Python – CSC
CSV Data 읽고 쓰기(Reading and Writing CSV Data)
읽기(Reading)
stocks.csv
stocks.csv
Symbol,Price,Date,Time,Change,Volume
"AA",39.48,"6/11/2007","9:36am",-0.18,181800
"AIG",71.38,"6/11/2007","9:36am",-0.15,195500
"AXP",62.58,"6/11/2007","9:36am",-0.46,935000
"BA",98.31,"6/11/2007","9:36am",+0.12,104800
"C",53.08,"6/11/2007","9:36am",-0.25,360900
"CAT",78.29,"6/11/2007","9:36am",-0.23,225400
csv library 사용
import csv
with open('stocks.csv') as f:
f_csv = csv.reader(f)
headers = next(f_csv)
for row in f_csv:
# Process row
#print(row)
print('basic : %s %s ' % (row[0], row[4]))
row
는 list 자료형- 인덱싱으로 자료 처리(indexing)
row[0]
(Symbol) androw[4]
(Change).- 인덱싱은 종종 혼동을 일으킴
namedtuple 사용
import csv
from collections import namedtuple
with open('stocks.csv') as f:
f_csv = csv.reader(f)
headings = next(f_csv)
Row = namedtuple('Row', headings)
for r in f_csv:
row = Row(*r)
# Process row
#print(row)
print('Row : %s %s ' % (row.Symbol, row.Change))
row.Symbol
androw.Change
- use of column headers
csv.DictReader 사용
import csv
with open('stocks.csv') as f:
f_csv = csv.DictReader(f)
for row in f_csv:
# process row
#print(row)
print('OrderedDict : %s %s ' % (row['Symbol'], row['Change']))
row['Symbol']
orrow['Change']
.
CSV data 쓰기 : csv.writer 사용
import csv
headers = ['Symbol','Price','Date','Time','Change','Volume']
rows = [('AA', 39.48, '6/11/2007', '9:36am', -0.18, 181800),
('AIG', 71.38, '6/11/2007', '9:36am', -0.15, 195500),
('AXP', 62.58, '6/11/2007', '9:36am', -0.46, 935000),
]
with open('stocks_new.csv','w', newline='') as f:
f_csv = csv.writer(f)
f_csv.writerow(headers)
f_csv.writerows(rows)
쓰기(Writing)
csv.DictWriter 사용
import csv
headers = ['Symbol', 'Price', 'Date', 'Time', 'Change', 'Volume']
rows = [{'Symbol':'AA', 'Price':39.48, 'Date':'6/11/2007',
'Time':'9:36am', 'Change':-0.18, 'Volume':181800},
{'Symbol':'AIG', 'Price': 71.38, 'Date':'6/11/2007',
'Time':'9:36am', 'Change':-0.15, 'Volume': 195500},
{'Symbol':'AXP', 'Price': 62.58, 'Date':'6/11/2007',
'Time':'9:36am', 'Change':-0.46, 'Volume': 935000},
]
with open('stocks_new.csv','w', newline='') as f:
f_csv = csv.DictWriter(f, headers)
f_csv.writeheader()
f_csv.writerows(rows)