Python将csv导入列表

我有一个大约有2000条记录的CSV文件。

每个记录都有一个字符串和一个类别：

This is the first line,Line1
This is the second line,Line2
This is the third line,Line3

我需要将此文件读入如下列表：

data = [('This is the first line', 'Line1'),
        ('This is the second line', 'Line2'),
        ('This is the third line', 'Line3')]

如何使用Python将CSV导入到我需要的列表中？

使用csv模块：

import csv

with open('file.csv', newline='') as f:
    reader = csv.reader(f)
    data = list(reader)

print(data)

输出：

[['This is the first line', 'Line1'], ['This is the second line', 'Line2'], ['This is the third line', 'Line3']]

如果您需要元组：

import csv

with open('file.csv', newline='') as f:
    reader = csv.reader(f)
    data = [tuple(row) for row in reader]

print(data)

输出：

[('This is the first line', 'Line1'), ('This is the second line', 'Line2'), ('This is the third line', 'Line3')]

旧的Python 2答案，也使用csv模块：

import csv
with open('file.csv', 'rb') as f:
    reader = csv.reader(f)
    your_list = list(reader)

print your_list
# [['This is the first line', 'Line1'],
#  ['This is the second line', 'Line2'],
#  ['This is the third line', 'Line3']]

已针对Python 3更新：

import csv

with open('file.csv', newline='') as f:
    reader = csv.reader(f)
    your_list = list(reader)

print(your_list)

输出：

[['This is the first line', 'Line1'], ['This is the second line', 'Line2'], ['This is the third line', 'Line3']]

熊猫非常擅长处理数据。这是一个如何使用它的示例：

import pandas as pd

# Read the CSV into a pandas data frame (df)
#   With a df you can do many things
#   most important: visualize data with Seaborn
df = pd.read_csv('filename.csv', delimiter=',')

# Or export it in many ways, e.g. a list of tuples
tuples = [tuple(x) for x in df.values]

# or export it as a list of dicts
dicts = df.to_dict().values()

一大优势是，熊猫自动处理标题行。

如果您还没有听说过Seaborn，建议您看看。

另请参阅：如何使用Python读写CSV文件？

熊猫＃2

import pandas as pd

# Get data - reading the CSV file
import mpu.pd
df = mpu.pd.example_df()

# Convert
dicts = df.to_dict('records')

df的内容是：

     country   population population_time    EUR
0    Germany   82521653.0      2016-12-01   True
1     France   66991000.0      2017-01-01   True
2  Indonesia  255461700.0      2017-01-01  False
3    Ireland    4761865.0             NaT   True
4      Spain   46549045.0      2017-06-01   True
5    Vatican          NaN             NaT   True

字典的内容是

[{'country': 'Germany', 'population': 82521653.0, 'population_time': Timestamp('2016-12-01 00:00:00'), 'EUR': True},
 {'country': 'France', 'population': 66991000.0, 'population_time': Timestamp('2017-01-01 00:00:00'), 'EUR': True},
 {'country': 'Indonesia', 'population': 255461700.0, 'population_time': Timestamp('2017-01-01 00:00:00'), 'EUR': False},
 {'country': 'Ireland', 'population': 4761865.0, 'population_time': NaT, 'EUR': True},
 {'country': 'Spain', 'population': 46549045.0, 'population_time': Timestamp('2017-06-01 00:00:00'), 'EUR': True},
 {'country': 'Vatican', 'population': nan, 'population_time': NaT, 'EUR': True}]

熊猫＃3

import pandas as pd

# Get data - reading the CSV file
import mpu.pd
df = mpu.pd.example_df()

# Convert
lists = [[row[col] for col in df.columns] for row in df.to_dict('records')]

的内容lists是：

[['Germany', 82521653.0, Timestamp('2016-12-01 00:00:00'), True],
 ['France', 66991000.0, Timestamp('2017-01-01 00:00:00'), True],
 ['Indonesia', 255461700.0, Timestamp('2017-01-01 00:00:00'), False],
 ['Ireland', 4761865.0, NaT, True],
 ['Spain', 46549045.0, Timestamp('2017-06-01 00:00:00'), True],
 ['Vatican', nan, NaT, True]]

