[Python] removing particular rows from DataFrame in pandas

I have a large .txt with data in bad formats. I would like to remove some rows and convert rest of data to float numbers. I would like to remove rows with 'X' or 'XX', The rest I should convert to float, number like 4;00.1 should be converted to 4.001 The file looks like this sample:

0,1,10/09/2012,3:01,4;09.1,5,6,7,8,9,10,11
1,-0.581586,11/09/2012,-1:93,0;20.3,739705,,0.892921,5,,6,7
2,XX,10/09/2012,3:04,4;76.0,0.183095,-0.057214,-0.504856,NaN,0.183095,12
3,-0.256051,10/09/2012,9:65,1;54.9,483293,0.504967,0.074442,-1.716287,7,0.504967,0.504967
4,-0.728092,11/09/2012,0:78,1;53.4,232247,4.556,0.328062,1.382914,NaN,4.556,4
5,4,11/09/2012,NaN,NaN,6.0008,NaN,NaN,NaN,6.000800,6.000000,6.000800
6,X,11/09/2012,X,X,5,X,8,2,1,17.000000,33.000000
7,,11/09/2012,,,,,,6.000000,5.000000,2.000000,2.000000
8,4,11/09/2012,7:98,3;04.5,5,6,3,7.000000,3.000000,3.000000,2
9,6,11/09/2012,2:21,4;67.2,5,2,2,7,3,8.000000,4.000000


I read it to DataFrame and choose rows

from pandas import *
from csv import *
fileName = '~/data.txt'
colName = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l']
df = DataFrame(read_csv(fileName, names=colName))
print df[df['b'].isin(['X','XX',None,'NaN'])].to_string()


An output from last last line gives me only:

>>> print df[df['b'].isin(['X','XX',None,'NaN'])].to_string()
b c d e f g h i j k l
a
2 XX 10/09/2012 3:04 4;76.0 0.183095 -0.057214 -0.504856 NaN 0.183095 12 NaN
6 X 11/09/2012 X X 5.000000 X 8.000000 2 1.000000 17 33


Does not pick up row 7, and I would like to go through all df not only one column (original file is very large).

At the moment for conversion I use as below, but need remove unwanted rows first to apply it to all df.

convert1 = lambda x : x.replace('.', '')
convert2 = lambda x : float(x.replace(';', '.'))
newNumber = convert2(convert1(df['e'][0]))


After choosing rows I would like to remove them from df, I try df.pop() but it works only for column not for rows. I try to name rows but don't luck. In this particular .txt I should finish with a new df from rows [0,3,8,9] with column 'c' as a date format, 'd' as a time format and the rest as the float. I try to figure it out for quite a while now, but do not know where to move, is it possible in pandas (probably should be) or do I need to change to ndarray or anything else? Thanks for your advise

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