如何在Pandas的同一數據框中合並/合並列？

Question

我有一個與此相似的數據框：

       0    1   2   3           4   5
0   1001    1   176 REMAINING   US  SOUTH
1   1002    1   176 REMAINING   US  SOUTH

我想做的是將第3,4和5列合並以創建包含第3,4和5列中所有數據的列。

所需的輸出：

       0    1   2   3           
0   1001    1   176 REMAINING US SOUTH
1   1002    1   176 REMAINING US SOUTH

我已經嘗試過了

hbadef['6'] = hbadef[['3', '4', '5']].apply(lambda x: ''.join(x), axis=1)

那沒有解決。

這是我實現時的堆棧跟蹤

 hbadef['3'] = hbadef['3'] + ' ' +  hbadef['4'] + ' ' + hbadef['5']

堆棧跟蹤：

TypeError                                 Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

TypeError: an integer is required

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2524             try:
-> 2525                 return self._engine.get_loc(key)
   2526             except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

KeyError: '3'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

TypeError: an integer is required

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-62-2da6c35d6e89> in <module>()
----> 1 hbadef['3'] = hbadef['3'] + ' ' +  hbadef['4'] + ' ' + hbadef['5']
      2 # hbadef.drop(['4', '5'], axis=1)
      3 # hbadef.columns = ['MKTcode', 'Region']
      4 
      5 # pd.concat(

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   2137             return self._getitem_multilevel(key)
   2138         else:
-> 2139             return self._getitem_column(key)
   2140 
   2141     def _getitem_column(self, key):

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in _getitem_column(self, key)
   2144         # get column
   2145         if self.columns.is_unique:
-> 2146             return self._get_item_cache(key)
   2147 
   2148         # duplicate columns & possible reduce dimensionality

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py in _get_item_cache(self, item)
   1840         res = cache.get(item)
   1841         if res is None:
-> 1842             values = self._data.get(item)
   1843             res = self._box_item_values(item, values)
   1844             cache[item] = res

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\internals.py in get(self, item, fastpath)
   3841 
   3842             if not isna(item):
-> 3843                 loc = self.items.get_loc(item)
   3844             else:
   3845                 indexer = np.arange(len(self.items))[isna(self.items)]

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2525                 return self._engine.get_loc(key)
   2526             except KeyError:
-> 2527                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2528 
   2529         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

KeyError: '3'

我嘗試刪除NaN值，但得到類似的結果。 我對為什么這樣一個簡單的功能無法正常工作感到困惑。

我將接受一個答案，以便我們可以“關閉”該問題。 這兩個答案都是可以接受的，可以解決問題，我遇到的問題很可能是應用程序錯誤，我必須獨立於該問題解決。

Answer 1

您可以簡單地添加

hbadef['3'] += ' ' +  hbadef['4'] + ' ' + hbadef['5']

然后刪除不需要的列

hbadef.drop(['4', '5'], axis=1, inplace=True)
>>> hbadef
    0   1   2   3
0   1001    1   176 REMAINING US SOUTH
1   1002    1   176 REMAINING US SOUTH

注意：如果您的欄是整數，請改用

hbadef.loc[:, 3] += ' ' + hbadef.loc[:, 4] + ' ' + hbadef.loc[:, 5]
hbadef.drop([4, 5], axis=1, inplace=True)

Answer 2

使用concat + agg

pd.concat(
    [df.iloc[:, :3], df.iloc[:, 3:].agg(' '.join, axis=1)], 
    axis=1, 
    ignore_index=True
)

      0  1    2                   3
0  1001  1  176  REMAINING US SOUTH
1  1002  1  176  REMAINING US SOUTH