将 Pandas DataFrame 中的列值与“NaN”值连接起来
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/23444858/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Concatenate column values in Pandas DataFrame with "NaN" values
提问by Nilani Algiriyage
I'm trying to concatenate Pandas DataFramecolumns with NaN values.
我正在尝试将 PandasDataFrame列与 NaN 值连接起来。
In [96]:df = pd.DataFrame({'col1' : ["1","1","2","2","3","3"],
'col2' : ["p1","p2","p1",np.nan,"p2",np.nan], 'col3' : ["A","B","C","D","E","F"]})
In [97]: df
Out[97]:
col1 col2 col3
0 1 p1 A
1 1 p2 B
2 2 p1 C
3 2 NaN D
4 3 p2 E
5 3 NaN F
In [98]: df['concatenated'] = df['col2'] +','+ df['col3']
In [99]: df
Out[99]:
col1 col2 col3 concatenated
0 1 p1 A p1,A
1 1 p2 B p2,B
2 2 p1 C p1,C
3 2 NaN D NaN
4 3 p2 E p2,E
5 3 NaN F NaN
Instead of 'NaN' values in "concatenated" column, I want to get "D" and "F" respectively for this example?
在这个例子中，我想分别得到“D”和“F”而不是“连接”列中的“NaN”值？
回答by Kiwi
I don't think your problem is trivial. However, here is a workaround using numpy vectorization :
我不认为你的问题是微不足道的。但是，这是使用 numpy 矢量化的解决方法：
In [49]: def concat(*args):
...: strs = [str(arg) for arg in args if not pd.isnull(arg)]
...: return ','.join(strs) if strs else np.nan
...: np_concat = np.vectorize(concat)
...:
In [50]: np_concat(df['col2'], df['col3'])
Out[50]:
array(['p1,A', 'p2,B', 'p1,C', 'D', 'p2,E', 'F'],
dtype='|S64')
In [51]: df['concatenated'] = np_concat(df['col2'], df['col3'])
In [52]: df
Out[52]:
col1 col2 col3 concatenated
0 1 p1 A p1,A
1 1 p2 B p2,B
2 2 p1 C p1,C
3 2 NaN D D
4 3 p2 E p2,E
5 3 NaN F F
[6 rows x 4 columns]
回答by sl1129
You could first replace NaNs with empty strings, for the whole dataframe or the column(s) you desire.
对于整个数据框或您想要的列，您可以先用空字符串替换 NaN。
In [6]: df = df.fillna('')
In [7]: df['concatenated'] = df['col2'] +','+ df['col3']
In [8]: df
Out[8]:
col1 col2 col3 concatenated
0 1 p1 A p1,A
1 1 p2 B p2,B
2 2 p1 C p1,C
3 2 D ,D
4 3 p2 E p2,E
5 3 F ,F
