<p><code>.merge()</code>与<code>pd.Series.map()</code>最接近。可以使用<code>suffixes=[]</code>关键字向重叠列添加自定义标头,例如<code>suffices=['', '_centers']</code>。在</p>
<p>注意<code>pd.Series</code>没有<code>.merge()</code>,而{<cd3>}没有{<cd9>}。在</p>
<p>与</p>
<pre><code>data2
x y Cluster
0 -1.406449 -0.244859 A
1 1.002103 0.214346 B
2 0.353894 0.353995 A
3 1.249199 -0.661904 B
4 0.623962 -1.754789 C
centers2
x y
A 0 9
B 6 9
C 0 6
</code></pre>
<p>你会得到:</p>
^{pr2}$
<p>还有一个<code>.join()</code>选项,它是另一种访问<code>.merge()</code>的方法,或者{<cd12>}如果{<cd1>}对两个{<cd15>}都是打开的<code>index</code>,则从源代码访问{<cd10>}:</p>
<pre><code>def join(self, other, on=None, how='left', lsuffix='', rsuffix='',
sort=False):
return self._join_compat(other, on=on, how=how, lsuffix=lsuffix,
rsuffix=rsuffix, sort=sort)
def _join_compat(self, other, on=None, how='left', lsuffix='', rsuffix='',
sort=False):
from pandas.tools.merge import merge, concat
if isinstance(other, Series):
if other.name is None:
raise ValueError('Other Series must have a name')
other = DataFrame({other.name: other})
if isinstance(other, DataFrame):
return merge(self, other, left_on=on, how=how,
left_index=on is None, right_index=True,
suffixes=(lsuffix, rsuffix), sort=sort)
else:
if on is not None:
raise ValueError('Joining multiple DataFrames only supported'
' for joining on index')
</code></pre>