Python pandas remove last string/symbol from a column

Question

I have a large csv, with a column that contains numbers preceeding with a zero and ending with a .

It looks like ..

TC_NUM
0101.0001.
0101.0002.
0101.0003.

I want it to look like..

TC_NUM

    0101.0001
    0101.0002
    0101.0003

My code:

df3['TC_NUM'] = df3['TC_NUM'].astype(str).str[:-1]

and wrong output of my code..

TC_NUM
101.0001
101.0002
101.0003
101.0004
101.0005

Using edchums fix ..

df4 = pd.read_csv('output2.csv', dtype=object, index_col=0)
print df4.head()
df4['TC_NUM'] = df4['TC_NUM'].str[:-1]

It prints correctly..

0                 dialog_testcase_0101.0001_greeting.xml       0101.0001
1                 dialog_testcase_0101.0002_greeting.xml       0101.0002
2                 dialog_testcase_0101.0003_greeting.xml       0101.0003
3                 dialog_testcase_0101.0004_greeting.xml       0101.0004
4                 dialog_testcase_0101.0005_greeting.xml       0101.0005

but using this

df4['TC_NUM'] = df4['TC_NUM'].str[:-1]
print df4.head
df4.to_csv('output2.csv', dtype=object,index_col=0)

The resulting csv output is..

0   dialog_testcase_0101.0001_greeting.xml  101.0001
1   dialog_testcase_0101.0002_greeting.xml  101.0002
2   dialog_testcase_0101.0003_greeting.xml  101.0003
3   dialog_testcase_0101.0004_greeting.xml  101.0004

Hence missing the beginning 0

Answer 1

You need to read it in as a str then you can slice it:

In [11]:
t="""TC_NUM
0101.0001.
0101.0002.
0101.0003."""
df = pd.read_csv(io.StringIO(t), dtype=object)
df

Out[11]:
       TC_NUM
0  0101.0001.
1  0101.0002.
2  0101.0003.

In [13]:
df['TC_NUM'] = df['TC_NUM'].str[:-1]
df

Out[13]:
      TC_NUM
0  0101.0001
1  0101.0002
2  0101.0003

Answer 2

I eventually figured it out after much coding, and keyboard bashing. The code was correct as the output printed, but open office naturally removes the leading zeros from columns. Solution was to put the numbers in '' so open office would leave it intact. Thank you all for the help!