英文:
How to calculate median while ignoring negative values?
问题
我有以下的数据框：
y-1-123210
我需要应用一个窗口大小为3的滚动窗口，并计算中位数，同时忽略负值（例如 -1）。我应该如何做？
这是我尝试过的方法：
window = 3y.rolling(window)[y >= 0].apply(lambda x: np.median(x)).dropna()
英文:
I have the following dataframe:
y-1-123210
I need to apply a rolling window of 3 and calculate a median, while ignoring negative (e.g. -1) values. How can I do so?
This is what I tried:
window = 3y.rolling(window)[y>=0].apply(lambda x: np.median(x)).dropna()
答案1
得分: 1
在lambda函数中筛选或在之前筛选，但输出不同
window = 3df['new1'] = df.y.rolling(window).apply(lambda x: np.median([x >= 0]), raw=False)df['new2'] = df.loc[df.y >= 0, 'y'].rolling(3).median()print(df)y new1 new20 -1 NaN NaN1 -1 NaN NaN2 2 0.0 NaN3 3 1.0 NaN4 -2 1.0 NaN5 -1 0.0 NaN6 0 0.0 2.0
英文:
Filter in lambda function or filter before, but output is different
window = 3df['new1'] = df.y.rolling(window).apply(lambda x: np.median([x>=0]), raw=False)df['new2'] = df.loc[df.y>=0, 'y'].rolling(3).median()print (df)y new1 new20 -1 NaN NaN1 -1 NaN NaN2 2 0.0 NaN3 3 1.0 NaN4 -2 1.0 NaN5 -1 0.0 NaN6 0 0.0 2.0
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