Jun 142019Import CSV as Dict
- Creates ordered dict
- You can increase file size limit
- Using next() can bypass the header row
import csv
# Dict reader creates an ordered dict (first row will be headers)
with open('./data/file.csv', newline='') as file:
# Huge csv files might give you a size limit error
csv.field_size_limit(100000000)
results = csv.DictReader(file, delimiter=';', quotechar='*', quoting=csv.QUOTE_ALL)
# next() can help in iterations sometimes
next(results)
for row in results:
# prints each item in the column with header 'key'
print(row['key'])
Import CSV with No Header (nested lists)
- newline='' prevents blank lines
- csv.reader uses indexes [0], [1]
# newline='' prevents blank lines
with open('./data/file.csv', newline='') as file:
results = csv.reader(file, delimiter=':', quoting=csv.QUOTE_NONE)
for row in results:
# csv reader uses indexes
print(row[0])
Writing and Creating Headers
- Create a csv.writer object
- Create header manually before loop
- Nested lists are better than tuples inside lists
- writer.writerow and writer.writerows
# Creates a csv writer object
writer = csv.writer(
file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
# Write header first if you would like
writer.writerow(['title', 'price', 'shipping'])
''' Tuples inside list (list inside lists are usually better though).
If you're using tuples and they are variable size, note that a single tuple
will convert to string type in a loop so indexing it [0] won't work. '''
products = [['slinky', '$5', 'Free'],
['pogo', '$12', '$6'],
['Yoyo', '$7', '$2']]
# write each row normal
for item in products:
writer.writerow(map(str, item))
# Writes all items into a single row
writer.writerow(sum(products, []))
# Writes all 3 rows
writer.writerows(products)
Using DictWriter for Headers
- fieldnames indicates header to object
- writer.writeheader() writes those fields
# DictWriter field names will add the headers for you when you call writeheader()
with open("./data/file.csv", "w") as file:
writer = csv.DictWriter(
file, fieldnames=['title', 'price', 'shipping'],
quoting=csv.QUOTE_NONNUMERIC)
writer.writeheader()
writer.writerows([['slinky', '$5', 'Free'],
['pogo', '$12', '$6'],
['Yoyo', '$7', '$2']])
Bonus - Flatten any List
- Function will flatten any level of nested lists
- or type == tuple() to catch tuples too
# -- Bonus (Off Topic) --
# You can flatten any list with type checking and recursion
l = [1, 2, [3, 4, [5, 6]], 7, 8, [9, [10]]]
output = []
def flatten_list(l):
for i in l:
if type(i) == list:
flatten_list(i)
else:
output.append(i)
reemovNestings(l)
