我有一个 CSV 文件，下面是它的样例：
Year: Dec: Jan:
1 50 60
2 25 50
3 30 30
4 40 20
5 10 10
我知道如何读取文件并打印每一列（例如 - ['Year', '1', '2', '3', etc]）。但我真正想做的是读取行，就像这样['Year', 'Dec', 'Jan']，然后['1', '50', '60']等等。
然后我想将这些数字存储['1', '50', '60']到变量中，以便稍后将它们汇总，例如：
Year_1 = ['50', '60']. 那我就可以了sum(Year_1) = 110。
我将如何在 Python 3 中做到这一点？
使用csv模块：
import csv
with open("test.csv", "r") as f:
reader = csv.reader(f, delimiter="\t")
for i, line in enumerate(reader):
print 'line[{}] = {}'.format(i, line)
输出：
line[0] = ['Year:', 'Dec:', 'Jan:']
line[1] = ['1', '50', '60']
line[2] = ['2', '25', '50']
line[3] = ['3', '30', '30']
line[4] = ['4', '40', '20']
line[5] = ['5', '10', '10']
你可以这样做：
with open("data1.txt") as f:
lis = [line.split() for line in f] # create a list of lists
for i, x in enumerate(lis): #print the list items
print "line{0} = {1}".format(i, x)
# output
line0 = ['Year:', 'Dec:', 'Jan:']
line1 = ['1', '50', '60']
line2 = ['2', '25', '50']
line3 = ['3', '30', '30']
line4 = ['4', '40', '20']
line5 = ['5', '10', '10']
或者 ：
with open("data1.txt") as f:
for i, line in enumerate(f):
print "line {0} = {1}".format(i, line.split())
# output
line 0 = ['Year:', 'Dec:', 'Jan:']
line 1 = ['1', '50', '60']
line 2 = ['2', '25', '50']
line 3 = ['3', '30', '30']
line 4 = ['4', '40', '20']
line 5 = ['5', '10', '10']
编辑：
with open('data1.txt') as f:
print "{0}".format(f.readline().split())
for x in f:
x = x.split()
print "{0} = {1}".format(x[0],sum(map(int, x[1:])))
# output
['Year:', 'Dec:', 'Jan:']
1 = 110
2 = 75
3 = 60
4 = 60
5 = 20
逐列阅读更难？
无论如何，这会读取该行并将值存储在列表中：
for line in open("csvfile.csv"):
csv_row = line.split() #returns a list ["1","50","60"]
现代解决方案：
# pip install pandas
import pandas as pd
df = pd.read_table("csvfile.csv", sep=" ")
最简单的方法是这样：
from csv import reader
# open file in read mode
with open('file.csv', 'r') as read_obj:
# pass the file object to reader() to get the reader object
csv_reader = reader(read_obj)
# Iterate over each row in the csv using reader object
for row in csv_reader:
# row variable is a list that represents a row in csv
print(row)
output:
['Year:', 'Dec:', 'Jan:']
['1', '50', '60']
['2', '25', '50']
['3', '30', '30']
['4', '40', '20']
['5', '10', '10']
import csv
with open('filepath/filename.csv', "rt", encoding='ascii') as infile:
read = csv.reader(infile)
for row in read :
print (row)
这将解决您的问题。不要忘记给出编码。
# This program reads columns in a csv file
import csv
ifile = open('years.csv', "r")
reader = csv.reader(ifile)
# initialization and declaration of variables
rownum = 0
year = 0
dec = 0
jan = 0
total_years = 0`
for row in reader:
if rownum == 0:
header = row #work with header row if you like
else:
colnum = 0
for col in row:
if colnum == 0:
year = float(col)
if colnum == 1:
dec = float(col)
if colnum == 2:
jan = float(col)
colnum += 1
# end of if structure
# now we can process results
if rownum != 0:
print(year, dec, jan)
total_years = total_years + year
print(total_years)
# time to go after the next row/bar
rownum += 1
ifile.close()
有点晚了，但仍然......您需要创建并识别名为“years.csv”的 csv 文件：
年份 十二月 一月 1 50 60 2 25 50 3 30 30 4 40 20 5 10 10
import pandas as pd
data = pd.read_csv('data.csv')
# read row line by line
for d in data.values:
# read column by index
print(d[2])
该csv模块按行处理 csv 文件。如果要按列处理，pandas是一个很好的解决方案。
此外，有两种方法可以使用纯简单的 Python 代码获取所有（或特定）列。
with open('demo.csv') as file:
data = {}
for row in csv.DictReader(file):
for key, value in row.items():
if key not in data:
data[key] = []
data[key].append(value)
这很容易理解。
with open('demo.csv') as file:
data = {values[0]: values[1:] for values in zip(*csv.reader(file))}
这不是很清楚，但很有效。
zip(x, y, z)transpose (x, y, z), 而x, y,z是列表。
*csv.reader(file)make (x, y, z)for zip，带有列名。
的内容demo.csv：
a,b,c
1,2,3
4,5,6
7,8,9
1的结果：
>>> print(data)
{'c': ['3', '6', '9'], 'b': ['2', '5', '8'], 'a': ['1', '4', '7']}
2的结果：
>>> print(data)
{'c': ('3', '6', '9'), 'b': ('2', '5', '8'), 'a': ('1', '4', '7')}
可以使用pandas库来做到这一点。
例子：
import numpy as np
import pandas as pd
file = r"C:\Users\unknown\Documents\Example.csv"
df1 = pd.read_csv(file)
df1.head()
我只是把我的解决方案留在这里。
import csv
import numpy as np
with open(name, newline='') as f:
reader = csv.reader(f, delimiter=",")
# skip header
next(reader)
# convert csv to list and then to np.array
data = np.array(list(reader))[:, 1:] # skip the first column
print(data.shape) # => (N, 2)
# sum each row
s = data.sum(axis=1)
print(s.shape) # => (N,)