通过matplotlib图表绘制python pandas dataframe并在图表上绘制点

Question

想在matplotlib图表上绘制下面的date和close列，并仅从BUY列的SELL列绘制act和date close act 11/06/2019 5.97 BHODL 10/06/2019 5.53 BUY 9/06/2019 5.13 SIT 8/06/2019 4.85 SIT 7/06/2019 4.87 SIT 6/06/2019 4.92 SIT 5/06/2019 4.9 SIT 4/06/2019 5.66 SIT 3/06/2019 5.66 SIT 2/06/2019 5.72 SIT 1/06/2019 5.72 SIT 31/05/2019 5.68 SIT 30/05/2019 6.05 SIT 29/05/2019 4.8 SIT 28/05/2019 4.92 SIT 27/05/2019 4.82 SIT 26/05/2019 4.82 SIT 25/05/2019 4.82 SIT 24/05/2019 4.82 SIT 23/05/2019 4.82 SIT 22/05/2019 4.87 SIT 21/05/2019 4.98 SIT 20/05/2019 4.92 SIT 19/05/2019 4.8 SHRTCLS 18/05/2019 4.61 BCLSHRT 17/05/2019 3.99 BHODL 16/05/2019 3.89 BHODL 15/05/2019 4.51 BHODL 14/05/2019 4.1 BHODL 13/05/2019 3.93 BUY 12/05/2019 3.97 SIT 11/05/2019 4.05 SIT 10/05/2019 4.05 SIT 9/05/2019 4.05 SIT 8/05/2019 3.92 SIT 7/05/2019 3.92 SIT 6/05/2019 3.92 SIT 5/05/2019 2.24 SIT 4/05/2019 2.27 BCLOSE 3/05/2019 2.27 BHODL 2/05/2019 2.27 BHODL 1/05/2019 2.92 BHODL 30/04/2019 2.72 BHODL 29/04/2019 2.69 BHODL 28/04/2019 2.69 BHODL 27/04/2019 4.2 BHODL 26/04/2019 3.95 BHODL 25/04/2019 3.5 BHODL 24/04/2019 3.3 BHODL 23/04/2019 3.33 BHODL 22/04/2019 3.33 BHODL 21/04/2019 3.33 BHODL 20/04/2019 3.55 BHODL 19/04/2019 3 BUY 18/04/2019 2.95 SIT 17/04/2019 2.95 SIT 16/04/2019 3.08 SIT 15/04/2019 3.3 SIT 14/04/2019 3.3 SIT 13/04/2019 3.3 SIT 12/04/2019 3.35 SIT 11/04/2019 3.35 SIT 10/04/2019 2.47 SIT 9/04/2019 2.5 SIT 8/04/2019 3 SIT 7/04/2019 2.99 SHRTCLS 6/04/2019 2.5 BCLSHRT 5/04/2019 2.43 BHODL 4/04/2019 2.37 BHODL 3/04/2019 2.25 BHODL 2/04/2019 2.59 BUY 1/04/2019 2.59 SIT 31/03/2019 3 BCLOSE 30/03/2019 2.75 BUY 29/03/2019 2.77 SIT 28/03/2019 2.77 SIT 27/03/2019 2.66 SIT 26/03/2019 2.72 SIT 25/03/2019 3.19 SIT 24/03/2019 3.42 SHRTCLS 23/03/2019 3.04 BCLSHRT 22/03/2019 2.93 BHODL 21/03/2019 2.93 BHODL 20/03/2019 2.93 BHODL 19/03/2019 2.98 BUY 18/03/2019 3.3 BCLOSE 17/03/2019 3.3 BHODL 16/03/2019 3.3 BHODL 15/03/2019 3.2 BHODL 14/03/2019 3.27 BHODL 13/03/2019 3.48 BHODL 12/03/2019 3.56 BHODL 11/03/2019 3.47 BHODL 10/03/2019 3.45 BHODL 