Python 如何将pandas数据帧转换为NumPy数组?
根据我从上一篇文章中得到的建议,我将熊猫数据帧转换为数字NumPy数组。为此,我使用了Python 如何将pandas数据帧转换为NumPy数组?,python,pandas,numpy,dataframe,Python,Pandas,Numpy,Dataframe,根据我从上一篇文章中得到的建议,我将熊猫数据帧转换为数字NumPy数组。为此,我使用了numpy.asarray 我的数据帧: DataFrame ---------- label vector 0 0 1:0.0033524514 2:-0.021896651 3:0.05087798 4:... 1 0 1:0.02134219 2:-0.007388
numpy.asarray
我的数据帧:
DataFrame
----------
label vector
0 0 1:0.0033524514 2:-0.021896651 3:0.05087798 4:...
1 0 1:0.02134219 2:-0.007388343 3:0.06835007 4:0....
2 0 1:0.030515702 2:-0.0037591448 3:0.066626 4:0....
3 0 1:0.0069114454 2:-0.0149497045 3:0.020777626 ...
4 1 1:0.003118149 2:-0.015105667 3:0.040879637 4:...
... ... ...
19779 0 1:0.0042634667 2:-0.0044222944 3:-0.012995412...
19780 1 1:0.013818732 2:-0.010984628 3:0.060777966 4:...
19781 0 1:0.00019213723 2:-0.010443398 3:0.01679976 4...
19782 0 1:0.010373874 2:0.0043582567 3:-0.0078354385 ...
19783 1 1:0.0016790542 2:-0.028346825 3:0.03908631 4:...
[19784 rows x 2 columns]
DataFrame datatypes :
label object
vector object
dtype: object
要转换为Numpy数组,我使用以下脚本:
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import svm
from sklearn import metrics
from sklearn.preprocessing import OneHotEncoder
import numpy as np
import matplotlib.pyplot as plt
r_filenameTSV = 'TSV/A19784.tsv'
tsv_read = pd.read_csv(r_filenameTSV, sep='\t',names=["vector"])
df = pd.DataFrame(tsv_read)
df = pd.DataFrame(df.vector.str.split(' ',1).tolist(),
columns = ['label','vector'])
print('DataFrame\n----------\n', df)
print('\nDataFrame datatypes :\n', df.dtypes)
arr = np.asarray(df, dtype=np.float64)
print('\nNumpy Array\n----------\n', arr)
print('\nNumpy Array Datatype :', arr.dtype)
我在第22行遇到这个错误arr=np.asarray(df,dtype=np.float64)
我如何解决这个问题
问候并感谢您的时间您的一列似乎是字符串,而不是整数。在将数据帧转换为数组之前,请删除该列或将其编码为字符串将列表理解与嵌套字典理解一起用于
数据帧
:
df = pd.read_csv(r_filenameTSV, sep='\t',names=["vector"])
df = pd.DataFrame([dict(y.split(':') for y in x.split()) for x in df['vector']])
print (df)
1 2 3 4
0 0.0033524514 -0.021896651 0.05087798 0
1 0.02134219 -0.007388343 0.06835007 0
2 0.030515702 -0.0037591448 0.066626 0
3 0.0069114454 -0.0149497045 0.020777626 0
4 0.003118149 -0.015105667 0.040879637 0.4
然后转换为浮点和numpy数组:
print (df.astype(float).to_numpy())
[[ 0.00335245 -0.02189665 0.05087798 0. ]
[ 0.02134219 -0.00738834 0.06835007 0. ]
[ 0.0305157 -0.00375914 0.066626 0. ]
[ 0.00691145 -0.0149497 0.02077763 0. ]
[ 0.00311815 -0.01510567 0.04087964 0.4 ]]
print (df.astype(float).to_numpy())
[[ 0.00335245 -0.02189665 0.05087798 0. ]
[ 0.02134219 -0.00738834 0.06835007 0. ]
[ 0.0305157 -0.00375914 0.066626 0. ]
[ 0.00691145 -0.0149497 0.02077763 0. ]
[ 0.00311815 -0.01510567 0.04087964 0.4 ]]