pandas 熊猫将列类型从列表转换为 np.array
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Pandas convert columns type from list to np.array
提问by LeoCella
I'm trying to apply a function to a pandas dataframe, such a function required two np.array as input and it fit them using a well defined model.
我正在尝试将一个函数应用于Pandas数据框，这样的函数需要两个 np.array 作为输入，它使用定义良好的模型来拟合它们。
The point is that I'm not able to apply this function starting from the selected columns since their "rows" contain list read from a JSON file and not np.array.
关键是我无法从选定的列开始应用此函数，因为它们的“行”包含从 JSON 文件读取的列表，而不是 np.array。
Now, I've tried different solutions:
现在，我尝试了不同的解决方案：
#Here is where I discover the problem
train_df['result'] = train_df.apply(my_function(train_df['col1'],train_df['col2']))
#so I've tried to cast the Series before passing them to the function in both these ways:
X_col1_casted = trai_df['col1'].dtype(np.array)
X_col2_casted = trai_df['col2'].dtype(np.array)
doesn't work.
不起作用。
X_col1_casted = trai_df['col1'].astype(np.array)
X_col2_casted = trai_df['col2'].astype(np.array)
doesn't work.
不起作用。
X_col1_casted = trai_df['col1'].dtype(np.array)
X_col2_casted = trai_df['col2'].dtype(np.array)
does'nt work.
不起作用。
What I'm thinking to do now is a long procedure like:
我现在想做的是一个很长的程序，例如：
starting from the uncasted column-series, convert them into list(), iterate on them apply the function to the np.array() single elements, and append the results into a temporary list. Once done I will convert this list into a new column. ( clearly, I don't know if it will work )
从未转换的列系列开始，将它们转换为 list()，对它们进行迭代，将函数应用于 np.array() 单个元素，并将结果附加到临时列表中。完成后，我会将这个列表转换为一个新列。（显然，我不知道它是否会起作用）
Does anyone of you know how to help me ?
你们中有人知道如何帮助我吗？
EDIT: I add one example to be clear:
编辑：为了清楚起见，我添加了一个示例：
The function assume to have as input two np.arrays. Now it has two lists since they are retrieved form a json file. The situation is this one:
该函数假设有两个 np.array 作为输入。现在它有两个列表，因为它们是从 json 文件中检索的。情况是这样的：
col1 col2 result
[1,2,3] [4,5,6] [5,7,9]
[0,0,0] [1,2,3] [1,2,3]
Clearly the function is not the sum one, but a own function. For a moment assume that this sum can work only starting from arrays and not form lists, what should I do ?
显然这个函数不是求和函数，而是一个自己的函数。暂时假设这个总和只能从数组开始而不是从列表开始，我该怎么办？
Thanks in advance
提前致谢
回答by Nickil Maveli
Use applyto convert each element to it's equivalent array:
使用apply每个元素转换为它的等效阵：
df['col1'] = df['col1'].apply(lambda x: np.array(x))
type(df['col1'].iloc[0])
numpy.ndarray
Data:
数据：
df = pd.DataFrame({'col1': [[1,2,3],[0,0,0]]})
df
