pandas.DataFrame.replace seems taking number string as integer and run into overflow error
#### Code Sample

```python
import pandas as pd

x = {'user_id':['100000715097692381911', 
                '100003840837471130074'], 
     'item_id': [1, 2]
     }
dfx = pd.DataFrame(x)
dfx['user_id'].replace(
    {
     '100000715097692381911': 0, 
     '100003840837471130074': 1
     }, inplace=True)
```
#### Problem description
I got overflow error:

File "/home/grain/ml/lib/python3.6/site-packages/pandas/core/dtypes/cast.py", line 683, in astype_nansafe
    return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
  File "pandas/_libs/lib.pyx", line 546, in pandas._libs.lib.astype_intsafe
OverflowError: Python int too large to convert to C long

*This error occurs on my laptop with pandas 0.24.1, python 3.6.7. The example code can handle the replacement correctly on another computer with an older version pandas 0.20.3.*

#### Expected Output

Since I loaded big id numbers like '100000715097692381911' as string type, the pandas.DataFrame.replace() method should replace it with the corresponding value in the dictionary. But I got overflow error. It seemed pandas took the id string as integer?

And if I modify just the first element of 'user_id' column to 's100000715097692381911', then the code won't run into overflow.

#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-46-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.1
pytest: None
pip: 19.0.3
setuptools: 40.6.3
Cython: None
numpy: 1.16.0
scipy: 1.2.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
