2012-04-14 26 views
2

我有一個數據集,它看起來低於我可以從文件流入python。 我想用熊貓來創建一個數據的HLOC圖表,每一分鐘從時間零開始是9:46,使用asof方法....我還想知道如何將數據流式傳輸到熊貓數據框中作爲更新。這可能嗎?如何用熊貓創建高低開放關閉圖表

2012-03-15 09:45:00 139.8000 
2012-03-15 09:45:11 139.7900 
2012-03-15 09:45:22 139.7850 
2012-03-15 09:45:33 139.8100 
2012-03-15 09:45:44 139.8000 
2012-03-15 09:45:55 139.8000 
2012-03-15 09:46:06 139.8100 
2012-03-15 09:46:16 139.8500 
2012-03-15 09:46:27 139.8400 
2012-03-15 09:46:38 139.8300 
2012-03-15 09:46:49 139.8000 
2012-03-15 09:46:59 139.8200 
2012-03-15 09:47:10 139.8200 
2012-03-15 09:47:21 139.8500 
2012-03-15 09:47:32 139.8600 
2012-03-15 09:47:42 139.8680 
2012-03-15 09:47:53 139.8600 
2012-03-15 09:48:04 139.8620 
2012-03-15 09:48:15 139.8500 
2012-03-15 09:48:25 139.8600 
2012-03-15 09:48:36 139.8400 
2012-03-15 09:48:47 139.8197 
2012-03-15 09:48:58 139.8200 
2012-03-15 09:49:08 139.8000 
2012-03-15 09:49:19 139.8300 
2012-03-15 09:49:30 139.8199 
2012-03-15 09:49:41 139.8300 
2012-03-15 09:49:52 139.8600 
2012-03-15 09:50:02 139.8600 
2012-03-15 09:50:13 139.8800 
2012-03-15 09:50:24 139.9000 
2012-03-15 09:50:35 139.9200 
2012-03-15 09:50:45 139.9300 
2012-03-15 09:50:56 139.9300 
2012-03-15 09:51:07 139.9290 
2012-03-15 09:51:18 139.9100 
2012-03-15 09:51:28 139.9200 
2012-03-15 09:51:39 139.9200 
2012-03-15 09:51:50 139.9370 
2012-03-15 09:52:01 139.9386 
2012-03-15 09:52:11 139.9400 
2012-03-15 09:52:22 139.9590 
2012-03-15 09:52:33 139.9650 
2012-03-15 09:52:44 139.9600 
2012-03-15 09:52:54 139.9800 
2012-03-15 09:53:05 139.9900 
2012-03-15 09:53:16 139.9800 
2012-03-15 09:53:27 139.9800 
2012-03-15 09:53:37 139.9700 
2012-03-15 09:53:48 139.9900 
2012-03-15 09:53:59 139.9884 
2012-03-15 09:54:10 139.9900 
2012-03-15 09:54:20 139.9900 
2012-03-15 09:54:31 140.0100 
2012-03-15 09:54:42 140.0000 
2012-03-15 09:54:53 139.9850 
2012-03-15 09:55:03 139.9900 
2012-03-15 09:55:14 140.0000 
2012-03-15 09:55:25 140.0090 
2012-03-15 09:55:36 140.0000 
2012-03-15 09:55:47 139.9890 
2012-03-15 09:55:57 139.9900 
2012-03-15 09:56:08 139.9900 
2012-03-15 09:56:19 140.0000 
2012-03-15 09:56:30 140.0400 
2012-03-15 09:56:40 140.0200 
2012-03-15 09:56:51 140.0200 
2012-03-15 09:57:02 140.0300 
2012-03-15 09:57:13 140.0400 
2012-03-15 09:57:23 140.0390 
2012-03-15 09:57:34 140.0300 
2012-03-15 09:57:45 140.0200 
2012-03-15 09:57:56 140.0200 
2012-03-15 09:58:06 140.0400 
2012-03-15 09:58:17 140.0300 
2012-03-15 09:58:28 140.0400 
2012-03-15 09:58:39 140.0300 
2012-03-15 09:58:49 140.0300 
2012-03-15 09:59:00 140.0500 
2012-03-15 09:59:11 140.0400 
