[英]dataframe row as into numpy array
I have a dataframe, columns to be used are "sepal_length" and "sepal_width".我有一个数据框,要使用的列是“sepal_length”和“sepal_width”。 I want to turn each single row into a single data point, like
point1= [5.1 3.5]
and point2 = [4.9 3]
and so on.我想把每一行变成一个单一的数据点,比如
point1= [5.1 3.5]
和point2 = [4.9 3]
等等。 .to_numpy() just turns the whole 2 columns into large-sized numpy array, so it does not work for me. .to_numpy() 只是将整个 2 列变成大型 numpy 数组,所以它对我不起作用。 How can I work out?
我该如何锻炼?
You can simply use this:你可以简单地使用这个:
nump_df=df.values
print(nump_df)
or或者
You can iterate over rows and convert each row to numpy array and append those arrays in a list.您可以遍历行并将每一行转换为 numpy 数组并将这些数组附加到列表中。 I hope the following code will help you:
我希望以下代码可以帮助您:
point=[]
for idx, row in df.iterrows():
p=row.to_numpy()
point.append(p)
print(point)
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