Pandas best way to subset a dataframe inplace, using a mask

问题

I have a pandas dataset that I want to downsize (remove all values under x).

The mask is df[my_column] > 50

I would typically just use df = df[mask], but want to avoid making a copy every time, particularly because it gets error prone when used in functions (as it only gets altered in the function scope).

What is the best way to subset a dataset inplace?

I was thinking of something along the lines of
df.drop(df.loc[mask].index, inplace = True)

Is there a better way to do this, or any situation where this won't work at all?

回答1:

You are missing the inplace parameter :

df.drop(df[df.my_column < 50].index, inplace = True)

回答2:

I think this works. Maybe there are better ways?

df = df.drop(df[df.my_column < 50].index)

来源：https://stackoverflow.com/questions/33103988/pandas-best-way-to-subset-a-dataframe-inplace-using-a-mask