Python：来自 dict 系列的 Pandas 数据框
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Python: Pandas dataframe from Series of dict
提问by makambi
I have a Pandas dataframe:
我有一个Pandas数据框：
type(original)
pandas.core.frame.DataFrame
which includes the series object original['user']:
其中包括系列对象original['user']：
type(original['user'])
pandas.core.series.Series
original['user']points to a number of dicts:
original['user']指向一些字典：
type(original['user'].ix[0])
dict
Each dict has the same keys:
每个字典都有相同的键：
original['user'].ix[0].keys()
[u'follow_request_sent',
u'profile_use_background_image',
u'profile_text_color',
u'id',
u'verified',
u'profile_location',
# ... keys removed for brevity
]
Above is (part of) one of the dicts of userfields in a tweet from tweeter API. I want to build a data frame from these dicts.
以上是user来自推文API的推文中字段的（部分）字典之一。我想从这些字典中构建一个数据框。
When I try to make a data frame directly, I get only one column for each row and this column contains the whole dict:
当我尝试直接制作数据框时，每行只有一列，而该列包含整个字典：
pd.DataFrame(original['user'][:2])
user
0 {u'follow_request_sent': False, u'profile_use_...
1 {u'follow_request_sent': False, u'profile_use_..
When I try to create a data frame using from_dict() I get the same result:
当我尝试使用 from_dict() 创建数据框时，我得到相同的结果：
pd.DataFrame.from_dict(original['user'][:2])
user
0 {u'follow_request_sent': False, u'profile_use_...
1 {u'follow_request_sent': False, u'profile_use_..
Next I tried a list comprehension which returned an error:
接下来我尝试了一个返回错误的列表理解：
item = [[k, v] for (k,v) in users]
ValueError: too many values to unpack
When I create a data frame from a single row, it nearly works:
当我从单行创建数据框时，它几乎可以工作：
df = pd.DataFrame.from_dict(original['user'].ix[0])
df.reset_index()
index contributors_enabled created_at default_profile default_profile_image description entities favourites_count follow_request_sent followers_count following friends_count geo_enabled id id_str is_translation_enabled is_translator lang listed_count location name notifications profile_background_color profile_background_image_url profile_background_image_url_https profile_background_tile profile_image_url profile_image_url_https profile_link_color profile_location profile_sidebar_border_color profile_sidebar_fill_color profile_text_color profile_use_background_image protected screen_name statuses_count time_zone url utc_offset verified
0 description False Mon May 26 11:58:40 +0000 2014 True False {u'urls': []} 0 False 157
It works almost like I want it to, except it sets the descriptionfield as the default index.
它几乎像我想要的那样工作，除了它将description字段设置为默认索引。
Each of the dicts has 40 keys but I only need about 10 of them and I have 28734 rows in data frame.
每个字典都有 40 个键，但我只需要大约 10 个键，并且我在数据框中有 28734 行。
How can I filter out the keys which I do not need?
如何过滤掉不需要的键？
采纳答案by Eyad
what I would try to do is the following:
我会尝试做的是以下内容：
new_df = pd.DataFrame(list(original['user']))
this will convert the series to list then pass it to pandas dataframe and it should take care of the rest.
这会将系列转换为列表，然后将其传递给 Pandas 数据框，它应该负责其余的工作。
