I have a csv file
col1, col2, col3
1, 2, 3
4, 5, 6
I want to create a list of dictionary from this csv.
output as :
# similar solution via namedtuple:
import csv
from collections import namedtuple
with open('foo.csv') as f:
fh = csv.reader(open(f, "rU"), delimiter=',', dialect=csv.excel_tab)
headers = fh.next()
Row = namedtuple('Row', headers)
list_of_dicts = [Row._make(i)._asdict() for i in fh]
Using the csv
module and a list comprehension:
import csv
with open('foo.csv') as f:
reader = csv.reader(f, skipinitialspace=True)
header = next(reader)
a = [dict(zip(header, map(int, row))) for row in reader]
print a
Output:
[{'col3': 3, 'col2': 2, 'col1': 1}, {'col3': 6, 'col2': 5, 'col1': 4}]
Use csv.DictReader:
import csv
with open('test.csv') as f:
a = [{k: int(v) for k, v in row.items()}
for row in csv.DictReader(f, skipinitialspace=True)]
Will result in :
[{'col2': 2, 'col3': 3, 'col1': 1}, {'col2': 5, 'col3': 6, 'col1': 4}]
Another simpler answer:
import csv
with open("configure_column_mapping_logic.csv", "r") as f:
reader = csv.DictReader(f)
a = list(reader)
print a
Simple method to parse CSV into list of dictionaries
with open('/home/mitul/Desktop/OPENEBS/test.csv', 'rb') as infile:
header = infile.readline().split(",")
for line in infile:
fields = line.split(",")
entry = {}
for i,value in enumerate(fields):
entry[header[i].strip()] = value.strip()
data.append(entry)
Well, while other people were out doing it the smart way, I implemented it naively. I suppose my approach has the benefit of not needing any external modules, although it will probably fail with weird configurations of values. Here it is just for reference:
a = []
with open("csv.txt") as myfile:
firstline = True
for line in myfile:
if firstline:
mykeys = "".join(line.split()).split(',')
firstline = False
else:
values = "".join(line.split()).split(',')
a.append({mykeys[n]:values[n] for n in range(0,len(mykeys))})