Compare dataframe columns to series

Question

I have a dataframe and a series, and want to compare the DF column-wise to series.

Dataframe (df) looks like:

1   1 4 7
2   2 3 1
3   2 3 9

Series (s) looks like:

1   3
2   4 
3   2

Want to conduct a boolean comparison (where columns values less than series values):

1   T F F
2   T T T
3   F F F

Of course I could do a loop, but there should be simpler ways to do that?

Answer 1

Use lt, and you can specify an axis.

df.lt(s, axis=0)

       1      2      3                   
1   True  False  False
2   True   True   True
3  False  False  False

The axis is 1 by default, and using the overloaded operator < doesn't give you as much flexibility that way. As DYZ mentioned in a comment, having the axis default to 1 here is an exception, because it usually defaults to 0 (in other functions such as apply and transform).

---

If the series and dataframe indexes don't align nicely, you can still get around that by comparing s.values instead.

df.lt(s.values, axis=0)

       1      2      3                   
1   True  False  False
2   True   True   True
3  False  False  False

Answer 2

(df.T<s).T
#       0      1      2
#0   True  False  False
#1   True   True   True
#2  False  False  False

Answer 3

Using [:,None], convert you serise

df.values<s.values[:,None]
Out[513]: 
array([[ True, False, False],
       [ True,  True,  True],
       [False, False, False]])