pandas 在python中计算逻辑回归
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Calculate logistic regression in python
提问by nilashan
I tried to calculate logical regression. I have the data as csv file. it looks like
我试图计算逻辑回归。我将数据作为 csv 文件。看起来像
node_id,second_major,gender,major_index,year,dorm,high_school,student_fac
0,0,2,257,2007,111,2849,1
1,0,2,271,2005,0,51195,2
2,0,2,269,2007,0,21462,1
3,269,1,245,2008,111,2597,1
..........................
This is my coding.
这是我的编码。
import pandas as pd
import statsmodels.api as sm
import pylab as pl
import numpy as np
df = pd.read_csv("Reed98.csv")
print df.describe()
dummy_ranks = pd.get_dummies(df['second_major'], prefix='second_major')
cols_to_keep = ['second_major', 'dorm', 'high_school']
data = df[cols_to_keep].join(dummy_ranks.ix[:, 'year':])
train_cols = data.columns[1:]
# Index([gre, gpa, prestige_2, prestige_3, prestige_4], dtype=object)
logit = sm.Logit(data['second_major'], data[train_cols])
result = logit.fit()
print result.summary()
When I run the coding in python I got an error:
当我在 python 中运行编码时，出现错误：
Traceback (most recent call last):
File "D:\project\logisticregression.py", line 24, in <module>
result = logit.fit()
File "c:\python26\lib\site-packages\statsmodels-0.5.0-py2.6- win32.egg\statsmodels\discrete\discrete_model.py", line 282, in fit
disp=disp, callback=callback, **kwargs)
File "c:\python26\lib\site-packages\statsmodels-0.5.0-py2.6- win32.egg\statsmodels\discrete\discrete_model.py", line 233, in fit
disp=disp, callback=callback, **kwargs)
File "c:\python26\lib\site-packages\statsmodels-0.5.0-py2.6- win32.egg\statsmodels\base\model.py", line 291, in fit
hess=hess)
File "c:\python26\lib\site-packages\statsmodels-0.5.0-py2.6-win32.egg\statsmodels\base\model.py", line 341, in _fit_mle_newton
newparams = oldparams - np.dot(np.linalg.inv(H),
File "C:\Python26\Lib\site-packages\numpy\linalg\linalg.py", line 445, in inv
return wrap(solve(a, identity(a.shape[0], dtype=a.dtype)))
File "C:\Python26\Lib\site-packages\numpy\linalg\linalg.py", line 328, in solve
raise LinAlgError('Singular matrix')
LinAlgError: Singular matrix
How to rewrite the code?
如何重写代码？
回答by jseabold
There's nothing wrong with your code. My guess is that you have missing values in your data. Try a dropnaor use missing='drop'to Logit. You might also check that the right hand side is full rank np.linalg.matrix_rank(data[train_cols].values)
你的代码没有任何问题。我的猜测是您的数据中缺少值。尝试使用dropna或使用missing='drop'Logit。您还可以检查右侧是否为满秩np.linalg.matrix_rank(data[train_cols].values)
