Python - 将数据拆分为 csv 文件中的列
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Python - splitting data as columns in csv file
提问by iron2man
I have data in a csv file that looks like that is imported as this.
我在一个 csv 文件中有数据，看起来像这样导入。
import csv
with open('Half-life.csv', 'r') as f:
data = list(csv.reader(f))
the data will come out as this to where it prints out the rows like data[0] = ['10', '2', '2']and so on.
数据将作为这个输出到它打印出诸如此类的行的地方data[0] = ['10', '2', '2']。
What i'm wanting though is to retrieve the data as columns in instead of rows, to where in this case, there are 3 columns.
我想要的是将数据作为列而不是行检索，在这种情况下，有 3 列。
回答by Alexander
You can create three separate lists, and then append to each using csv.reader.
您可以创建三个单独的列表，然后使用csv.reader.
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])
回答by jpmc26
A little more automatic and flexible version of Alexander's answer:
亚历山大答案的更自动和灵活的版本：
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)
You could also modify this to use column headers instead of column numbers.
您还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)
回答by Ryan James
Another option, if you have numpyinstalled, you can use loadtxtto read a csv file into a numpy array. You can then transpose the array if you want more columns than rows (I wasn't quite clear on how you wanted the data to look). For example:
另一种选择，如果您已numpy安装，则可以使用loadtxt将 csv 文件读入 numpy 数组。如果您想要的列多于行，您可以转置数组（我不太清楚您希望数据的外观）。例如：
import numpy as np
# Load data
data = np.loadtxt('csv_file.csv', delimiter=',')
# Transpose data if needs be
data = np.transpose(data)
