带有元组列表的python字典到CSV

Question

怎么会有这样的python字典：

{
    'RCLS1': [(0, 20),  (10, 112),  (20, 130), (30, 102)],
    'RCLS2': [(0, 16),(10, 53),(20, 96), (30, 45)]
}

转换为具有结构的 CSV：

RCLS1,  0,  20
RCLS1, 10, 112
.
.
.
RLCS2, 30,  45

我试过这个：

with open(r'E:\data.csv', "wb") as f:
    csv.writer(f).writerows((k,) + v for k, v in dct.items())

但这导致了以下错误：

can only concatenate tuple (not "list") to tuple

Answer 1

根据您提供的示例输入/输出，您可以遍历字典的键值对，然后遍历与每个键关联的元组值列表，构建关联的 CSV 行字符串，并将其写入 CSV文件，像这样：

dct = {'RCLS1':[(0, 20),  (10, 112),  (20, 130), (30, 102)], 'RCLS2': [(0, 16),(10, 53),(20, 96), (30, 45)]}
int_to_str = lambda int_value: str(int_value)

with open(r"data.csv", "w") as csv_file:
    for key, values in dct.items():
         for tuple_value in values:
             csv_row = [key] + list(map(int_to_str, list(tuple_value)))
             csv_file.write(", ".join(csv_row) + "\n")

data.csv 结果：

RCLS2, 0, 16
RCLS2, 10, 53
RCLS2, 20, 96
RCLS2, 30, 45
RCLS1, 0, 20
RCLS1, 10, 112
RCLS1, 20, 130
RCLS1, 30, 102

Answer 2

如果我从你的问题中理解的是正确的，那么你正在尝试做这样的事情（不需要使用csv 模块）：

a = {'RCLS1':[(0, 20),  (10, 112),  (20, 130), (30, 102)], 'RCLS2': [(0, 16),(10, 53),(20, 96), (30, 45)]}

with open('E:\data.csv', 'a+') as f:
    for k,v in a.items():
        f.write("{0}: {1}\n".format(k,", ".join(", ".join(str(j) for j in k) for k in v)))

输出（文件中的日期将与此输出类似）：

RCLS1: 0, 20, 10, 112, 20, 130, 30, 102
RCLS2: 0, 16, 10, 53, 20, 96, 30, 45

否则，如果您想成对获取数据，您可以执行以下操作：

with open('E:\data.csv', 'a+') as f:
    for k,v in a.items():
        f.write("{0}: {1}\n".format(k, "".join(", ".join(str(k) for k in v))))

输出：

RCLS1: (0, 20), (10, 112), (20, 130), (30, 102)
RCLS2: (0, 16), (10, 53), (20, 96), (30, 45)

编辑：

新更新的快速解决方案。你可以这样做：

a = {'RCLS1':[(0, 20),  (10, 112),  (20, 130), (30, 102)], 'RCLS2': [(0, 16),(10, 53),(20, 96), (30, 45)]}

with open('E:\data.csv', 'a+') as f:
    for k,v in a.items():
        for j in v:
            f.write("{0}: {1}\n".format(k, ", ".join(str(k) for k in j)))

输出：

RCLS2: 0, 16
RCLS2: 10, 53
RCLS2: 20, 96
RCLS2: 30, 45
RCLS1: 0, 20
RCLS1: 10, 112
RCLS1: 20, 130
RCLS1: 30, 102

Answer 3

使用pandas 的另一种答案：

>>> import pandas as pd
>>> d={'RCLS1':[(0, 20),  (10, 112),  (20, 130), (30, 102)], 'RCLS2': [(0, 16),(10, 53),(20, 96), (30, 45)]}
>>> df=pd.DataFrame(d)


       RCLS1     RCLS2
0    (0, 20)   (0, 16)
1  (10, 112)  (10, 53)
2  (20, 130)  (20, 96)
3  (30, 102)  (30, 45)
[4 rows x 2 columns]

>>> dfs=df.stack().reset_index(level=0)

       level_0          0
RCLS1        0    (0, 20)
RCLS2        0    (0, 16)
RCLS1        1  (10, 112)
RCLS2        1   (10, 53)
RCLS1        2  (20, 130)
RCLS2        2   (20, 96)
RCLS1        3  (30, 102)
RCLS2        3   (30, 45)


>>> dfs=dfs[0].apply(pd.Series)  # break the tuples in column with "name"=0

        0    1
RCLS1   0   20
RCLS2   0   16
RCLS1  10  112
RCLS2  10   53
RCLS1  20  130
RCLS2  20   96
RCLS1  30  102
RCLS2  30   45


>>> dfs.to_csv('fileName.csv')