[英]Pandas DataFrame Column of Lists: Remove a Specific Value
我有一个带有列表列的Pandas DataFrame。 我想创建一个包含这些相同列表的新列,减去一个特定元素:
[In]:
key1 = 'site channel fiscal_week'.split()
key2 = 'site dude fiscal_week'.split()
key3 = 'site eng fiscal_week'.split()
keys = pd.DataFrame({'key': [1,2,3],
'dims': [key1,key2,key3]})
keys
[Out]:
dims key
[site, channel, fiscal_week] 1
[site, dude, fiscal_week] 2
[site, eng, fiscal_week] 3
这是我的方法失败了:
keys['reduced_dims'] = keys['dims'].remove('fiscal_week')
我需要能够删除特定元素,而不是最后一个元素的pop()
。
所需的输出:
[Out]:
dims key reduced_dims
[site, channel, fiscal_week] 1 [site, channel]
[site, dude, fiscal_week] 2 [site, dude]
[site, eng, fiscal_week] 3 [site, eng]
keys['dims']
是pd.Series
,不是list
,也没有list.remove()
方法。 您应该使用pd.Series.apply()
方法,该方法将某些函数应用于每行中的值。
keys['reduced_dims'] = keys['dims'].apply(
lambda row: [val for val in row if val != 'fiscal_week']
)
keys['reduced_dims']
Out:
0 [site, channel]
1 [site, dude]
2 [site, eng]
Name: reduced_dims, dtype: object
而且,您不能只使用list.remove()
函数来代替列表理解功能,
lambda row: [val for val in row if val != 'fiscal_week']
因为list.remove()
返回None
,所以您会得到这样的系列:
keys['reduced_dims'] = keys['dims'].apply(lambda x: x.remove('fiscal_week'))
keys['reduced_dims']
Out:
0 None
1 None
2 None
Name: reduced_dims, dtype: object
你可以试试
def rem_fw(lst):
lst.remove('fiscal_week')
return lst
keys['reduced_dims'] = keys['dims'].apply(rem_fw)
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