我正在尝试过滤掉field_A为空的记录或数据框中的空字符串,如下所示:
my_df[my_df.editions is not None]
my_df.shape
这给了我错误:
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-40-e1969e0af259> in <module>()
1 my_df['editions'] = my['editions'].astype(str)
----> 2 my_df = my_df[my_df.editions is not None]
3 my_df.shape
/home/edamame/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc in __getitem__(self, key)
1995 return self._getitem_multilevel(key)
1996 else:
-> 1997 return self._getitem_column(key)
1998
1999 def _getitem_column(self, key):
/home/edamame/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc in _getitem_column(self, key)
2002 # get column
2003 if self.columns.is_unique:
-> 2004 return self._get_item_cache(key)
2005
2006 # duplicate columns & possible reduce dimensionality
/home/edamame/anaconda2/lib/python2.7/site-packages/pandas/core/generic.pyc in _get_item_cache(self, item)
1348 res = cache.get(item)
1349 if res is None:
-> 1350 values = self._data.get(item)
1351 res = self._box_item_values(item, values)
1352 cache[item] = res
/home/edamame/anaconda2/lib/python2.7/site-packages/pandas/core/internals.pyc in get(self, item, fastpath)
3288
3289 if not isnull(item):
-> 3290 loc = self.items.get_loc(item)
3291 else:
3292 indexer = np.arange(len(self.items))[isnull(self.items)]
/home/edamame/anaconda2/lib/python2.7/site-packages/pandas/indexes/base.pyc in get_loc(self, key, method, tolerance)
1945 return self._engine.get_loc(key)
1946 except KeyError:
-> 1947 return self._engine.get_loc(self._maybe_cast_indexer(key))
1948
1949 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4154)()
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4018)()
pandas/hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12368)()
pandas/hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12322)()
KeyError: True
或
my_df[my_df.editions != None]
my_df.shape
这个没有错误,但没有过滤掉任何None值。
我也尝试过:
my_df = my_df[my_df.editions.notnull()]
这个没有给出错误,但也没有过滤掉任何无值。
有人可以建议如何解决这个问题吗?谢谢!
答案 0 :(得分:3)
您可以通过过滤创建新的数据框吗?
之前的数据框:
a b
1 9
2 10
3 11
4 12
5 13
6 14
7 15
8 null
示例:
import pandas
my_df = pandas.DataFrame({"a":[1,2,3,4,5,6,7,8],"b":[9,10,11,12,13,14,15,"null"]})
my_df2= my_df[(my_df['b']!="null")]
print(my_df2)
之后的数据框:
a b
1 9
2 10
3 11
4 12
5 13
6 14
7 15
它正在做的是寻找&#34; null&#34;并排除它。你可以用空字符串做同样的事情。
答案 1 :(得分:3)
您可以在使用~
进行过滤时对条件进行否定。
因此,您应该这样做:
my_df = my_df[~my_df.editions.isnull()]
答案 2 :(得分:1)
您可以像这样过滤掉数据框中的空字符串:
df = df[df['str_field'].str.len() > 0]
答案 3 :(得分:0)
如果我们想根据 Null 和 Empty 字符串过滤掉,我们可以使用
df = df[ (df['str_field'].isnull()) | (df['str_field'].str.len() == 0) ]
使用逻辑运算符 ('|' , '&', '~') 混合两个条件