pandas unable to read from large StringIO object
cstringio, csv, pandas, python, stringio
Solution
There are two issues here, one fundamental and one you simply haven't come across yet. :^)
First, after you write to `c`, you're at the end of the (virtual) file. You need to `seek` back to the start. We'll use a smaller grid as an example:
>>> a = np.random.randint(0,256,(10,10)).astype('uint8')
>>> b = pd.DataFrame(a)
>>> c = StringIO()
>>> b.to_csv(c, delimiter=' ', header=False, index=False)
>>> next(c)
Traceback (most recent call last):
File "<ipython-input-57-73b012f9653f>", line 1, in <module>
next(c)
StopIteration
which generates the "no columns" error. If we `seek` first, though:
>>> c.seek(0)
>>> next(c)
'103,3,171,239,150,35,224,190,225,57\n'
But now you'll notice the second issue-- commas? I thought we requested space delimiters? But `to_csv` only accepts `sep`, not `delimiter`. Seems to me it should either accept it or object that it doesn't, but silently ignoring it feels like a bug. Anyway, if we use `sep` (or `delim_whitespace=True`):
>>> a = np.random.randint(0,256,(10,10)).astype('uint8')
>>> b = pd.DataFrame(a)
>>> c = StringIO()
>>> b.to_csv(c, sep=' ', header=False, index=False)
>>> c.seek(0)
>>> d = pd.read_csv(c, sep=' ', header=None, dtype='uint8')
>>> d
0 1 2 3 4 5 6 7 8 9
0 209 65 218 242 178 213 187 63 137 145
1 161 222 50 92 157 31 49 62 218 30
2 182 255 146 249 115 91 160 53 200 252
3 192 116 87 85 164 46 192 228 104 113
4 89 137 142 188 183 199 106 128 110 1
5 208 140 116 50 66 208 116 72 158 169
6 50 221 82 235 16 31 222 9 95 111
7 88 36 204 96 186 205 210 223 22 235
8 136 221 98 191 31 174 83 208 226 150
9 62 93 168 181 26 128 116 92 68 153
Problem
I'm using pandas to manage a large array of 8-byte integers. These integers are included as space-delimited elements of a column in a comma-delimited CSV file, and the array size is about 10000x10000. Pandas is able to quickly read the comma-delimited data from the first few columns as a DataFrame, and also quickly store the space-delimited strings in another DataFrame with minimal hassle. The trouble comes when I try to cast transform the table from a single column of space-delimited strings to a DataFrame of 8-bit integers. I have tried the following: ``` intdata = pd.DataFrame(strdata.columnname.str.split().tolist(), dtype='uint8') ``` But the memory usage is unbearable - 10MB worth of integers consumes 2GB of memory. I'm told that it's a limitation of the language and there's nothing I can do about it in this case. As a possible workaround, I was advised to save the string data to a CSV file and then reload the CSV file as a DataFrame of space-delimited integers. This works well, but to avoid the slowdown that comes from writing to disk, I tried writing to a StringIO object. Here's a minimal non-working example: ``` import numpy as np import pandas as pd from cStringIO import StringIO a = np.random.randint(0,256,(10000,10000)).astype('uint8') b = pd.DataFrame(a) c = StringIO() b.to_csv(c, delimiter=' ', header=False, index=False) d = pd.io.parsers.read_csv(c, delimiter=' ', header=None, dtype='uint8') ``` Which yields the following error message: ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/lib64/python2.7/site-packages/pandas/io/parsers.py", line 443, in parser_f return _read(filepath_or_buffer, kwds) File "/usr/lib64/python2.7/site-packages/pandas/io/parsers.py", line 228, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "/usr/lib64/python2.7/site-packages/pandas/io/parsers.py", line 533, in __init__ self._make_engine(self.engine) File "/usr/lib64/python2.7/site-packages/pandas/io/parsers.py", line 670, in _make_engine self._engine = CParserWrapper(self.f, **self.options) File "/usr/lib64/python2.7/site-packages/pandas/io/parsers.py", line 1032, in __init__ self._reader = _parser.TextReader(src, **kwds) File "parser.pyx", line 486, in pandas.parser.TextReader.__cinit__ (pandas/parser.c:4494) ValueError: No columns to parse from file ``` Which is puzzling, because if I run the exact same code with `'c.csv'` instead of `c`, the code works perfectly. Also, if I use the following snippet: ``` file = open('c.csv', 'w') file.write(c.getvalue()) ``` The CSV file gets saved without any problems, so writing to the StringIO object is not the issue. It is possible that I need to replace `c` with `c.getvalue()` in the read_csv line, but when I do that, the interpreter tries to print the contents of `c` in the terminal! Surely there is a way to work around this. Thanks in advance for the help.