Code Sample, a copy-pastable example if possible

# Your code here
data = pd.DataFrame( {'ab' : ['A','B','A','A','B'], 'num' : ['01','02','01','01','01']})

a_replacements = { 'num' : { '01' : 'funny', '02' : 'serious' }}
b_replacements = { 'num' : { '01' : 'beginning', '02' : 'end' }}

data[data.ab == 'A'].replace(inplace=True, to_replace=a_replacements)

Problem description

The reason I have the mask (data.ab == 'A') is because there are two levels for A and two levels for B. If I were to run data.replace(inplace=True, to_replace=a_replacements, for rows where ab==B column num would be encoded as funny or serious instead of beginning or end.

Expected Output

My thought is that the last line of the above code block should result in a data frame that has all the 01's and 02's replaced for all rows that have 'ab' == 'A'. But this does not work. No exception is thrown. Not quite sure what I'm doing wrong.

Output of pd.show_versions()

# Paste the output here pd.show_versions() here ```INSTALLED VERSIONS ------------------ commit: None python: 3.6.0.final.0 python-bits: 64 OS: Darwin OS-release: 16.4.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 pandas: 0.19.2 nose: None pip: 9.0.1 setuptools: 27.2.0 Cython: None numpy: 1.12.0 scipy: None statsmodels: None xarray: None IPython: 5.3.0 sphinx: None patsy: None dateutil: 2.6.0 pytz: 2016.10 blosc: None bottleneck: None tables: None numexpr: None matplotlib: None openpyxl: 2.4.1 xlrd: 1.0.0 xlwt: None xlsxwriter: None lxml: None bs4: None html5lib: 0.999 httplib2: None apiclient: None sqlalchemy: None pymysql: None psycopg2: None jinja2: 2.9.5 boto: None pandas_datareader: None 
</details>


**Comment From: TomAugspurger**

Copy-pastable example:

```python

In [28]: data = pd.DataFrame({"num": ['01', '02']})

In [29]: data[[True, False]].replace({"num": {"01": "funny", "02": "begining"}}, inplace=True)
/Users/tom.augspurger/Envs/py3/lib/python3.6/site-packages/pandas/pandas/core/generic.py:3664: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  regex=regex)

In [30]: data[[True, True]].replace({"num": {"01": "funny", "02": "begining"}}, inplace=True)

In [31]: data
Out[31]:
  num
0  01
1  02
So I think `In[29]` shows why this isn't working for you. Your slice `data[data.ab == 'A']` may be a copy, and so your inplace replace is operating on a copy, not the original, so it looks like it's not working. The potential bug here is why an all-True mask didn't raise the SettingWithCopy warning. As you can see, you're probably better off not using `inplace`. **Comment From: jreback** This is not a correct usage. As indicated by the error message it *might* work, but is not idiomatic. 
In [4]: data[data.ab == 'A'].replace(inplace=True, to_replace=a_replacements)
/Users/jreback/pandas/pandas/core/generic.py:3664: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  regex=regex)
Instead use this pattern. The rhs is aligned to the lhs. This is the what pandas does for you by default. (you can also use ``.loc[data.ab=='A'].replace(...)`` on the rhs if its more clear. 
In [14]: data.loc[data.ab=='A'] = data.replace(to_replace=a_replacements)

In [15]: data
Out[15]: 
  ab    num
0  A  funny
1  B     02
2  A  funny
3  A  funny
4  B     01
**Comment From: alokshenoy** Thanks for the solution. It works well when I'm trying to replace values in ```num``` for each case ```ab == 'A', ab=='B'``` Let's say I have 26 cases (```ab=='C'....ab=='Z'```) and I'm trying to use a for loop to iterate through those cases, I get a TypeError ```TypeError: cannot replace ['a_replacements'] with method pad on a DataFrame``` code: 
for letter in data.ab.unique():
    data.loc[data.ab == letter] = data.replace(to_replace=letter+"_replacements")
To which I get : 
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-96-acd3197ceef4> in <module>()
      1 for letter in data.ab.unique():
      2     print(letter.lower()+"_replacements")
----> 3     data.loc[data.ab == letter] = data.replace(to_replace=letter.lower()+"_replacements")

/Users/alokshenoy/.pyenv/versions/miniconda3-latest/lib/python3.6/site-packages/pandas/core/generic.py in replace(self, to_replace, value, inplace, limit, regex, method, axis)
   3427             if isinstance(to_replace, (tuple, list)):
   3428                 return _single_replace(self, to_replace, method, inplace,
-> 3429                                        limit)
   3430 
   3431             if not is_dict_like(to_replace):

/Users/alokshenoy/.pyenv/versions/miniconda3-latest/lib/python3.6/site-packages/pandas/core/generic.py in _single_replace(self, to_replace, method, inplace, limit)
     70     if self.ndim != 1:
     71         raise TypeError('cannot replace {0} with method {1} on a {2}'
---> 72                         .format(to_replace, method, type(self).__name__))
     73 
     74     orig_dtype = self.dtype

TypeError: cannot replace ['a_replacements'] with method pad on a DataFrame
Also tried the rhs = lhs way, and that throws the same error. Curious as to what changes once inside the for loop? **Comment From: jreback** @alokshenoy you should ask on Stack Overflow