BUG: TypeError: object of type 'int' has no len() when saving DataFrame with object dtype column
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd

df = pd.DataFrame({"a": [None, None]})
df.loc[0, "a"] = float(1)
df.loc[1, "a"] = float(2)

hdf = pd.HDFStore("test.h5", write_mode="w")
hdf.put("table", df, format="table")
```

This causes following error:
```
  ...
  File "/opt/venv/lib64/python3.6/site-packages/pandas/io/pytables.py", line 1042, in put
    errors=errors,
  File "/opt/venv/lib64/python3.6/site-packages/pandas/io/pytables.py", line 1709, in _write_to_group
    data_columns=data_columns,
  File "/opt/venv/lib64/python3.6/site-packages/pandas/io/pytables.py", line 4143, in write
    data_columns=data_columns,
  File "/opt/venv/lib64/python3.6/site-packages/pandas/io/pytables.py", line 3813, in _create_axes
    errors=self.errors,
  File "/opt/venv/lib64/python3.6/site-packages/pandas/io/pytables.py", line 4800, in _maybe_convert_for_string_atom
    for i in range(len(block.shape[0])):
TypeError: object of type 'int' has no len()
```

#### Problem description

After initial creation of DataFrame the dtype is of `object` dtype. After putting float in the `a` column I would expect that the dtype of the `a` column will change to `float64` dtype, but it remains `object` dtype. The problem is that the type of `df.loc[0, "a"]` is `float` during saving the DataFrame, which causes the problem pasted above.

#### Expected Output

I would expect one of the following:

- Implicit conversion of the column to `float` dtype
- Conversion during `hdf.put()`
- Proper exception saying that I am saving mixed typed column

There's a pretty big chance that I am wrong and this is expected behaviour. If that's the case, please, can you explain me why, or point me to somewhere, so that I can read something about it?

Maybe it's linked with this issue #34274

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

<details>

commit           : None
python           : 3.6.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.18.0-147.5.1.el8_1.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.4
numpy            : 1.16.4
pytz             : 2018.7
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 46.4.0
Cython           : 0.29.2
pytest           : 5.1.2
hypothesis       : None
sphinx           : 1.8.4
blosc            : None
feather          : None
xlsxwriter       : 1.1.2
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.9.0
pandas_datareader: None
bs4              : 4.8.0
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 2.0.0
numexpr          : 2.6.8
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.1.2
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : 1.1.2
numba            : None

</details>