2012-03-15 09:59:22 140.0200 
2012-03-15 09:59:32 140.0300 
2012-03-15 09:59:43 140.0300 
2012-03-15 09:59:54 140.0200 
2012-03-15 10:00:05 140.0100 
2012-03-15 10:00:15 140.0100 
2012-03-15 10:00:26 140.0700 
2012-03-15 10:00:37 140.0900 
2012-03-15 10:00:48 140.0899 
2012-03-15 10:00:58 140.0700 
2012-03-15 10:01:09 140.0800 
2012-03-15 10:01:20 140.0300 
2012-03-15 10:01:31 140.0200 
2012-03-15 10:01:41 140.0100 
2012-03-15 10:01:52 139.9800 
2012-03-15 10:02:03 139.9300 
2012-03-15 10:02:14 139.9900 
2012-03-15 10:02:25 140.0200 
2012-03-15 10:02:35 140.0000 
2012-03-15 10:02:46 139.9700 
2012-03-15 10:02:57 139.9300 
2012-03-15 10:03:08 139.9300 
2012-03-15 10:03:18 139.9200 
2012-03-15 10:03:29 139.9700 
2012-03-15 10:03:40 139.9700 
2012-03-15 10:03:51 139.9600 
2012-03-15 10:04:01 139.9700 
2012-03-15 10:04:12 139.9200 
2012-03-15 10:04:23 139.9100 
2012-03-15 10:04:34 139.9200 
2012-03-15 10:04:44 139.9100 
2012-03-15 10:04:55 139.9100 
2012-03-15 10:05:06 139.8900 
2012-03-15 10:05:17 139.9000 
2012-03-15 10:05:27 139.9900 
2012-03-15 10:05:38 139.9700 
2012-03-15 10:05:49 139.9521 
2012-03-15 10:06:00 139.9700 
2012-03-15 10:06:10 139.9800 
2012-03-15 10:06:21 140.0200 
2012-03-15 10:06:32 140.0400 
2012-03-15 10:06:43 140.0400 
2012-03-15 10:06:53 140.0300 
2012-03-15 10:07:04 140.0400 
2012-03-15 10:07:15 139.9893 
2012-03-15 10:07:26 140.0100 
2012-03-15 10:07:36 140.0100 
2012-03-15 10:07:47 140.0010 
2012-03-15 10:07:58 139.9900 
2012-03-15 10:08:09 140.0100 
2012-03-15 10:08:19 139.9800 
2012-03-15 10:08:30 139.9899 
2012-03-15 10:08:41 140.0000 
2012-03-15 10:08:52 140.0000 
2012-03-15 10:09:03 139.9710 
2012-03-15 10:09:13 139.9710 
2012-03-15 10:09:24 139.9700 
2012-03-15 10:09:35 139.9700 
2012-03-15 10:09:46 139.9700 
2012-03-15 10:09:56 139.9614 
2012-03-15 10:10:07 139.9700 
2012-03-15 10:10:18 139.9400 
2012-03-15 10:10:29 139.9100 
2012-03-15 10:10:39 139.9300 
2012-03-15 10:10:50 139.9400 
2012-03-15 10:11:01 139.9800 
2012-03-15 10:11:12 140.0000 
2012-03-15 10:11:22 139.9700 
2012-03-15 10:11:33 139.9400 
2012-03-15 10:11:44 139.8900 
2012-03-15 10:11:55 139.8800 
2012-03-15 10:12:05 139.9000 
2012-03-15 10:12:16 139.9100 
2012-03-15 10:12:27 139.9100 
2012-03-15 10:12:38 139.9000 
2012-03-15 10:12:48 139.9300 
2012-03-15 10:12:59 139.9200 
2012-03-15 10:13:10 139.9300 
2012-03-15 10:13:21 139.9500 
2012-03-15 10:13:31 139.9500 
2012-03-15 10:13:42 139.9700 
2012-03-15 10:13:53 139.9600 
2012-03-15 10:14:04 139.9700 
2012-03-15 10:14:14 139.9400 
2012-03-15 10:14:25 140.0300 

