How to deal with SettingWithCopyWarning in Pandas

I just upgraded my Pandas from 0.11 to 0.13.0rc1. Now, the application is popping out many new warnings. One of them like this:
E:\FinReporter\FM_EXT.py:449: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_index,col_indexer] = value instead
quote_df['TVol'] = quote_df['TVol']/TVOL_SCALE


What exactly does it mean? Do I need to change something?

How should I suspend the warning if I insist on using quote_df['TVol'] = quote_df['TVol']/TVOL_SCALE?
The function that gives warnings

def _decode_stock_quote(list_of_150_stk_str):
    """decode the webpage and return dataframe"""

    from cStringIO import StringIO

    str_of_all = "".join(list_of_150_stk_str)

    quote_df = pd.read_csv(
        StringIO(str_of_all),
        sep=',',
        names=list('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefg')) 
        #dtype={'A': object, 'B': object, 'C': np.float64}
    quote_df.rename(
        columns={
            'A':'STK', 'B':'TOpen', 'C':'TPCLOSE', 'D':'TPrice',
            'E':'THigh', 'F':'TLow', 'I':'TVol', 'J':'TAmt',
            'e':'TDate', 'f':'TTime'},
        inplace=True)
    quote_df = quote_df.ix[:,[0,3,2,1,4,5,8,9,30,31]]
    quote_df['TClose'] = quote_df['TPrice']
    quote_df['RT']     = 100 * (quote_df['TPrice']/quote_df['TPCLOSE'] - 1)
    quote_df['TVol']   = quote_df['TVol']/TVOL_SCALE
    quote_df['TAmt']   = quote_df['TAmt']/TAMT_SCALE
    quote_df['STK_ID'] = quote_df['STK'].str.slice(13,19)
    quote_df['STK_Name'] = quote_df['STK'].str.slice(21,30)#.decode('gb2312')
    quote_df['TDate']  = quote_df.TDate.map(lambda x: x[0:4]+x[5:7]+x[8:10])
    
    return quote_df

More warning messages
`E:\FinReporter\FM_EXT.py:449: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_index,col_indexer] = value instead
quote_df['TVol'] = quote_df['TVol']/TVOL_SCALE
E:\FinReporter\FM_EXT.py:450: SettingWithCopyWarning: A value is try

The SettingWithCopyWarning was created to flag potentially confusing "chained" assignments, such as the following, which does not always work as expected, particularly when the first selection returns a copy. [see GH5390 and GH5597 for background discussion.]

df[df['A'] > 2]['B'] = new_val  # new_val not set in df

The warning offers a suggestion to rewrite as follows:

df.loc[df['A'] > 2, 'B'] = new_val

However, this doesn't fit your usage, which is equivalent to:

df = df[df['A'] > 2]
df['B'] = new_val

While it's clear that you don't care about writes making it back to the original frame (since you are overwriting the reference to it), unfortunately this pattern cannot be differentiated from the first chained assignment example. Hence the (false positive) warning. The potential for false positives is addressed in the docs on indexing, if you'd like to read further. You can safely disable this new warning with the following assignment.

import pandas as pd
pd.options.mode.chained_assignment = None  # default='warn'

Other Resources

• pandas User Guide: Indexing and selecting data

• Python Data Science Handbook: Data Indexing and Selection

• Real Python: SettingWithCopyWarning in Pandas: Views vs Copies

• Dataquest: SettingwithCopyWarning: How to Fix This Warning in Pandas

• Towards Data Science: Explaining the SettingWithCopyWarning in pandas

Stack Overflow Q#20625582, score: 1730