Convert Select Columns in Pandas Dataframe to Numpy Array

I would like to convert everything but the first column of a pandas dataframe into a numpy array. For some reason using the columns= parameter of DataFrame.to_matrix() is not working.

df:

  viz  a1_count  a1_mean     a1_std
0   n         3        2   0.816497
1   n         0      NaN        NaN 
2   n         2       51  50.000000

I tried X=df.as_matrix(columns=[df[1:]]) but this yields an array of all NaNs

the easy way is the "values" property df.iloc[:,1:].values

a=df.iloc[:,1:]
b=df.iloc[:,1:].values

print(type(df))
print(type(a))
print(type(b))

so, you can get type

<class 'pandas.core.frame.DataFrame'>
<class 'pandas.core.frame.DataFrame'>
<class 'numpy.ndarray'>

Please use the Pandas to_numpy() method. Below is an example--

>>> import pandas as pd
>>> df = pd.DataFrame({"A":[1, 2], "B":[3, 4], "C":[5, 6]})
>>> df 
    A  B  C
 0  1  3  5
 1  2  4  6
>>> s_array = df[["A", "B", "C"]].to_numpy()
>>> s_array

array([[1, 3, 5],
   [2, 4, 6]]) 

>>> t_array = df[["B", "C"]].to_numpy() 
>>> print (t_array)

[[3 5]
 [4 6]]

Hope this helps. You can select any number of columns using

columns = ['col1', 'col2', 'col3']
df1 = df[columns]

Then apply to_numpy() method.