Python: skip comment lines marked with # in csv.DictReader
Solution 1
Actually this works nicely with filter
:
import csv
fp = open('samples.csv')
rdr = csv.DictReader(filter(lambda row: row[0]!='#', fp))
for row in rdr:
print(row)
fp.close()
Solution 2
Good question. Python's CSV library lacks basic support for comments (not uncommon at the top of CSV files). While Dan Stowell's solution works for the specific case of the OP, it is limited in that #
must appear as the first symbol. A more generic solution would be:
def decomment(csvfile):
for row in csvfile:
raw = row.split('#')[0].strip()
if raw: yield raw
with open('dummy.csv') as csvfile:
reader = csv.reader(decomment(csvfile))
for row in reader:
print(row)
As an example, the following dummy.csv
file:
# comment
# comment
a,b,c # comment
1,2,3
10,20,30
# comment
returns
['a', 'b', 'c']
['1', '2', '3']
['10', '20', '30']
Of course, this works just as well with csv.DictReader()
.
Solution 3
Another way to read a CSV file is using pandas
Here's a sample code:
df = pd.read_csv('test.csv',
sep=',', # field separator
comment='#', # comment
index_col=0, # number or label of index column
skipinitialspace=True,
skip_blank_lines=True,
error_bad_lines=False,
warn_bad_lines=True
).sort_index()
print(df)
df.fillna('no value', inplace=True) # replace NaN with 'no value'
print(df)
For this csv file:
a,b,c,d,e
1,,16,,55#,,65##77
8,77,77,,16#86,18#
#This is a comment
13,19,25,28,82
we will get this output:
b c d e
a
1 NaN 16 NaN 55
8 77.0 77 NaN 16
13 19.0 25 28.0 82
b c d e
a
1 no value 16 no value 55
8 77 77 no value 16
13 19 25 28 82
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Dan Stowell
Updated on July 05, 2022Comments
-
Dan Stowell almost 2 years
Processing CSV files with csv.DictReader is great - but I have CSV files with comment lines (indicated by a hash at the start of a line), for example:
# step size=1.61853 val0,val1,val2,hybridisation,temp,smattr 0.206895,0.797923,0.202077,0.631199,0.368801,0.311052,0.688948,0.597237,0.402763 -169.32,1,1.61853,2.04069e-92,1,0.000906546,0.999093,0.241356,0.758644,0.202382 # adaptation finished
The csv module doesn't include any way to skip such lines.
I could easily do something hacky, but I imagine there's a nice way to wrap a
csv.DictReader
around some other iterator object, which preprocesses to discard the lines. -
Duncan over 11 yearsThat will read the whole file into memory. If it isn't too large then no problem, otherwise you might want to use a generator expression or
itertools.ifilter()
. -
Andy Mikhaylenko over 10 years...or a generator expression:
csv.DictReader(row for row in fp if not row.startswith('#'))
-
The Aelfinn about 6 years@Duncan no need for itertools in Python3.6, as
filter()
will return an iterator by default, therefore the file will not be loaded into memory. -
Lacek almost 5 years
pandas
is indeed a powerful library, yet it is a dependency that require setup and learning to use. Moreover, the author had already stated in the question that he simply wanted to use the built-incsv.DictReader
module and relevant answers were provided years ago already. I don't understand why you add this solution as an alternative. -
Granny Aching almost 5 yearsThe author of the question might not need pandas. But the purpose of this forum is more than just help each question's author with their specific problem.
-
Thibault Reuille about 4 yearsI believe you meant "yield row" not "yield raw" in the decomment() function. A CSV file can contain # characters in a string and it is perfectly valid.
-
sigvaldm about 4 years@ThibaultReuille: It is true that many CSV files can contain # in strings, although the CSV format is not well standardized. I meant
yield raw
. My suggestion would not deal with # in strings in any case. -
sigvaldm about 4 years@ThibaultReuille: What you're pointing at is exactly why it is inadvisable to manually type a lot of code for something a library can do for you; you probably won't get all the details right the first time (for instance, you could also have newlines in strings), and it will take away time from the task you're actually solving. I consider my solution a quick fix for something that ought to have been in
csv
. If it would need considerable expansion to work for you, perhaps you should consider another csv library, for instance the one in pandas. Hope that helps. -
sigvaldm about 4 yearsThis will not work when comments follow at the end of rows, e.g.,
a,b,c # comment
. -
Micheal J. Roberts over 3 years@GrannyAching What exactly does
.sort_index()
achieve here? :) -
Ulf Gjerdingen over 2 yearspretty sure @Andy Mikhaylenko's generator expression worked really well but it doesn't any more. what up? (Python 3.7.5)