21	-0.97595	-0.13727	0.16191
22	-1.21762	0.79154	0.72163
23	-1.16496	0.92156	-1.23495
24	0.84414	0.05782	0.70263
25	0.38439	1.19563	-0.10204
26	-0.42113	-0.01238	0.66721
27	0.37524	0.54643	3.11326
28	-0.71481	0.19422	-0.51565
29	1.53656	-0.56987	-0.40423
30	0.46822	-0.60372	-0.86801
31	1.98273	0.31136	-0.33260
32	-1.45302	1.57467	-0.52988

In [6]:

result.varimax()

Out[6]:

(array([[ 0.63692282,  0.52945063,  0.56036716],
        [-0.55715964,  0.81850672, -0.14007104],
        [-0.53282498, -0.22299952,  0.81631412]]),
 array([[-0.76583098,  0.19090031, -0.16829944],
        [-0.82578471, -0.0655237 ,  0.10674419],
        [ 0.01642114,  0.8107385 , -0.09294327],
        [-0.22983558,  0.77564922,  0.27115532],
        [-0.1543819 , -0.83345268,  0.02554101],
        [ 0.18452178,  0.14605752,  0.88487489],
        [ 0.3486223 ,  0.14131112,  0.73900317],
        [-0.66252588, -0.08906645, -0.17048799],
        [ 0.18284105,  0.20377209, -0.44813857]]))