I am working with pandas df and I am trying to make all the numbers that are outside of range set as null, but having trouble
df['Numbers'] = df['Numbers'].mask((df['Numbers']< -10) & (df['Numbers']> 10), inplace=True)
So I want to keep the numbers between -10 and 10, if the numbers are outside of those two numbers, it should be set as null.
What am I doing wrong here?
One thing that immediately strikes out at me is that you're using & with your two conditions, so you're basically trying to select all numbers that are both less than -10 and greater than 10...which isn't gonna work ;)
I'd rewrite your code like this:
df.loc[df['Numbers'].lt(-10) | df['Numbers'].gt(10), 'Numbers'] = np.nan
.lt() instead of <?.eq, .ne, .lt, .gt etc., instead of their corresponding Python operators, because you don't have to wrap the conditions using them in parentheses when you're joining them with & or |. I.e., you can say df[a.eq(b) | x.eq(y)] instead of df[(a == b) | (x == y)]. Now, in that little example, the latter does look more readable, but the former I prefer in larger settings where there are more complex and more complex conditions.I would do it like this:
df['Numbers'] = df['Numbers'].where((df['Numbers']>-10) & (df['Numbers']<10))
df.loc[~df['Numbers'].between(-10, 10), 'Numbers'] = np.nanlike this answer