回答

4

在即將到來的大熊貓0.8.0版本(在git的主人可用電流,請報告任何錯誤),你可以這樣做:

In [52]: ts.resample('T', how='ohlc') 
Out[52]: 
         open  low  high  close 
2012-03-15 09:45:00 139.8000 139.8000 139.800 139.8000 
2012-03-15 09:46:00 139.7900 139.7850 139.810 139.8000 
2012-03-15 09:47:00 139.8100 139.8000 139.850 139.8200 
2012-03-15 09:48:00 139.8200 139.8200 139.868 139.8600 
2012-03-15 09:49:00 139.8620 139.8197 139.862 139.8200 
2012-03-15 09:50:00 139.8000 139.8000 139.860 139.8600 
2012-03-15 09:51:00 139.8600 139.8600 139.930 139.9300 
2012-03-15 09:52:00 139.9290 139.9100 139.937 139.9370 
2012-03-15 09:53:00 139.9386 139.9386 139.980 139.9800 
2012-03-15 09:54:00 139.9900 139.9700 139.990 139.9884 
2012-03-15 09:55:00 139.9900 139.9850 140.010 139.9850 
2012-03-15 09:56:00 139.9900 139.9890 140.009 139.9900 
2012-03-15 09:57:00 139.9900 139.9900 140.040 140.0200 
2012-03-15 09:58:00 140.0300 140.0200 140.040 140.0200 
2012-03-15 09:59:00 140.0400 140.0300 140.050 140.0500 
2012-03-15 10:00:00 140.0400 140.0200 140.040 140.0200 
2012-03-15 10:01:00 140.0100 140.0100 140.090 140.0700 
2012-03-15 10:02:00 140.0800 139.9800 140.080 139.9800 
2012-03-15 10:03:00 139.9300 139.9300 140.020 139.9300 
2012-03-15 10:04:00 139.9300 139.9200 139.970 139.9600 
2012-03-15 10:05:00 139.9700 139.9100 139.970 139.9100 
2012-03-15 10:06:00 139.8900 139.8900 139.990 139.9700 
2012-03-15 10:07:00 139.9800 139.9800 140.040 140.0300 
2012-03-15 10:08:00 140.0400 139.9893 140.040 139.9900 
2012-03-15 10:09:00 140.0100 139.9800 140.010 140.0000 
2012-03-15 10:10:00 139.9710 139.9614 139.971 139.9614 
2012-03-15 10:11:00 139.9700 139.9100 139.970 139.9400 
2012-03-15 10:12:00 139.9800 139.8800 140.000 139.8800 
2012-03-15 10:13:00 139.9000 139.9000 139.930 139.9200 
2012-03-15 10:14:00 139.9300 139.9300 139.970 139.9600 
2012-03-15 10:15:00 139.9700 139.9400 140.030 140.0300 

對於OHLC圖,看看這裏:http://matplotlib.sourceforge.net/examples/pylab_examples/finance_demo.html 。我計劃最終爲熊貓添加一個不錯的方法。

+0

我該如何得到0.8.0。請點鏈接。我可以去github,我如何拉開發版本。在上面,我如何更新表新數據而不重新創建整個表。是否有添加到表的方法....思考.....採取新的數據,過程(ts.convert)。 append table..numpy添加到數組。這裏有任何幫助。 – SlyFly 2012-04-16 14:34:10

+0

您可以使用df.append(new_data)追加數據(產生一個新對象),但這不是特別有效 – 2012-04-25 03:18:26