将数值数组转换为稀疏时出错

我正在研究一个庞大的数据集，我有将数值数组转换为稀疏的问题 .

import pandas as pd
l = pd.read_csv('merge_from_ofoct.csv')
l.drop('Unnamed: 12', axis=1, inplace=True)
l.drop('CRS_ARR_TIME', axis=1, inplace=True)
l.drop('CRS_DEP_TIME', axis=1, inplace=True)
l = l[(l.T != 0).any()]
count_nan = len(l) - l.count()  #gives the no. of rows with no values in it
l_no_missing = l.dropna()  #Dropping the rows with missing values
f = l_no_missing  #final dataframe with no missing values
count_nan = len(f) - f.count()  #verifying if the missing vaules are removed
count_nan
airport_data = pd.read_csv('Airport_data.csv', 
                               header = 0) 
training.drop(training.columns[0], axis = 1, inplace = True)
f['CARRIER'] = f['UNIQUE_CARRIER']
f["CARRIER"] = pd.factorize(f["CARRIER"])[0]
CARRIER = f[['UNIQUE_CARRIER', 'CARRIER']].drop_duplicates()
training = f
training.drop('UNIQUE_CARRIER', axis = 1, inplace = True)
scalingDF = training[['DISTANCE']] # Numerical features
categDF = training[['MONTH', 'DAY_OF_MONTH', 'ORIGIN_AIRPORT_ID', 
                   'DEST_AIRPORT_ID', 
                   'CARRIER', 'DAY_OF_WEEK']] # Categorical features


from sklearn.preprocessing import OneHotEncoder

encoder = OneHotEncoder() # Create encoder object
categDF_encoded = encoder.fit_transform(categDF) 

type(categDF_encoded) 
from scipy import sparse # Need this to create a sparse array
scalingDF_sparse = sparse.csr_matrix(scalingDF) #can't convert numerical array to sparse

scipy import sparse中的TypeError Traceback（最近一次调用last）（＃1）需要这个来创建一个稀疏数组----> 2 scalingDF_sparse = sparse.csr_matrix（scalingDF）/ Users / nikhil_maladkar / anaconda / lib / python2 . 7 / site-packages / scipy / sparse / compressed.pyc in init（self，arg1，shape，dtype，copy）67 self.format）68来自.coo import coo_matrix ---> 69 self._set_self（self.class（ coo_matrix（arg1，dtype = dtype）））70 71＃读取给定的矩阵尺寸，如果在init中有/Users/nikhil_maladkar/anaconda/lib/python2.7/site-packages/scipy/sparse/compressed.pyc（self，arg1 ，形状，类型，复制）29 arg1 = arg1.copy（）30其他：---> 31 arg1 = arg1.asformat（self.format）32 self._set_self（arg1）33 / Users / nikhil_maladkar / anaconda / lib / asformat中的python2.7 / site-packages / scipy / sparse / base.pyc（self，format）218返回self 219 else： - > 220 return getattr（self，'to'format）（）221 222 #### ################################################## ############# /Users/nikhil_maladkar/anaconda/lib/python2.7/site-packages tocsr中的/scipy/sparse/coo.pyc（self）328 indptr = np.empty（M 1，dtype = idx_dtype）329 indices = np.empty（self.nnz，dtype = idx_dtype） - > 330 data = np . 空（self.nnz，dtype = upcast（self.dtype））331 332 coo_tocsr（M，N，self.nnz，/ Users / nikhil_maladkar / anaconda / lib / python2.7 / site-packages / scipy / sparse / sputils . pyc in upcast（* args）55返回t 56 ---> 57引发TypeError（'类型不支持转换：％r'％（args，））58 59 TypeError：类型不支持转换：（dtype（'O “））