1、list 转 numpy.ndarray: ? np.array()
2、numpy.ndarray 转 pandas.Dataframe： pandas.DataFrame()
3、pandas.Dataframe 转 numpy.ndarray： Dataframe.values
4、numpy.ndarray 转 list: ?array.tolist()
示例：
import numpy as np
import pandas as pd
a = [[1, 2, 3],[4, 5, 6]] # list
b = np.array(a) # list to ndarray
c = pd.DataFrame(b) # ndarray to dataframe
print('type a:',type(a),'\ntype b:',type(b),'\ntype c:',type(c))
d = c.values # dataframe to ndarray
e = d.tolist() # ndarray to list
print('type d:',type(d),'\ntype e:',type(e))输出结果：
type a: <class 'list'>
type b: <class 'numpy.ndarray'>
type c: <class 'pandas.core.frame.DataFrame'>
type d: <class 'numpy.ndarray'>
type e: <class 'list'>numpy.ndarray 与 torch.tensor 的相互转换：
import torch
import numpy as np
a = np.ones(10) # array
b = torch.from_numpy(a).type(torch.FloatTensor) # array to tensor
c = b.numpy() # tensor to array
print('type a:',type(a),'\ntype b:',type(b),'\ntype c:',type(c))输出结果：
type a: <class 'numpy.ndarray'>
type b: <class 'torch.Tensor'>
type c: <class 'numpy.ndarray'>
