pandas 在熊猫数据框中随机插入 NA 的值
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Randomly insert NA's values in a pandas dataframe
提问by mitsi
How can I randomly insert np.nan's in a DataFrame ?
Let's say I want 10% null values inside my DataFrame.
如何np.nan在 DataFrame 中随机插入's ？假设我希望 DataFrame 中有 10% 的空值。
My data looks like this :
我的数据如下所示：
df = pd.DataFrame(np.random.randn(5, 3),
index=['a', 'b', 'c', 'd', 'e'],
columns=['one', 'two', 'three'])
one two three
a 0.695132 1.044791 -1.059536
b -1.075105 0.825776 1.899795
c -0.678980 0.051959 -0.691405
d -0.182928 1.455268 -1.032353
e 0.205094 0.714192 -0.938242
Is there an easy way to insert the null values?
有没有一种简单的方法来插入空值？
回答by Kodiologist
Here's a way to clear exactly 10% of cells (or rather, as close to 10% as can be achieved with the existing data frame's size).
这是一种精确清除 10% 的单元格的方法（或者更确切地说，使用现有数据框的大小可以达到的接近 10%）。
import random
ix = [(row, col) for row in range(df.shape[0]) for col in range(df.shape[1])]
for row, col in random.sample(ix, int(round(.1*len(ix)))):
df.iat[row, col] = np.nan
Here's a way to clear cells independently with a per-cell probability of 10%.
这是一种独立清除单元格的方法，每个单元格的概率为 10%。
df = df.mask(np.random.random(df.shape) < .1)
回答by Jaroslav Bezděk
I think you can easily iterate over data frame columns and assign NaNvalue to every cell produced by pandas.DataFrame.sample()method.
我认为您可以轻松地遍历数据框列并将NaN值分配给pandas.DataFrame.sample()方法生成的每个单元格。
The code is following.
代码如下。
for col in df.columns:
df.loc[df.sample(frac=0.1).index, col] = pd.np.nan
