如何使用多个 numpy 1d 数组创建一个 Pandas DataFrame？
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How to create a pandas DataFrame with several numpy 1d arrays?
提问by laurenz
I've created some np.arrays to do some calculation with them. (All have the same size [100,1]) Now I want to create a pandas Dataframe and each array shoud be one column of that DF. The Names of the arrays should be the header of the DataFrame.
我创建了一些 np.arrays 来对它们进行一些计算。（都具有相同的大小 [100,1]）现在我想创建一个 Pandas Dataframe，并且每个数组都应该是该 DF 的一列。数组的名称应该是 DataFrame 的标题。
In Matlab I would easily do it like that:
在 Matlab 中，我会很容易地这样做：
Table = table(array1, array2, array3, ... );
Table = table(array1, array2, array3, ... );
How can I do this in Python?
我怎样才能在 Python 中做到这一点？
thanks in advance!
提前致谢！
回答by ayhan
Let's say these are your arrays:
假设这些是您的数组：
arr1, arr2, arr3 = np.zeros((3, 100, 1))
arr1.shape
Out: (100, 1)
You can use hstackto stack them and pass the resulting 2D array to the DataFrame constructor:
您可以使用hstack来堆叠它们并将生成的二维数组传递给 DataFrame 构造函数：
df = pd.DataFrame(np.hstack((arr1, arr2, arr3)))
df.head()
Out:
0 1 2
0 0.0 0.0 0.0
1 0.0 0.0 0.0
2 0.0 0.0 0.0
3 0.0 0.0 0.0
4 0.0 0.0 0.0
Or name the columns as arr1, arr2, ...:
或将列命名为arr1, arr2, ...：
df = pd.DataFrame(np.hstack((arr1, arr2, arr3)),
columns=['arr{}'.format(i+1) for i in range(3)])
which gives
这使
df.head()
Out:
arr1 arr2 arr3
0 0.0 0.0 0.0
1 0.0 0.0 0.0
2 0.0 0.0 0.0
3 0.0 0.0 0.0
4 0.0 0.0 0.0
回答by jezrael
Solution with numpy.concatenatefor 2d array and DataFrameconstructor:
numpy.concatenate二维数组和DataFrame构造函数的解决方案：
df = pd.DataFrame(np.concatenate([arr1, arr2, arr3], axis=1), columns= ['a','b','c'])
