pandas.read_csv outputs two data frames in Jupiter Notebook 
### My code:

First cell:
```python
import pandas as pd
test = pd.read_csv("dump.csv")
```

Second cell:
```python
test
```

Output:
<img width="1114" alt="Screenshot 2020-05-04 at 13 42 52" src="https://user-images.githubusercontent.com/10774221/80962334-284bd980-8e0d-11ea-9d3e-456a112770d4.png">

and 

```python
type(test)
```

Output: 
<img width="1113" alt="Screenshot 2020-05-04 at 13 43 45" src="https://user-images.githubusercontent.com/10774221/80962402-47e30200-8e0d-11ea-9a56-4bf387b37257.png">

It seems like the command imports two dataframes but only in Jupyter Notebook.

I tested it in Spyder and there everything works fine.

### Setup:

The file I am reading: [sp500.csv.zip](https://github.com/pandas-dev/pandas/files/4574412/sp500.csv.zip)


```python
pd.show_versions()
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.4.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200330
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.0.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.4.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200330
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.0.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
```