我在csv文件中有数据,看起来就是这样导入的。
import csv
with open('Half-life.csv', 'r') as f:
data = list(csv.reader(f))
数据将在此处显示为打印出data[0] = ['10', '2', '2']
等行的位置。
我想要的是将数据检索为列而不是行,在这种情况下,有3列。
答案 0 :(得分:3)
Alexander's answer的更自动,更灵活的版本:
import csv
from collections import defaultdict
columns = defaultdict(list)
with open('Half-life.csv', 'r') as f:
reader = csv.reader(f, delimiter=',')
for row in reader:
for i in range(len(row)):
columns[i].append(row[i])
# Following line is only necessary if you want a key error for invalid column numbers
columns = dict(columns)
您也可以修改它以使用列标题而不是列号。
import csv
from collections import defaultdict
columns = defaultdict(list)
with open('Half-life.csv', 'r') as f:
reader = csv.reader(f, delimiter=',')
headers = next(reader)
column_nums = range(len(headers)) # Do NOT change to xrange
for row in reader:
for i in column_nums:
columns[headers[i]].append(row[i])
# Following line is only necessary if you want a key error for invalid column names
columns = dict(columns)
答案 1 :(得分:2)
您可以创建三个单独的列表,然后使用csv.reader
附加到每个列表。
import csv
c1 = []
c2 = []
c3 = []
with open('Half-life.csv', 'r') as f:
reader = csv.reader(f, delimiter=',')
for row in reader:
c1.append(row[0])
c2.append(row[1])
c3.append(row[2])
答案 2 :(得分:2)
另一个选项是,如果安装了numpy
,则可以使用loadtxt
将csv文件读入numpy数组。如果你想要更多的列而不是行,你可以转置数组(我不清楚你想要数据的外观)。例如:
import numpy as np
# Load data
data = np.loadtxt('csv_file.csv', delimiter=',')
# Transpose data if needs be
data = np.transpose(data)