在Pandas中，将dictionary与输出数据帧的单个值组合

Question

如果我有很多字典，如何最好地将它们组合成一个Panda DataFrame？我还希望有一个添加的列，每个列都有一个给定的值；批次"；字典。

示例输入：

# Declare initial parameters:
bonuscolumn_name = 'Col_A'
desired_pd = pd.DataFrame(columns=['bonuscolumn_name', 'name', 'age'])
# First batch of dictionaries:
bonuscolumn_value1 = 'somevalue'
dict1 = {'name':'Sam', 'age':26}
dict2 = {'name':'Albert', 'age':21}
dict3 = {'name':'Brock', 'age':57}
# Second batch of dictionaries:
bonuscolumn_value1 = 'diffvalue'
dict4 = {'name':'Fred', 'age':14}
dict5 = {'name':'Philbert', 'age':20}

期望输出：

1//tr>7

Col_A	name	age
somevalue	Sam	26
somevalue	Tyler
somevalue	Brock
diffvalue	Fred	14
diffvalue	Philbert	20

您可以为每个数据元素创建一个数据帧，然后使用：

df = pd.concat([dict1, dict2, dict3, dict4, dict5, dict6], keys=[dict1, dict2, dict3, dict4, dict5, dict6])

然后：

df.reset_index(inplace=True)

尝试：

# First batch of dictionaries:
bonuscolumn_value1 = 'somevalue'
dict1 = {'name':'Sam', 'age':26}
dict2 = {'name':'Albert', 'age':21}
dict3 = {'name':'Brock', 'age':57}
df1 = pd.DataFrame([dict1, dict2, dict3]).assign(bonuscolumn_name=bonuscolumn_value1)
# Second batch of dictionaries:
bonuscolumn_value1 = 'diffvalue'
dict4 = {'name':'Fred', 'age':14}
dict5 = {'name':'Philbert', 'age':20}
df2 = pd.DataFrame([dict4, dict5]).assign(bonuscolumn_name=bonuscolumn_value1)
df = pd.concat([df1, df2], ignore_index=True)

最终输出：

>>> df
name  age bonuscolumn_name
0       Sam   26        somevalue
1    Albert   21        somevalue
2     Brock   57        somevalue
3      Fred   14        diffvalue
4  Philbert   20        diffvalue