Python 使用 Pandas 为字符串列中的每个值添加字符串前缀
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add a string prefix to each value in a string column using Pandas
提问by TheChymera
I would like to append a string to the start of each value in a said column of a pandas dataframe (elegantly). I already figured out how to kind-of do this and I am currently using:
我想在 Pandas 数据帧的所述列中的每个值的开头附加一个字符串（优雅）。我已经想出了如何做到这一点，我目前正在使用：
df.ix[(df['col'] != False), 'col'] = 'str'+df[(df['col'] != False), 'col']
This seems one hell of an inelegant thing to do - do you know any other way (which maybe also adds the character to rows where that column is 0 or NaN)?
这似乎是一件非常不雅的事情 - 您知道其他任何方式吗（这可能还会将字符添加到该列为 0 或 NaN 的行中）？
In case this is yet unclear, I would like to turn:
如果这还不清楚，我想转：
col
1 a
2 0
into:
进入：
col
1 stra
2 str0
采纳答案by Roman Pekar
df['col'] = 'str' + df['col'].astype(str)
Example:
例子：
>>> df = pd.DataFrame({'col':['a',0]})
>>> df
col
0 a
1 0
>>> df['col'] = 'str' + df['col'].astype(str)
>>> df
col
0 stra
1 str0
回答by Cleb
As an alternative, you can also use an applycombined with format(or better with f-strings) which I find slightly more readable if one e.g. also wants to add a suffix or manipulate the element itself:
作为替代方案，您还可以使用apply与format（或更好地与 f-strings）结合使用，如果一个人还想添加后缀或操纵元素本身，我发现它的可读性稍强：
df = pd.DataFrame({'col':['a', 0]})
df['col'] = df['col'].apply(lambda x: "{}{}".format('str', x))
which also yields the desired output:
这也产生了所需的输出：
col
0 stra
1 str0
If you are using Python 3.6+, you can also use f-strings:
如果您使用的是 Python 3.6+，您还可以使用 f-strings：
df['col'] = df['col'].apply(lambda x: f"str{x}")
yielding the same output.
产生相同的输出。
The f-string version is almost as fast as @RomanPekar's solution (python 3.6.4):
f-string 版本几乎与@RomanPekar 的解决方案（python 3.6.4）一样快：
df = pd.DataFrame({'col':['a', 0]*200000})
%timeit df['col'].apply(lambda x: f"str{x}")
117 ms ± 451 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)
%timeit 'str' + df['col'].astype(str)
112 ms ± 1.04 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
Using format, however, is indeed far slower:
format但是，使用确实要慢得多：
%timeit df['col'].apply(lambda x: "{}{}".format('str', x))
185 ms ± 1.07 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
回答by Vasyl Vaskivskyi
If you load you table file with dtype=str
or convert column type to string df['a'] = df['a'].astype(str)
then you can use such approach:
如果您加载表文件dtype=str
或将列类型转换为字符串，df['a'] = df['a'].astype(str)
则可以使用这种方法：
df['a']= 'col' + df['a'].str[:]
This approach allows prepend, append, and subset string of df.
Works on Pandas v0.23.4, v0.24.1. Don't know about earlier versions.
这种方法允许在df.
适用于 Pandas v0.23.4、v0.24.1。不知道早期版本。
回答by Lukas
Another solution with .loc:
.loc 的另一个解决方案：
df = pd.DataFrame({'col': ['a', 0]})
df.loc[df.index, 'col'] = 'string' + df['col'].astype(str)
This is not as quick as solutions above (>1ms per loop slower) but may be useful in case you need conditional change, like:
这不像上面的解决方案那么快（每个循环慢> 1ms），但在您需要条件更改的情况下可能很有用，例如：
mask = (df['col'] == 0)
df.loc[mask, 'col'] = 'string' + df['col'].astype(str)
回答by Boxtell
You can use pandas.Series.map :
您可以使用 pandas.Series.map ：
df['col'].map('str{}'.format)
It will apply the word "str" before all your values.
它将在所有值之前应用“str”一词。
