read_csv() issue for CSV files with mimetype application/vnd.ms-excel
I use `pandas.read_csv()` to read an URL of an uploaded CSV file. 

However, sometimes it caused an issue that `read_csv()` returns an empty DataFrame with NaN. 

I think it caused by the mime type of the CSV `application/vnd.ms-excel`, because all CSVs with mimetype `text/csv` doesn't have any issue.

Is that a known issue? 

I found this [post](https://stackoverflow.com/questions/47965296/python-pandas-read-csv-giving-nans-for-file-but-not-for-content) that seems like the same issue.

Is this `read_csv()`'s issue? Or something else?

The traceback:

```
Traceback (most recent call last):
  File "/env/local/lib/python2.7/site-packages/flask/app.py", line 1982, in wsgi_app
    response = self.full_dispatch_request()
  File "/env/local/lib/python2.7/site-packages/flask/app.py", line 1614, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/env/local/lib/python2.7/site-packages/flask/app.py", line 1517, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "/env/local/lib/python2.7/site-packages/flask/app.py", line 1612, in full_dispatch_request
    rv = self.dispatch_request()
  File "/env/local/lib/python2.7/site-packages/flask/app.py", line 1598, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "/home/vmagent/app/main.py", line 144, in visualize_file
    df = process(df)
  File "/home/vmagent/app/main.py", line 122, in process
    result = foo(df)
  File "/home/vmagent/app/main.py", line 85, in foo
    len_ts = int(np.array(data)[:, 0].max())
ValueError: cannot convert float NaN to integer
```

And the code:

```
@app.route('/upload', methods=['GET', 'POST'])
def upload_file():
    # Upload file to Google Cloud Storage
    ......

import numpy as np
def foo(data):    
    len_ts = int(np.array(data)[:, 0].max())
    ......
    return df

def process(df):
    df = np.array(df)
    ......
    df = foo(df)
    return bar(df)

@app.route('/graph/<filename>')
def visualize_file(filename):
    import pandas as pd
    df = pd.read_csv('https://storage.cloud.google.com/project-name/' + filename + '.csv'))
    df = process(df)
    df = pd.DataFrame(df, columns=['col1', 'data1', 'data2'])
    chart_data = df.to_dict(orient='records')
    chart_data = json.dumps(chart_data, indent=2)
    data = {'chart_data': chart_data}
    return render_template("graph.html", data=data)
```