to_dict doesn't convert np.int64 to python integers (second try)
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
import pandas as pd

data = [{'id': 11, 'text': 'Osv1wbZoL'},
        {'id': 0, 'text': 'KQpPReW3S9nZOS3'},
        {'id': 0, 'text': 'cbqLhjrb0B2Ah6E'},
        {'id': 3, 'text': 'qu1Jlnyba'},
        {'id': 14, 'text': 'aJUv5DBjbcGc3'},
        {'id': 12, 'text': 'Yobf9'},
        {'id': 4, 'text': 'awzZCV'},
        {'id': 4, 'text': '3NvBAVL'},
        {'id': 11, 'text': '80sPCxIf9s5wmEZ1'},
        {'id': 5, 'text': 'afrPD0X6mIzFK'}]
df = pd.DataFrame(data)

df.dtypes
id       int64
text    object
dtype: object
type(df[['id', 'text']].to_dict(orient='records')[0]['id'])
<class 'int'>
type(df[['id']].to_dict(orient='records')[0]['id'])
<class 'numpy.int64'>

```
#### Problem description

_Here I am just repeating here the description given my @Tomasz-Kluczkowski in #16048, which I believe is erroneously closed, because the issue still there in the latest stable version._

depending on the count of output columns, numpy integers getting converted to python integers
afterwards both json.dumps and ujson.dumps fails to encode

#13258 promises the solution for 0.21.0, but as seen above issue is still there in 0.23.4

Als workaround helps casting all types to strings bevor calling to_dict():

type(df[['id']].astype(object).to_dict(orient='records')[0]['id'])
<class 'int'>

Opening this as a new issue, because I cannot re-open the #16048.

#### Expected Output

```
type(df[['id']].to_dict(orient='records')[0]['id'])
<class 'int'>
```

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

<details>

```
pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.2.final.0
python-bits: 32
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.4
pytest: 4.1.1
pip: 18.1
setuptools: 40.6.3
Cython: None
numpy: 1.16.0
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: 1.2.16
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
```
</details>
