在 Pandas 数据框中检查 None
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Check for None in pandas dataframe
提问by ConanG
I would like to find where None is found in the dataframe.
我想在数据框中找到 None 的位置。
pd.DataFrame([None,np.nan]).isnull()
OUT:
0
0 True
1 True
isnull() finds both numpy Nan and None values.
isnull() 找到 numpy Nan 和 None 值。
I only want the None values and not numpy Nan. Is there an easier way to do that without looping through the dataframe?
我只想要 None 值而不是 numpy Nan。有没有更简单的方法来做到这一点而不循环遍历数据框？
Edit: After reading the comments, I realized that in my dataframe in my work also include strings, so the None were not coerced to numpy Nan. So the answer given by Pisdom works.
编辑：阅读评论后，我意识到在我的工作中的数据框中还包含字符串，因此 None 没有被强制为 numpy Nan。所以 Pisdom 给出的答案是有效的。
回答by Psidom
You could use applymapwith a lambdato check if an element is Noneas follows, (constructed a different example, as in your original one, Noneis coerced to np.nanbecause the data type is float, you will need an objecttype column to hold Noneas is, or as commented by @Evert, Noneand NaNare indistinguishable in numeric type columns):
你可以使用applymap一个lambda检查一个element is None如下，（构建不同的例子，在你原来的，None将强制使用np.nan，因为数据类型float，您将需要一个object类型列保持None原样，或由@Evert评论,None并且NaN在数字类型列中无法区分）：
df = pd.DataFrame([[None, 3], ["", np.nan]])
df
# 0 1
#0 None 3.0
#1 NaN
df.applymap(lambda x: x is None)
# 0 1
#0 True False
#1 False False
