python-3.x - ValueError:无法将字符串转换为 float ，Python

Question

我有一个数据框，我正在尝试在其上实现功能选择。 有 45 列类型，整数、浮点和对象。

但是我无法拟合任何特征选择模型，因为它抛出了错误。请帮帮我

数据框:

member_id   loan_amnt   funded_amnt funded_amnt_inv term        batch_enrolled   int_rate   grade
58189336    14350       14350       14350           36 months                    19.19      E
70011223    4800        4800        4800            36 months   BAT1586599       10.99      B

 sub_grade  emp_title   emp_length  home_ownership  annual_inc  verification_status pymnt_plan  desc                purpose title      zip_code addr_state   dti
 E3         clerk       9 years     OWN             28700       Source Verified     n           debt_consolidation  Debt consolidation 349xx    FL        33.88
 B4         HR          < 1 year    MORTGAGE        65000       Source Verified     n           home_improvement    Home improvement    209xx   MD      3.64

 last_week_pay  loan_status
 44th week          0
 9th week           1

代码:

 import numpy
 from pandas import read_csv
 from sklearn.decomposition import PCA
 # load data
 df = pd.read_csv("C:/Users/anagha/Documents/Python  Scripts/train_indessa.csv")
 array = df.values
 X = array[:,0:44]
 Y = array[:,44]
 # feature extraction
 pca = PCA(n_components=3)
 fit = pca.fit(X)

错误:

 Traceback (most recent call last):

 File "<ipython-input-8-20f3863fd66e>", line 2, in <module>
 fit = pca.fit(X)

 File "C:\Users\anagha\Anaconda3\lib\site-  packages\sklearn\decomposition\pca.py", line 301, in fit
self._fit(X)

File "C:\Users\anagha\Anaconda3\lib\site-packages\sklearn\decomposition\pca.py", line 333, in _fit
copy=self.copy)

File "C:\Users\anagha\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 382, in check_array
array = np.array(array, dtype=dtype, order=order, copy=copy)

ValueError: could not convert string to float: '44th week'

Answer 1

无法将“44th week”之类的字符串转换为浮点型。

字符串中Python实际上可以转换的唯一部分是44。为了做到这一点，我建议更改字符串以保留唯一的数字。之后，您将轻松应用 sklearn fit。以下代码应显示如何让 np 数组准备好转换为浮点型。

import numpy as np
import pandas as pd

data = np.array([['rows','col1','Col2','Col_withtext'],
            ['Row1',1,2,'44th week'],
            ['Row2',3,4,'the 30th week']])


df = pd.DataFrame(data=data[1:,1:],
              index=data[1:,0],
              columns=data[0,1:])

使用pandas替换删除文本

df['Col_withtext'].replace(to_replace="[a-zA-Z]", value='', 
regex=True, inplace=True)

df.values

##打印出来

 array([['1', '2', '44 '],
   ['3', '4', ' 30 ']], dtype=object)

让我知道进展如何!