I am trying to read the content of number of csv files using pandas and load it in a pandas dataframe.

All the csv files consists of the header (1st row) which defines the columns names and then the numerical data. I am interested in reading the numerical data only and thus I am using the option skiprows=[0]. 

For instance:

```
path = 'mypath'
file = 'example1.csv'

```

where my example1.csv is something like:

```
time varA varB
1.0  2.3  3.2
2.0  4.2  3.4
...  ...  ...

```

And I then use this piece of code:

```
array_list = []

for file in os.listdir(path):
    df = pd.read_csv(file, skiprows=[0], header=None)
    array_list.append(df.as_matrix())

```

This works until I get a file, which consists of the header only (just one raw), without data, as in the example below, example2.cvs:

```
time varA varB

```

and I get the error

```
EmptyDataError: No columns to parse from file

```

Any suggestion about how to introduce the exception of a file which consists of just the header only, which does not mean it is empty?

Thank you so much for any help,

MarcoC