将数据框转换为元组列表 [英] Convert a dataframe to list of tuples

问题描述

我有一个像这样的python pandas dataframe df:

I have a python pandas dataframe df like this:

a  b
1  3
3  6
5  7
6  4
7  8

我想将其转移到列表中

[(1,3),(3,6),(5,7),(6,4),(7,8)]

谢谢.

推荐答案

如果性能很重要，请使用列表理解:

If performance is important, use a list comprehension:

[tuple(r) for r in df.to_numpy()]
# [(1, 3), (3, 6), (5, 7), (6, 4), (7, 8)]

注意:对于熊猫< 0.24，请改用df.values.

Note: For pandas < 0.24, please use df.values instead.

如果遍历列表而不是numpy数组，则可能会发现更好的性能:

You may find even better performance if you iterate over lists instead of the numpy array:

[tuple(r) for r in df.to_numpy().tolist()]
# [(1, 3), (3, 6), (5, 7), (6, 4), (7, 8)]

此方法可以任意数量的列.但是，如果要选择一组要转换的特定列，则可以预先选择它们.

This method to any number of columns. However, if you want to select a specific set of columns to convert, you can select them beforehand.

[tuple(r) for r in df[['a', 'b']].to_numpy()]
# [(1, 3), (3, 6), (5, 7), (6, 4), (7, 8)]

---

另一种替代方法是使用map.

list(map(tuple, df.to_numpy()))
# [(1, 3), (3, 6), (5, 7), (6, 4), (7, 8)]

就性能而言，这与列表理解大致相同.您可以使用相同的方式进行概括.

This is roughly the same as the list comprehension, performance wise. You can generalise the same way.

另一种选择是使用apply并将结果转换为列表:

Another option is to use apply and convert the result to a list:

df.apply(tuple, axis=1).tolist()
# [(1, 3), (3, 6), (5, 7), (6, 4), (7, 8)]

这比较慢，所以不推荐.

This is slower, so it not recommended.

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