我们怎样才能完成从字典中追加 excel 的过程?

How can we do the process of appending excel from dictionary?

我正在尝试编写一个代码来解析来自网络输出的一些数据,并在一组设备上循环并将结果附加到字典中,然后将每个字典键和值写入 excel sheet

我现在面临的问题是每次执行循环时键值都打印为列headers

dictionary = {"key1":[],"key2":[],"key3":[]}
dictionary["key1"].append(parse_value1)
dictionary["key2"].append(parse_value2)
dictionary_to_df = pd.DataFrame(dictionary)
dictionary_to_df("csv path,mode = "a",index = False, header = True)

输出是这样的:

key1 key2 key3
value1 value2 value3
key 1 key2 key3
value4 value5 value6

不过我想得到如下输出

key1 key2 key3
value1 value2 value3
value4 value5 value6

使用简单代码(pd.DataFrame.from_dict):

dictionary = {"key1":[],"key2":[]}
parse_value1=["value1","value2","value3"]
parse_value2=["value4","value5","value6"]
dictionary["key1"].extend(parse_value1)
dictionary["key2"].extend(parse_value2)
dictionary_to_df  =pd.DataFrame.from_dict(dictionary)
dictionary_to_df.to_csv("test.csv",mode = "a",index = False, header = True)

您可以尝试将从循环生成的所有数据帧连接到一个更大的数据帧

dfs = []

for loop
    dictionary = {"key1":[],"key2":[],"key3":[]}
    dictionary["key1"].append(parse_value1)
    dictionary["key2"].append(parse_value2)
    dictionary_to_df = pd.DataFrame(dictionary)
    dfs.append(dictionary_to_df)

df = pd.concat([dfs])
df.to_csv("csv path", mode = "a",index = False, header = True)

或者使 dictionary 对于 for-loop

是全局的
dictionary = {"key1":[],"key2":[],"key3":[]}

for loop
    dictionary["key1"].append(parse_value1)
    dictionary["key2"].append(parse_value2)

dictionary_to_df = pd.DataFrame(dictionary)
dictionary_to_df.to_csv("csv path", mode = "a",index = False, header = True)

或者检查文件头是否存在

for loop
    dictionary = {"key1":[],"key2":[],"key3":[]}
    dictionary["key1"].append(parse_value1)
    dictionary["key2"].append(parse_value2)
    dictionary_to_df = pd.DataFrame(dictionary)
    with open("csv path", 'a') as f:
        dictionary_to_df.to_csv(f,mode = "a",index=False, header=not f.tell())

我通过

解决了这个问题
  1. 在循环外定义header
  2. 将header写入output.csv文件
  3. 将字典转换为数据框
  4. 使用 header option = false
  5. 将数据框附加到 output.csv 文件中