python - Pandas Select DataFrame columns using boolean

Question

I want to use a boolean to select the columns with more than 4000 entries from a dataframe comb which has over 1,000 columns. This expression gives me a Boolean (True/False) result:

criteria = comb.ix[:,'c_0327':].count()>4000

I want to use it to select only the True columns to a new Dataframe.
The following just gives me "Unalignable boolean Series key provided":

comb.loc[criteria,]

I also tried:

comb.ix[:, comb.ix[:,'c_0327':].count()>4000] 

Similar to this question answer dataframe boolean selection along columns instead of row but that gives me the same error: "Unalignable boolean Series key provided"

comb.ix[:,'c_0327':].count()>4000

yields:

c_0327    False
c_0328    False
c_0329    False
c_0330    False
c_0331    False
c_0332    False
c_0333    False
c_0334    False
c_0335    False
c_0336    False
c_0337     True
c_0338    False
.....

Answer 1

What is returned is a Series with the column names as the index and the boolean values as the row values.

I think actually you want:

this should now work:

comb[criteria.index[criteria]]

Basically this uses the index values from criteria and the boolean values to mask them, this will return an array of column names, we can use this to select the columns of interest from the orig df.