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<p>我有两个Pandas数据帧,即:<code>habitat_family</code>和{<cd2>}。我想根据分类法<code>lookupMap</code>和{<cd1>}中的值填充{<cd2>}:</p>
<pre><code>import pandas as pd
import numpy as np
species = ['tiger', 'lion', 'mosquito', 'ladybug', 'locust', 'seal', 'seabass', 'shark', 'dolphin']
families = ['mammal','fish','insect']
lookupMap = {'tiger':'mammal', 'lion':'mammal', 'mosquito':'insect', 'ladybug':'insect', 'locust':'insect',
'seal':'mammal', 'seabass':'fish', 'shark':'fish', 'dolphin':'mammal' }
habitat_family = pd.DataFrame({'id': range(1,11),
'mammal': [101,123,523,562,546,213,562,234,987,901],
'fish' : [625,254,929,827,102,295,174,777,123,763],
'insect': [345,928,183,645,113,942,689,539,789,814]
}, index=range(1,11), columns=['id','mammal','fish','insect'])
habitat_species = pd.DataFrame(0.0, index=range(1,11), columns=species)
# My highly inefficient solution:
for id in habitat_family.index: # loop through habitat id's
for spec in species: # loop through species
corresp_family = lookupMap[spec]
habitat_species.loc[id,spec] = habitat_family.loc[id,corresp_family]
</code></pre>
<p>上面嵌套的for循环完成了这项工作。但实际上,我的数据帧的大小是巨大的,使用for循环是不可行的。在</p>
<p><strong>是否有一种更有效的方法来实现这一点,使用may<code>dataframe.apply()</code>或类似的函数?</strong></p>
<p>编辑:所需的输出<code>habitat_species</code>是:</p>
^{pr2}$