从 Pandas 数据框中选择指定列不全为 NaN 的行 [英] Select rows from pandas data frame where specified columns are not all NaN

问题描述

我有一个 Pandas DataFrame 对象 data 列 'a', 'b', 'c', ..., 'z'

I have a Pandas DataFrame object data with columns 'a', 'b', 'c', ..., 'z'

我想选择满足以下条件的所有行:'b'、'c'、'g'列中的数据不是 NaN 同时.我试过了:

I want to select all rows which satisfy the following condition: data in columns 'b', 'c', 'g' is not NaN simultaneously. I tried:

new_data = data[not all(np.isnan(value) for value in data[['b', 'c', 'g']])]

但它不起作用 - 引发错误:

but it didn't work - throws an error:

Traceback (most recent call last):
  File "<input>", line 1, in <module>`
  File "<input>", line 1, in <genexpr>
 TypeError: Not implemented for this type

推荐答案

我想选择满足以下条件的所有行:列 'b'、'c'、'g' 中的数据不是 NaN同时.

然后就可以使用dropna:

new_data = data.dropna(how='all', subset=['b', 'c', 'g'])

使用参数:

how : {'any', 'all'}
    * any : if any NA values are present, drop that label
    * all : if all values are NA, drop that label
subset : array-like
    Labels along other axis to consider, e.g. if you are dropping rows
    these would be a list of columns to include

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