List index out of range with Panda read_csv
<p>I'm trying to read large data (thousands of rows) through a python script from csv files which look like this: </p>

<pre><code>.....
2015-11-03 20:16:28,000;63,62;
2015-11-03 20:16:29,000;63,75;
2015-11-03 20:16:30,000;63,86;
2015-11-03 20:16:31,000;64,25;
</code></pre>

<p>but it appears that one of the files has extra empty rows that have 196541465 blank spaces — then the code crashes when reading it with read_csv of pandas lib.</p>

<pre><code>     File "/usr/lib/python2.7/dist-packages/pandas/core/frame.py", line 4221, in append
        elif isinstance(other, list) and not isinstance(other[0], DataFrame):
IndexError: list index out of range
</code></pre>

<p>I'm using the folowing command: </p>

<pre><code>data = pd.read_csv(input_file,skiprows = [0],usecols=[0,1,2],delimiter=';',decimal=',', names = [ 'date','angle','Unnamed'],na_filter = False,parse_dates = [0],date_parser = reformat_date,error_bad_lines = False,skip_blank_lines=True)#,nrows = 8191)
</code></pre>

<p>the culprit row is the 8192'th, when limiting rows (by <code>rows = 8191</code>) it works just fine. I've tried many options from the doc but it doesn't seem to work! Any idea?</p>