Python Pandas 查找所有值为 NaN 的所有行
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Python Pandas find all rows where all values are NaN
提问by Steven Setteducati Jr.
So I have a dataframe with 5 columns. I would like to pull the indices where all of the columns are NaN. I was using this code:
所以我有一个包含 5 列的数据框。我想提取所有列都是 NaN 的索引。我正在使用此代码：
nan = pd.isnull(df.all)
but that is just returning false because it is logically saying no not all values in the dataframe are null. There are thousands of entries so I would prefer to not have to loop through and check each entry. Thanks!
但这只是返回 false，因为从逻辑上讲，并非数据帧中的所有值都为空。有数千个条目，所以我宁愿不必循环检查每个条目。谢谢！
采纳答案by piRSquared
It should just be:
它应该只是：
df.isnull().all(1)
The indexcan be accessed like:
将index可以访问，如：
df.index[df.isnull().all(1)]
Demonstration
示范
np.random.seed([3,1415])
df = pd.DataFrame(np.random.choice((1, np.nan), (10, 2)))
df
idx = df.index[df.isnull().all(1)]
nans = df.ix[idx]
nans
Timing
定时
code
代码
np.random.seed([3,1415])
df = pd.DataFrame(np.random.choice((1, np.nan), (10000, 5)))
回答by Alexander
Assuming your dataframe is named df, you can use boolean indexing to check if all columns (axis=1) are null. Then take the index of the result.
假设您的数据框名为df，您可以使用布尔索引来检查所有列 ( axis=1) 是否为空。然后取结果的索引。
np.random.seed(0)
df = pd.DataFrame(np.random.randn(5, 3))
df.iloc[-2:, :] = np.nan
>>> df
0 1 2
0 1.764052 0.400157 0.978738
1 2.240893 1.867558 -0.977278
2 0.950088 -0.151357 -0.103219
3 NaN NaN NaN
4 NaN NaN NaN
nan = df[df.isnull().all(axis=1)].index
>>> nan
Int64Index([3, 4], dtype='int64')
回答by user357269
From the master himself: https://stackoverflow.com/a/14033137/6664393
来自大师本人：https: //stackoverflow.com/a/14033137/6664393
nans = pd.isnull(df).all(1).nonzero()[0]
