我有一个看起来像这样的数据框:
0 1 2
0 April 0.002745 ADANIPORTS.NS
1 July 0.005239 ASIANPAINT.NS
2 April 0.003347 AXISBANK.NS
3 April 0.004469 BAJAJ-AUTO.NS
4 June 0.006045 BAJFINANCE.NS
5 June 0.005176 BAJAJFINSV.NS
6 April 0.003321 BHARTIARTL.NS
7 November 0.003469 INFRATEL.NS
8 April 0.002667 BPCL.NS
9 April 0.003864 BRITANNIA.NS
10 April 0.005570 CIPLA.NS
11 October 0.000925 COALINDIA.NS
12 April 0.003666 DRREDDY.NS
13 April 0.002836 EICHERMOT.NS
14 April 0.003793 GAIL.NS
15 April 0.003850 GRASIM.NS
16 April 0.002858 HCLTECH.NS
17 December 0.005666 HDFC.NS
18 April 0.003484 HDFCBANK.NS
19 April 0.004173 HEROMOTOCO.NS
20 April 0.006395 HINDALCO.NS
21 June 0.001844 HINDUNILVR.NS
22 October 0.004620 ICICIBANK.NS
23 April 0.004020 INDUSINDBK.NS
24 January 0.002496 INFY.NS
25 September 0.001835 IOC.NS
26 May 0.002290 ITC.NS
27 April 0.005910 JSWSTEEL.NS
28 April 0.003570 KOTAKBANK.NS
29 May 0.003346 LT.NS
30 April 0.006131 M&M.NS
31 April 0.003912 MARUTI.NS
32 March 0.003596 NESTLEIND.NS
33 April 0.002180 NTPC.NS
34 April 0.003209 ONGC.NS
35 June 0.001796 POWERGRID.NS
36 April 0.004182 RELIANCE.NS
37 April 0.004246 SHREECEM.NS
38 October 0.004836 SBIN.NS
39 April 0.002596 SUNPHARMA.NS
40 April 0.004235 TCS.NS
41 April 0.006729 TATAMOTORS.NS
42 October 0.003395 TATASTEEL.NS
43 August 0.002440 TECHM.NS
44 June 0.003481 TITAN.NS
45 April 0.003749 ULTRACEMCO.NS
46 April 0.005854 UPL.NS
47 April 0.004991 VEDL.NS
48 July 0.001627 WIPRO.NS
49 April 0.003728 ZEEL.NS
我如何创建多索引数据框,该数据框将在groupby
列中0
。当我这样做时:
new.groupby([0])
Out[315]: <pandas.core.groupby.generic.DataFrameGroupBy object at 0x0A938BB0>
我无法将所有月份归为一类。
答案 0 :(得分:1)
根据您的信息,我建议以下内容:
#rename columns to make useful
new = new.rename(columns={0:'Month',1:'Price', 2:'Ticker'})
new.groupby(['Month','Ticker'])['Price'].sum()
请注意-您应将“月”更改为日期时间,否则顺序将不合逻辑。
另外,documentation对于熊猫来说非常强大。