从csv文件创建字典？

Question

我正在尝试从csv文件创建一个字典.csv文件的第一列包含唯一键,第二列包含值.csv文件的每一行代表字典中唯一的键值对.我试图使用csv.DictReader和csv.DictWriter类,但我只能弄清楚如何为每一行生成一个新的字典.我想要一本字典.这是我尝试使用的代码:

import csv

with open('coors.csv', mode='r') as infile:
    reader = csv.reader(infile)
    with open('coors_new.csv', mode='w') as outfile:
    writer = csv.writer(outfile)
    for rows in reader:
        k = rows[0]
        v = rows[1]
        mydict = {k:v for k, v in rows}
    print(mydict)

当我运行上面的代码时,我得到了一个ValueError: too many values to unpack (expected 2).如何从csv文件创建一个字典？谢谢.

Answer 1

我相信你要找的语法如下:

with open('coors.csv', mode='r') as infile:
    reader = csv.reader(infile)
    with open('coors_new.csv', mode='w') as outfile:
        writer = csv.writer(outfile)
        mydict = {rows[0]:rows[1] for rows in reader}

或者,对于python <= 2.7.1,您需要:

mydict = dict((rows[0],rows[1]) for rows in reader)

Answer 2

通过调用open然后打开文件csv.DictReader.

input_file = csv.DictReader(open("coors.csv"))

您可以通过遍历input_file来迭代csv文件dict reader对象的行.

for row in input_file:
    print row

或仅访问第一行

dictobj = csv.DictReader(open('coors.csv')).next() 

Answer 3

import csv
reader = csv.reader(open('filename.csv', 'r'))
d = {}
for row in reader:
   k, v = row
   d[k] = v

Answer 4

这不是优雅,而是使用熊猫的一线解决方案.

import pandas as pd
pd.read_csv('coors.csv', header=None, index_col=0, squeeze=True).to_dict()

如果要为索引指定dtype(如果因为错误而使用index_col参数,则无法在read_csv中指定):

import pandas as pd
pd.read_csv('coors.csv', header=None, dtype={0: str}).set_index(0).squeeze().to_dict()

Answer 5

你必须将csv.reader转换为dict:

~ >> cat > 1.csv
key1, value1
key2, value2
key2, value22
key3, value3

~ >> cat > d.py
import csv
with open('1.csv') as f:
    d = dict(filter(None, csv.reader(f)))

print(d)

~ >> python d.py
{'key3': ' value3', 'key2': ' value22', 'key1': ' value1'}

Answer 6

你也可以使用numpy.

from numpy import loadtxt
key_value = loadtxt("filename.csv", delimiter=",")
mydict = { k:v for k,v in key_value }

Answer 7

单线解决方案

import pandas as pd

dict = {row[0] : row[1] for _, row in pd.read_csv("file.csv").iterrows()}

Answer 8

对于简单的 csv 文件，例如以下

id,col1,col2,col3
row1,r1c1,r1c2,r1c3
row2,r2c1,r2c2,r2c3
row3,r3c1,r3c2,r3c3
row4,r4c1,r4c2,r4c3

您可以仅使用内置函数将其转换为 Python 字典

with open(csv_file) as f:
    csv_list = [[val.strip() for val in r.split(",")] for r in f.readlines()]

(_, *header), *data = csv_list
csv_dict = {}
for row in data:
    key, *values = row   
    csv_dict[key] = {key: value for key, value in zip(header, values)}

这应该产生以下字典

{'row1': {'col1': 'r1c1', 'col2': 'r1c2', 'col3': 'r1c3'},
 'row2': {'col1': 'r2c1', 'col2': 'r2c2', 'col3': 'r2c3'},
 'row3': {'col1': 'r3c1', 'col2': 'r3c2', 'col3': 'r3c3'},
 'row4': {'col1': 'r4c1', 'col2': 'r4c2', 'col3': 'r4c3'}}

注意：Python 字典有唯一的键，所以如果你的 csv 文件有重复，ids你应该将每一行附加到一个列表中。

for row in data:
    key, *values = row

    if key not in csv_dict:
            csv_dict[key] = []

    csv_dict[key].append({key: value for key, value in zip(header, values)})

Answer 9

我建议添加if rows以防文件末尾有空行

import csv
with open('coors.csv', mode='r') as infile:
    reader = csv.reader(infile)
    with open('coors_new.csv', mode='w') as outfile:
        writer = csv.writer(outfile)
        mydict = dict(row[:2] for row in reader if row)

Answer 10

假设您有一个这种结构的 CSV：

"a","b"
1,2
3,4
5,6

并且您希望输出为：

[{'a': '1', ' "b"': '2'}, {'a': '3', ' "b"': '4'}, {'a': '5', ' "b"': '6'}]

zip 函数（尚未提及）很简单而且很有帮助。

def read_csv(filename):
    with open(filename) as f:
        file_data=csv.reader(f)
        headers=next(file_data)
        return [dict(zip(headers,i)) for i in file_data]

如果你更喜欢熊猫，它也可以很好地做到这一点：

import pandas as pd
def read_csv(filename):
    return pd.read_csv(filename).to_dict('records')