我在Pandas中有一个DataFrame
PRICE Name PER CATEGORY STORENAME
0 9.99 MF gram Indica Store1
1 9.99 HY gram Herb Store2
2 9.99 FF gram Herb Store2
我想要做的是将它们分成多个数据框以具有唯一的名称,然后分成那些分类.
当前代码:
names = df['STORENAME'].unique().tolist() #find unique values
store1 = df[df['STORENAME']==names[0]]
store2 = df[df['STORENAME']==names[1]]
这段代码完美无缺,但我想知道是否有Pythonic方式,因为商店的数量可能会改变.
这需要绘制商店中类别的价格差异.
谢谢!
我正在尝试从 url 读取 xls 文件：
使用请求：
page = requests.get(url) # xls url
df = pd.read_excel(page.content,engine = 'xlrd') #engine is passed
File "f:\python36\lib\site-packages\pandas\util\_decorators.py", line 118, in wrapper
return func(*args, **kwargs)
File "f:\python36\lib\site-packages\pandas\io\excel.py", line 230, in read_excel
io = ExcelFile(io, engine=engine)
File "f:\python36\lib\site-packages\pandas\io\excel.py", line 296, in __init__
raise ValueError('Must explicitly set engine if not passing in'
ValueError: Must explicitly set engine if not passing in buffer or path for io.
# if i put in random engine name it throws an unsupported …我有一个Python列表:
data = ['Cost', '$', 4244, '$', 4090, '$', 3967]
我想要做的是合并$前面的元素并获得一个新的列表:
data = ['Cost', '$4244', '$4090', '$3967']
实现这一目标的最佳方法是什么？