pandas 从多索引数据框中删除特定行
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Drop specific rows from multiindex Dataframe
提问by micyukcha
I have a multi-index dataframe that looks like this:
我有一个多索引数据框，如下所示：
start grad
1995-96 1995-96 15 15
1996-97 6 6
2002-03 1 1
2007-08 1 1
I'd like to drop by the specific values for the first level (level=0). In this case, I'd like to drop everything that has 1995-96 in the first index.
我想删除第一级（级别 = 0）的特定值。在这种情况下，我想删除第一个索引中包含 1995-96 的所有内容。
回答by Paul H
pandas.DataFrame.droptakes level as an optional argument
pandas.DataFrame.drop将 level 作为可选参数
df.drop('1995-96', level='start')
df.drop('1995-96', level='start')
As of v0.18.1, its docstring says:
从 v0.18.1 开始，它的文档字符串说：
""" Signature: df.drop(labels, axis=0, level=None, inplace=False, errors='raise') Docstring: Return new object with labels in requested axis removed. Parameters ---------- labels : single label or list-like axis : int or axis name level : int or level name, default None For MultiIndex inplace : bool, default False If True, do operation inplace and return None. errors : {'ignore', 'raise'}, default 'raise' If 'ignore', suppress error and existing labels are dropped. .. versionadded:: 0.16.1 """
""" Signature: df.drop(labels, axis=0, level=None, inplace=False, errors='raise') Docstring: Return new object with labels in requested axis removed. Parameters ---------- labels : single label or list-like axis : int or axis name level : int or level name, default None For MultiIndex inplace : bool, default False If True, do operation inplace and return None. errors : {'ignore', 'raise'}, default 'raise' If 'ignore', suppress error and existing labels are dropped. .. versionadded:: 0.16.1 """
