使用标头和dtypes将pandas数据帧转换为numpy数组(Converting pandas dataframe to numpy array with headers and dtypes)

 我一直在尝试将pandas数据帧转换为numpy数组，并带有dtypes和头名称以便于参考。 我需要这样做，因为对熊猫的处理过于缓慢，numpy快10倍。 我有这个来自SO的代码，它给了我除了我需要的东西，结果看起来不像标准的numpy数组 - 即它没有显示形状中的列数。 
 
[In]:
df = pd.DataFrame(randn(10,3),columns=['Acol','Ccol','Bcol'])
arr_ip = [tuple(i) for i in df.as_matrix()]
dtyp = np.dtype(list(zip(df.dtypes.index, df.dtypes)))
dfnp= np.array(arr_ip, dtype=dtyp)
print(dfnp.shape)
dfnp

[Out]: 

(10,) #expecting (10,3)

array([(-1.0645345 ,  0.34590193,  0.15063829),
( 1.5010928 ,  0.63312454,  2.38309797),
(-0.10203999, -0.40589525,  0.63262773),
( 0.92725915,  1.07961763,  0.60425353),
( 0.18905164, -0.90602597, -0.27692396),
(-0.48671514,  0.14182815, -0.64240004),
( 0.05012859, -0.01969079, -0.74910076),
( 0.71681329, -0.38473052, -0.57692395),
( 0.60363249, -0.0169229 , -0.16330232),
( 0.04078263,  0.55943898, -0.05783683)],
dtype=[('Acol', '<f8'), ('Ccol', '<f8'), ('Bcol', '<f8')])
 
 我错过了什么或者有其他方法吗？ 我有很多df要转换，他们的dtypes和列名称不同，所以我需要这种自动化方法。 由于大量的df，我也需要它才能高效。 

I have been trying to convert a pandas dataframe into a numpy array, carrying over the dtypes and header names for ease of reference. I need to do this as the processing on pandas is WAY too slow, numpy is 10 fold quicker. I have this code from SO that gives me what I need apart from that the result does not look like a standard numpy array - i.e. it does not show the columns numbers in the shape.
 
[In]:
df = pd.DataFrame(randn(10,3),columns=['Acol','Ccol','Bcol'])
arr_ip = [tuple(i) for i in df.as_matrix()]
dtyp = np.dtype(list(zip(df.dtypes.index, df.dtypes)))
dfnp= np.array(arr_ip, dtype=dtyp)
print(dfnp.shape)
dfnp

[Out]: 

(10,) #expecting (10,3)

array([(-1.0645345 ,  0.34590193,  0.15063829),
( 1.5010928 ,  0.63312454,  2.38309797),
(-0.10203999, -0.40589525,  0.63262773),
( 0.92725915,  1.07961763,  0.60425353),
( 0.18905164, -0.90602597, -0.27692396),
(-0.48671514,  0.14182815, -0.64240004),
( 0.05012859, -0.01969079, -0.74910076),
( 0.71681329, -0.38473052, -0.57692395),
( 0.60363249, -0.0169229 , -0.16330232),
( 0.04078263,  0.55943898, -0.05783683)],
dtype=[('Acol', '<f8'), ('Ccol', '<f8'), ('Bcol', '<f8')])
 
Am I missing something or is there another way of doing this? I have many df's to convert and their dtypes and column names vary so I need this automated approach. I also need it to be efficient due to the large number of df's. 

原文：https://stackoverflow.com/questions/49734441