英文:
How do I stack a wide Polars DataFrame in Rust into a narrow DataFrame?
问题
在R中，我正在像这样堆叠一个数据框：stack(preds[1:(ncol(preds)-4)])
这会选择1,000列，并将它们全部堆叠到一个单独的列中，同时创建一个第二列，该列是原始行来自的列的名称的字符串。
然后，我使用cbind()组合了我没有堆叠的其余列，由于它们的长度与堆叠的数据框不同，它们会被隐式重复。
cbind(preds[ncol(preds)], preds[ncol(preds)-3], preds[ncol(preds)-2], preds[ncol(preds)-1], stack(preds[1:(ncol(preds)-4)])
我正在尝试在Rust中使用Polars来复制这个操作，但找不到任何堆叠函数。我是否只需迭代要堆叠的所有Series，调用append()，并手动重复其余的列，然后使用with_columns()将它们连接到堆叠的列中？
英文:
In R, I am stacking a data.frame like so: stack(preds[1:(ncol(preds)-4)])
This selects 1,000 columns, and stacks them all into a single column, while creating a second column which is a string, the name of the column that row originally came from.
I then combine the remaining columns I did not stack with cbind(), which are implicitly repeated since they do not have the same length as the stacked data.frame.
cbind(preds[ncol(preds)], preds[ncol(preds)-3], preds[ncol(preds)-2], preds[ncol(preds)-1], stack(preds[1:(ncol(preds)-4)]))
I am trying to replicate this in Rust using Polars, but cannot find any kind of stacking function. Do I just need to iterate over all the Series to be stacked, calling append(), and manually repeat the remaining columns and join those to the stacked one with with_columns()?
答案1
得分: 1
melt() 是用于此目的的内置函数。请注意，当前最新版本0.27.2的时间复杂度是O(n^2)。如果您需要它更快，您将需要从主分支安装 polars = { git = "https://github.com/pola-rs/polars" }，以获取最新的bug修复，使其具有O(n)的时间复杂度。
英文:
melt() is the built-in function for this purpose. Note that the current latest release, 0.27.2, is O(n^2). If you need it to be fast you will need to install from the master branch polars = { git = "https://github.com/pola-rs/polars" } to get the latest bug fix that makes it O(n).
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