本文介绍了 pandas ：迭代过滤DataFrame的行的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
假设我有一个 DataFrame ，所以
df = pd.DataFrame([['x', 1, 2], ['x', 1, 3], ['y', 2, 2]],
columns=['a', 'b', 'c'])
选择所有行，其中 c == 2 和 a =='x'，我可以做一些像
To select all rows where c == 2 and a == 'x', I could do something like,
df[(df['a'] == 'x') & (df['c'] == 2)]
或者我可以通过临时变量进行迭代细化，
Or I could iterative refine by making temporary variables,
df1 = df[df['a'] == 'x']
df2 = df1[df1['c'] == 2]
有没有办法迭代细化行？ p>
Is there a way to iterative refine on rows?
(
df
.refine(lambda row: row['a'] == 'x') # this method doesn't exist
.refine(lambda row: row['c'] == 2)
)
推荐答案
虽然这不是现在的解决方案，在pandas版本0.13中，您可以做到
While this isn't a solution for now, in pandas version 0.13 you'll be able to do
df.query('a == "x"').query('c == 2')
实现你想要的。
你也可以做
df['a == "x"']['c == 2']
和
df['a == "x" and c == 2']
ith
df[(df.a == 'x') & (df.c == 2)]
直到0.13？
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