Question

我有一本看起来像这样的字典......

cla_1results= {"Tom":[1,7,4],"Dunc":[3,9,4],"Jack":[1,3,5]}

我想将这个字典写入csv，以便它采用以下格式

没有代表发布图片，但它会是这样的......

Tom,  1, 7, 4
Dunc  3, 9, 4
Jack  1, 3, 5

我尝试过的任何事都没有奏效。我最近的努力在下面，但我是一个真正的初学者，一般都是Python和编程。

import csv

cla_1results= {"Tom":[1,7,4],"Dunc":[3,9,4],"Jack":[1,3,5]}
cla_2results = {"Jane":[1,7,4],"Lynda":[3,9,4],"Dave":[1,3,5]}
cla_3results = {"Gemma":[1,7,4],"Steve":[3,9,4],"Jay":[1,3,5]}

b = open ('test.csv','w')
a = csv.writer(b)
data = cla_1results= {"Tom":[1,7,4],"Dunc":[3,9,4],"Jack":[1,3,5]}
a.writerows(data)
b.close()

不幸的是只给了我：

T, o, m
D, u, n, c
J, a, c, k

等

Answer 1

这应该可行，您只需要一个列表来生成csv文件，因此它也可以动态生成。

import csv
cla_1results= {"Tom":[1,7,4],"Dunc":[3,9,4],"Jack":[1,3,5]}
with open('test.csv', 'wb') as csvfile:

        writer = csv.writer(csvfile, delimiter=',')

        for key,value in cla_1results.iteritems():
                writer.writerow([key]+value)

Answer 2

您可以使用DataFrame.from_dict() classmethod将dict转换为DataFrame，然后使用to_csv将数据框转换为csv。我使用header=False来删除标题。

from pandas import DataFrame

cla_1results = {"Tom": [1, 7, 4], "Dunc": [3, 9, 4], "Jack": [1, 3, 5]}

df = DataFrame.from_dict(cla_1results, orient='index')

print(df.to_csv(header=False))

Dunc,3,9,4
Jack,1,3,5
Tom,1,7,4

Answer 3

尝试：

import csv

with open('test.csv', 'wb') as csvfile:
    c = csv.writer(csvfile)
    line = []
    for key, value in cla.iteritems():
        line.append(key)
        for i in value:
            line.append(i)
        c.writerow(line)

Answer 4

data = {"Tom":[1,7,4],"Dunc":[3,9,4],"Jack":[1,3,5]}
with open('test.csv', 'w') as f:
    for k, vals in data.items():
        line = ','.join([k] + map(str, vals)) + '\n'
        f.write(line)

Answer 5

执行此操作的众多方法之一：

import csv

cla_1results = {
    "Tom": [1, 7, 4],
    "Dunc": [3, 9, 4],
    "Jack": [1, 3, 5]
}

with open("test.csv", 'w+') as file:
    writer = csv.writer(file)

    for name in cla_1results:
        writer.writerow([name, ] + [i for i in cla_1results[name]])

如何编写一个包含多个键的字典，每个键都有多个值到Python中的csv？

5 个答案: