[英]Create a new column in data frame from a dict
I have a Pandas df: 我有一个熊猫df:
a b c
0 'k' 2 4
1 'l' 3 7
2 'm' 0 -3
3 'n' 4 4
I have a dict: {'k': 'kilo', 'l': 'lima', 'm': 'mike', 'n': 'november'} 我有一个字典:{'k':'kilo','l':'lima','m':'mike','n':'十一月'}
How can I create a new column in my df across those keys from the dict: 如何在df中跨字典的那些键创建新列:
a b c new
0 'k' 2 4 'kilo'
1 'l' 3 7 'lima'
2 'm' 0 -3 'mike'
3 'n' 4 4 'november'
Thank you. 谢谢。
Just call map
and pass the dict, this will perform a lookup of your series values against the values in your dict, this is vectorised and will be much faster than doing this in a loop: 只需调用
map
并传递dict,这将对您的dict中的值执行一系列值的查找,这是矢量化的,并且比循环执行要快得多:
In [26]:
t = {'k': 'kilo', 'l': 'lima', 'm': 'mike', 'n': 'november'}
df['new'] = df['a'].map(t)
df
Out[26]:
a b c new
0 k 2 4 kilo
1 l 3 7 lima
2 m 0 -3 mike
3 n 4 4 november
I notice that in your data you have quote marks around your data, in which case the above won't work because your dict keys are just a single character so you would need to define your dict with quote marks also for the keys: 我注意到,在您的数据中,您的数据周围带有引号,在这种情况下,上述操作将无效,因为您的字典键只是一个字符,因此您还需要为键定义带引号的字典:
In [28]:
t = {"'k'": 'kilo', "'l'": 'lima', "'m'": 'mike', "'n'": 'november'}
df['new'] = df['a'].map(t)
df
Out[28]:
a b c new
0 'k' 2 4 kilo
1 'l' 3 7 lima
2 'm' 0 -3 mike
3 'n' 4 4 november
however, I would just remove the quote marks if they are unnecessary: 但是,如果不需要引号,我将删除它们:
In [30]:
df['a'] = df['a'].str.replace("'", '')
df['a']
Out[30]:
0 k
1 l
2 m
3 n
Name: a, dtype: object
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