BUG: read_csv() encoding latin1 gives KeyError on 1st column in new version 1.0.3
- [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
#data = pd.read_csv("dataset.csv", encoding="latin1").fillna(method="ffill")
data = pd.DataFrame({'Sentence #': ['Sentence 1','',''],
                   'Word': ['Thousands','of','demonstrators'],
                   'POS': ['NNS', 'IN', 'NNS']}) # this should be in the csv file to reproduce the error
gk = data.groupby('Sentence #')
print(gk.first())

```

#### Problem description
read_csv() encoding 'latin1' gives KeyError on 1st column in new version 1.0.3
This works perfectly in old version 0.25.3 but gives KeyError when run in new version 1.0.3
Works correctly when changed to 'utf-8'

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]

#### Expected Output
                 Word  POS
Sentence #
Sentence 1  Thousands  NNS

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : AMD64 Family 22 Model 48 Stepping 1, AuthenticAMD
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 0.25.3
numpy            : 1.17.0
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 19.3.1
setuptools       : 40.8.0
Cython           : 0.29.13
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.9.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-76-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 9.0.1
setuptools       : 39.0.1
Cython           : 0.29.14
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None

pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
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

[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]

</details>
