Miki Tebeka wrote:
> Greetings,
>
>> I should've mentioned that I want to import my csv as a data frame or
>> numpy array or as a table.
> If you know the max length of a row, then you can do something like:
> def gen_rows(stream, max_length):
> for row in csv.reader(stream):
> yield row + ([None] * (max_length - len(line))
>
> max_length = 10
> with open('data.csv') as fo:
> df = pd.DataFrame.from_records(gen_rows(fo, max_length))
With the help of the search engine that must not be named and some trial and
error I also found a way to use pandas.read_csv():
$ cat data.csv
a,b
a,b,c,d
a,b,c
$ python3
Python 3.3.2+ (default, Feb 28 2014, 00:52:16)
[GCC 4.8.1] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas
>>> pandas.read_csv("data.csv", names=list(range(4)))
0 1 2 3
0 a b NaN NaN
1 a b c d
2 a b c NaN
And if the maximum row length is not known here's a modification of Miki's
recipe:
def gen_rows(stream, max_length=None):
rows = csv.reader(stream)
if max_length is None:
rows = list(rows)
max_length = max(len(row) for row in rows)
for row in rows:
yield row + [None] * (max_length - len(row))
with open('data.csv') as f:
df = pd.DataFrame.from_records(list(gen_rows(f))) # my version of pandas
# does not accept a
# generator
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