pandas - Python perform operation in string -

so i'm trying pass variable operation (user defined) function , having trouble trying find way of doing it. can think of hard code options function following:

def dothings(conditions): import re import pandas pd d = {'time' : pd.series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),      'legnth' : pd.series([4., 5., 6., 7.], index=['a', 'b', 'c', 'd'])} df = pd.dataframe(d) print df  condition in conditions:     # split condition 2 parts     splitcondition = re.split('<=|>=|!=|<|>|=',condition)      # if right side of conditional statement number convert float     if splitcondition[1].isdigit():         splitcondition[1] = float(splitcondition[1])      # perform condition specified     if "<=" in condition:         df = df[df[splitcondition[0]]<=splitcondition[1]]         print "one"     elif ">=" in condition:         df = df[df[splitcondition[0]]>=splitcondition[1]]         print "two"     elif "!=" in condition:         df = df[df[splitcondition[0]]!=splitcondition[1]]         print "three"     elif "<" in condition:         df = df[df[splitcondition[0]]<=splitcondition[1]]         print "four"     elif ">" in condition:         df = df[df[splitcondition[0]]>=splitcondition[1]]         print "five"     elif "=" in condition:         df = df[df[splitcondition[0]]==splitcondition[1]]         print "six" return df  # specify conditions conditions = ["time>2","legnth<=6"] df = dothings(conditions)   # call function  print df 

which results in this:

   legnth  time       4     1 b       5     2 c       6     3 d       7     4 5 1    legnth  time c       6     3 

this , , everything, i'm wondering if there better or more efficient way of passing conditions functions without writing if statements possible out. ideas?

solution:

def dothings(conditions):     import re     import pandas pd     d = {'time' : pd.series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd']),          'legnth' : pd.series([4., 5., 6., 7.], index=['a', 'b', 'c', 'd'])}     df = pd.dataframe(d)     print df      condition in conditions:         # split condition 2 parts         splitcondition = re.split('<=|>=|!=|<|>|=',condition)          # if right side of conditional statement number convert float         if splitcondition[1].isdigit():             splitcondition[1] = float(splitcondition[1])          import operator         ops = {'<=': operator.le, '>=': operator.ge, '!=': operator.ne, '<': operator.lt, '>': operator.gt, '=': operator.eq}         cond = re.findall(r'<=|>=|!=|<|>|=', condition)         df = df[ops[cond[0]](df[splitcondition[0]],splitcondition[1])]      return df    # specify conditions conditions = ["time>2","legnth<=6"] df = dothings(conditions)   # call function  print df 

output:

   legnth  time       4     1 b       5     2 c       6     3 d       7     4    legnth  time c       6     3 

you can access built-in operators via operator module, , build table mapping operator names built-in ones, in cut-down example:

import operator ops = {'<=': operator.le, '>=': operator.ge}  in [3]: ops['>='](2, 1) out[3]: true