pandas 如何选择数据框中的特定列？
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How to choose specific columns in a dataframe?
提问by DevanshuMishra
I have a dataframe with 25 columns and an array([ 2, 4, 8, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22, 23], dtype=int64). I want to choose some specific columns from the dataframe whose indices are given by the elements of the array and store them in a new dataframe(say df1). So for example,the new dataframe, will have the 2nd, 4th,....23rd column of the original data frame.
我有一个包含 25 列的数据框和一个数组 ([ 2, 4, 8, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22, 23], dtype=int64)。我想从数据框中选择一些特定的列，这些列的索引由数组的元素给出，并将它们存储在一个新的数据框中（比如 df1）。因此，例如，新数据框将具有原始数据框的第 2、第 4、....23 列。
采纳答案by Zev
You can use ilocto accomplish this. For example:
您可以使用它iloc来完成此操作。例如：
import pandas as pd
df = pd.DataFrame(
[np.random.rand(5),np.random.rand(5), np.random.rand(5), np.random.rand(5)]
)
df.iloc[:,[1,3]]
Which outputs:
哪些输出：
1 3
0 0.883848 0.409460
1 0.537549 0.426643
2 0.825185 0.361043
3 0.039343 0.674435
You may see older answers suggesting .ix(such as the answer in this questionthat I adapted this from) however, that has been deprecated.
您可能会看到较旧的答案暗示.ix（例如我改编自的这个问题中的答案），但是，这已被弃用。
