替换熊猫数据帧中所有出现的字符串（Python）
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Replace all occurrences of a string in a pandas dataframe (Python)
提问by nauti
I have a pandas dataframe with about 20 columns.
我有一个大约有 20 列的熊猫数据框。
It is possible to replace all occurrences of a string (here a newline) by manually writing all column names:
可以通过手动编写所有列名来替换所有出现的字符串（这里是换行符）：
df['columnname1'] = df['columnname1'].str.replace("\n","<br>")
df['columnname2'] = df['columnname2'].str.replace("\n","<br>")
df['columnname3'] = df['columnname3'].str.replace("\n","<br>")
...
df['columnname20'] = df['columnname20'].str.replace("\n","<br>")
This unfortunately does not work:
不幸的是，这不起作用：
df = df.replace("\n","<br>")
Is there any other, more elegant solution?
还有其他更优雅的解决方案吗？
采纳答案by Alex Riley
You can use replaceand pass the strings to find/replace as dictionary keys/items:
您可以使用replace和传递字符串作为字典键/项目来查找/替换：
df.replace({'\n': '<br>'}, regex=True)
For example:
例如：
>>> df = pd.DataFrame({'a': ['1\n', '2\n', '3'], 'b': ['4\n', '5', '6\n']})
>>> df
a b
0 1\n 4\n
1 2\n 5
2 3 6\n
>>> df.replace({'\n': '<br>'}, regex=True)
a b
0 1<br> 4<br>
1 2<br> 5
2 3 6<br>
回答by Yichuan Wang
It seems Pandas has change its API to avoid ambiguity when handling regex. Now you should use:
Pandas 似乎已经改变了它的 API 以避免在处理正则表达式时出现歧义。现在你应该使用：
df.replace({'\n': '<br>'}, regex=True)
For example:
例如：
>>> df = pd.DataFrame({'a': ['1\n', '2\n', '3'], 'b': ['4\n', '5', '6\n']})
>>> df
a b
0 1\n 4\n
1 2\n 5
2 3 6\n
>>> df.replace({'\n': '<br>'}, regex=True)
a b
0 1<br> 4<br>
1 2<br> 5
2 3 6<br>
回答by Jasper Kinoti
This will remove all newlines and unecessary spaces. You can edit the ' '.jointo specify a replacement character
这将删除所有换行符和不必要的空格。您可以编辑' '.join以指定替换字符
df['columnname'] = [''.join(c.split()) for c in df['columnname'].astype(str)]
