将 np 数组添加到现有的 Pandas 数据框
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Adding np arrays to existing pandas dataframe
提问by
I've been trying to figure out a problem I came across for a while now, but somehow I cannot find the solution.
我一直试图找出我现在遇到的一个问题，但不知何故我找不到解决方案。
I've created a pandas dataframe which is already filled with values, let's say dimension (4,3)
我创建了一个已经填充了值的 Pandas 数据框，比如说维度 (4,3)
df=
A B C
0 valX valX valX
1 valY valY valY
2 valZ valZ valZ
3 valW valW valW
What I want to do right now is append ten additional columns, each containing a numpy array filled with 38 zero's.
我现在想要做的是附加十个额外的列，每列包含一个填充了 38 个零的 numpy 数组。
My solution seems to be working when I first cast my array to a string and then add it to the original df.
当我第一次将数组转换为字符串然后将其添加到原始 df 时，我的解决方案似乎有效。
However, Pandas doesn't accept a plain numpy array. I need the value of the column to be a numpy array, as I will later do some sklearn computations on them.
但是，Pandas 不接受普通的 numpy 数组。我需要列的值是一个 numpy 数组，因为我稍后会对它们进行一些 sklearn 计算。
Later in my code, I substitute certain columns with a one-hot encoding of certain characters. The remaining columns act as a zero-padding.
后来在我的代码中，我用某些字符的一次性编码替换了某些列。其余列充当零填充。
Example of my code (which works for adding 10 columns):
我的代码示例（适用于添加 10 列）：
#create empty array
x = np.zeros(38)
for i in range(0, 10):
col_name = "char_" + str(i)
df[col_name] = str(x)
The problem here is that I need to cast x to a string. If I keep it as a numpy array, it throws me this error:
这里的问题是我需要将 x 转换为字符串。如果我将它保留为一个 numpy 数组，它会抛出这个错误：
ValueError: Length of values does not match length of index
采纳答案by jezrael
Use:
用：
x = np.zeros(38)
for i in range(0, 10):
col_name = "char_" + str(i)
df[col_name] = pd.Series([x], index=df.index)
print (type(df.loc[0,'char_9']))
<class 'numpy.ndarray'>