Python3更新：

import csv
from pprint import pprint

with open('text.csv', newline='') as file:
    reader = csv.reader(file)
    res = list(map(tuple, reader))

pprint(res)

输出：

[('This is the first line', ' Line1'),
 ('This is the second line', ' Line2'),
 ('This is the third line', ' Line3')]

如果csvfile是文件对象，则应使用打开newline=''。
CSV模组

如果你相信有您的输入没有逗号，以外的其他类别分开，你可以逐行读取文件中的行和分裂上,，然后推结果List

也就是说，您似乎正在查看CSV文件，因此您可以考虑为其使用模块

result = []
for line in text.splitlines():
    result.append(tuple(line.split(",")))

正如评论中已经说过的那样，您可以csv在python中使用该库。csv的意思是逗号分隔的值，这似乎与您的情况完全相同：标签和由逗号分隔的值。

作为类别和值类型，我宁愿使用字典类型而不是元组列表。

无论如何，在下面的代码中，我都会同时显示两种方式：d是字典，l是元组列表。

import csv

file_name = "test.txt"
try:
    csvfile = open(file_name, 'rt')
except:
    print("File not found")
csvReader = csv.reader(csvfile, delimiter=",")
d = dict()
l =  list()
for row in csvReader:
    d[row[1]] = row[0]
    l.append((row[0], row[1]))
print(d)
print(l)

一个简单的循环就足够了：

lines = []
with open('test.txt', 'r') as f:
    for line in f.readlines():
        l,name = line.strip().split(',')
        lines.append((l,name))

print lines

不幸的是，我发现没有一个现有的答案特别令人满意。

这是一个使用csv模块的简单，完整的Python 3解决方案。

import csv

with open('../resources/temp_in.csv', newline='') as f:
    reader = csv.reader(f, skipinitialspace=True)
    rows = list(reader)

print(rows)

注意skipinitialspace=True参数。这是必要的，因为不幸的是，OP的CSV在每个逗号后都包含空格。

输出：

[['This is the first line', 'Line1'], ['This is the second line', 'Line2'], ['This is the third line', 'Line3']]

稍微扩展您的需求，并假设您不关心行的顺序，并希望将它们分组在类别下，则以下解决方案可能适用于您：

>>> fname = "lines.txt"
>>> from collections import defaultdict
>>> dct = defaultdict(list)
>>> with open(fname) as f:
...     for line in f:
...         text, cat = line.rstrip("\n").split(",", 1)
...         dct[cat].append(text)
...
>>> dct
defaultdict(<type 'list'>, {' CatA': ['This is the first line', 'This is the another line'], ' CatC': ['This is the third line'], ' CatB': ['This is the second line', 'This is the last line']})

这样，您可以在字典中键为类别下获得所有可用的相关行。

这是Python 3.x中最简单的将CSV导入多维数组的方法，它仅4行代码而无需导入任何内容！

#pull a CSV into a multidimensional array in 4 lines!

L=[]                            #Create an empty list for the main array
for line in open('log.txt'):    #Open the file and read all the lines
    x=line.rstrip()             #Strip the \n from each line
    L.append(x.split(','))      #Split each line into a list and add it to the
                                #Multidimensional array
print(L)

接下来是一段代码，该代码使用csv模块，但使用第一行（即csv表的标头）将file.csv内容提取到字典列表中

import csv
def csv2dicts(filename):
  with open(filename, 'rb') as f:
    reader = csv.reader(f)
    lines = list(reader)
    if len(lines) < 2: return None
    names = lines[0]
    if len(names) < 1: return None
    dicts = []
    for values in lines[1:]:
      if len(values) != len(names): return None
      d = {}
      for i,_ in enumerate(names):
        d[names[i]] = values[i]
      dicts.append(d)
    return dicts
  return None

if __name__ == '__main__':
  your_list = csv2dicts('file.csv')
  print your_list