蟒蛇字典，以CSV

Question

元组的列表哪有Python字典，看起来像这样：

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

转换为CSV具有结构：

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

我已经试过这样：

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

但这会导致以下错误：

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，遍历与每个键关联的元组值列表，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

如果我从你的问题理解是正确的，你正在尝试做这样的事情（无需否则

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

，如果你想拥有的对你能做的数据：使用csv模块）的：

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（在文件中的日期将是类似这样的输出）是这样的：

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：

迅速解决您的新的更新。你可以做这样的：

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一个备选答案：

>>> 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')