Select subset of rows of dataframe using multiple conditions

Question

I would like to select a subset of a dataframe that satisfies multiple conditions on multiple rows. I know I could this sequentially -- first selecting the subset that matches the first condition, then the portion of those that match the second, etc, but it seems like it should be able to be done in a single step. The following seems like it should work, but doesn't. Apparently it does work like this in other languages' implementations of DataFrame. Any thoughts?

using DataFrames
df = DataFrame()
df[:A]=[ 1, 3, 4, 7, 9]
df[:B]=[ "a", "c", "c", "D", "c"]
df[(df[:A].<5)&&(df[:B].=="c"),:] 

type: non-boolean (DataArray{Bool,1}) used in boolean context
while loading In[18], in expression starting on line 5

Answer 1

This is a Julia thing, not so much a DataFrame thing: you want & instead of &&. For example:

julia> [true, true] && [false, true]
ERROR: TypeError: non-boolean (Array{Bool,1}) used in boolean context

julia> [true, true] & [false, true]
2-element Array{Bool,1}:
 false
  true

julia> df[(df[:A].<5)&(df[:B].=="c"),:]
2x2 DataFrames.DataFrame
| Row | A | B   |
|-----|---|-----|
| 1   | 3 | "c" |
| 2   | 4 | "c" |

FWIW, this works the same way in pandas in Python:

>>> df[(df.A < 5) & (df.B == "c")]
   A  B
1  3  c
2  4  c

Answer 2

I have the same now as https://stackoverflow.com/users/5526072/jwimberley , occurring on my update to julia 0.6 from 0.5, and now using dataframes v 0.10.1.

Update: I made the following change to fix:

r[(r[:l] .== l) & (r[:w] .== w), :] # julia 0.5

r[.&(r[:l] .== l, r[:w] .== w), :] # julia 0.6

but this gets very slow with long chains (time taken \propto 2^chains) so maybe Query is the better way now:

# r is a dataframe
using Query
q1 = @from i in r begin
    @where i.l == l && i.w == w && i.nl == nl && i.lt == lt && 
    i.vz == vz && i.vw == vw && i.vδ == vδ && 
    i.ζx == ζx && i.ζy == ζy && i.ζδx == ζδx
    @select {absu=i.absu, i.dBU}
    @collect DataFrame
end

for example. This is fast. It's in the DataFrames documentation.