将数据框转换为具有列表值的字典
问题描述：
假设我有一个 Dataframe df :
Label1 Label2 Label3
key1 col1value1 col2value1
key2 col1value2 col2value2
key3 col1value3 col2value3
dict1 = df.set_index('Label1').to_dict()
当我们有2列时，此方法有效.
This works when we have 2 columns..
预期输出:
my_dict = {key1: [col1value1,col2value1] , key2: [ col1value2,col2value2] , key3:[col1value3,col2value3] }
我可以在数据框 df 上使用to_dict以具有 2个其他列作为值的键，以列表的形式?
Can I use to_dict on Dataframe df to have a key with 2 other columns as values in form of list ??
答
那么您可以使用字典理解和迭代:
Well you could use a dictionary comprehension and iterrows:
print {key:row.tolist() for key,row in df.set_index('Label1').iterrows()}
{'key3': ['col1value3', 'col2value3'],
'key2': ['col1value2', 'col2value2'],
'key1': ['col1value1', 'col2value1']}
此外，我认为以下内容也可以使用:
Also, I think the following will work too:
df = df.set_index('Label1')
print df.T.to_dict(outtype='list')
{'key3': ['col1value3', 'col2value3'],
'key2': ['col1value2', 'col2value2'],
'key1': ['col1value1', 'col2value1']}
截至2017年秋季的更新; outtype不再是关键字参数.改用orient:
Update as of fall 2017; outtype is no longer the keyword argument. Use orient instead:
In [11]: df.T.to_dict(orient='list')
Out[11]:
{'key1': ['col1value1', 'col2value1'],
'key2': ['col1value2', 'col2value2'],
'key3': ['col1value3', 'col2value3']}