我有这本字典
example = {
'view_id_ga_standard_111': {'view_id': '111',
'request_type': 'ga_standard',
'start_date': '2019-07-01',
'end_date': '2019-09-01',
'status': 'New'},
'view_id_ga_standard_333': {'view_id': '333',
'request_type': 'ga_standard',
'start_date': '2019-07-01',
'end_date': '2019-09-01',
'status': 'New'},
'view_id_ga_corporate_222': {'view_id': '222',
'request_type': 'ga_corporate',
'start_date': '2018-07-01',
'end_date': '2018-09-01',
'status': 'New'}
}
并且需要用它制作一个熊猫df,所以看起来像这样
id request_type start_date end_date request_id status
2 111 ga_standard 2019-07-01 2019-09-01 1 New
3 333 ga_standard 2019-07-01 2019-09-01 2 New
5 222 ga_corporate 2018-07-01 2018-09-01 3 New
我结束了这个功能
def ga_make_request_types(params):
vids = []
rtypes = []
sdates = []
edates = []
js = []
statuses = []
j = 0
for k,v in data_for_config.items():
j = j + 1
view_id = v['view_id']
vids.append(view_id)
request_type = v['request_type']
rtypes.append(request_type)
start_date = v['start_date']
sdates.append(start_date)
end_date = v['end_date']
edates.append(end_date)
status = v['status']
statuses.append(status)
js.append(j)
df = pd.DataFrame(zip(vids, rtypes, sdates, edates, js, statuses), columns=['id', 'request_type', 'start_date', 'end_date', 'request_id', 'status'])
return df
但这很丑陋,是否可以通过列表理解来缩短代码?
我已经尝试过这样
for k,v in data_for_config.items():
vids = [v['view_id'] for v in k]
像这样
for k,v in data_for_config.items():
vids = [v['view_id'] for v in data_for_config[k]]
但这会引发错误
TypeError: string indices must be integers
最佳答案
怎么样:
df = pd.DataFrame(example).T
输出:
end_date request_type start_date status view_id
view_id_ga_corporate_222 2018-09-01 ga_corporate 2018-07-01 New 222
view_id_ga_standard_111 2019-09-01 ga_standard 2019-07-01 New 111
view_id_ga_standard_333 2019-09-01 ga_standard 2019-07-01 New 333
编辑:
我不确定如何确定
request_id
,但是您可以执行以下操作:df['request_id'] = range(1, df.shape[0] + 1)
关于python - 如何优化代码以遍历字典并将值存储在列表中?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/58604958/