9/03/2019 3.44 BHODL 8/03/2019 3.44 BHODL 7/03/2019 3.5 BUY 6/03/2019 3.85 SIT 5/03/2019 4.55 SIT 4/03/2019 4.38 SIT 3/03/2019 4.17 SIT 2/03/2019 4.22 SHRTCLS 1/03/2019 4.33 BCLSHRT 28/02/2019 4.27 BHODL 27/02/2019 4.33 BHODL 26/02/2019 4.29 BHODL 25/02/2019 4.3 BUY 24/02/2019 4.5 BCLOSE 23/02/2019 4.21 BHODL 22/02/2019 4.58 BHODL 21/02/2019 5 BUY 20/02/2019 5 SIT 19/02/2019 5.29 SIT 18/02/2019 5.57 SIT 17/02/2019 6.65 SIT 16/02/2019 6 SIT 15/02/2019 6.8 SIT 14/02/2019 7 SIT 13/02/2019 6.3 SIT 12/02/2019 7.14 BCLOSE 11/02/2019 7 BUY 10/02/2019 6.51 BCLOSE 9/02/2019 6.6 BUY 8/02/2019 6.3 SIT 7/02/2019 7.15 BCLOSE 6/02/2019 7.1 BHODL 5/02/2019 6 BHODL 4/02/2019 7.1 BHODL 3/02/2019 6.22 BHODL 2/02/2019 6.95 BHODL 1/02/2019 6.77 BUY 31/01/2019 6.79 SIT 30/01/2019 6.52 SIT 29/01/2019 6.55 SIT 28/01/2019 6.31 SIT 27/01/2019 5.5 SHRTCLS 26/01/2019 5.88 BCLSHRT 25/01/2019 4.91 BHODL 24/01/2019 5.5 BHODL 23/01/2019 5.58 BHODL 22/01/2019 5.3 BHODL 21/01/2019 5.88 BUY 20/01/2019 6.28 SIT 19/01/2019 6.3 SIT 18/01/2019 5.94 SIT 17/01/2019 5.6 SHRTCLS 16/01/2019 5.6 BCLSHRT 15/01/2019 5.69 BHODL 14/01/2019 5.87 BHODL 13/01/2019 5.89 BHODL 12/01/2019 5.88 BHODL 11/01/2019 5.5 BHODL 10/01/2019 5.67 BUY 9/01/2019 5.79 SIT 8/01/2019 4.89 SIT 7/01/2019 4.69 SIT 6/01/2019 4.51 SIT 5/01/2019 4.67 SIT 4/01/2019 4.23 SIT 3/01/2019 4.38 SIT 2/01/2019 4.44 SIT 1/01/2019 4.58 BCLOSE 31/12/2018 4.51 BHODL 30/12/2018 5.22 BHODL 29/12/2018 4.95 BUY 28/12/2018 5 BCLOSE 27/12/2018 4.98 BHODL 26/12/2018 5.04 BHODL 25/12/2018 4.88 BUY 24/12/2018 4.99 SIT 23/12/2018 5 SIT 22/12/2018 4.79 SIT 21/12/2018 4.65 SIT 20/12/2018 4.81 SHRTCLS 19/12/2018 5.06 BCLSHRT 18/12/2018 4.98 BHODL 17/12/2018 4.93 BUY 16/12/2018 5.01 BUY 15/12/2018 4.93 SELL 14/12/2018 4.94 BUYCLS 13/12/2018 5 SCLBUY 12/12/2018 4.99 SELL 11/12/2018 5.3 BUYCLS 10/12/2018 5.27 SCLBUY 9/12/2018 5.39 SHODL 8/12/2018 5.26 SHODL 7/12/2018 5.42 SHODL 6/12/2018 5.25 SHODL 5/12/2018 4.83 SELL 4/12/2018 4.79 SIT 3/12/2018 4.96 SIT 2/12/2018 4.91 SIT 1/12/2018 4.78 SIT 30/11/2018 4.83 SIT 29/11/2018 4.54 SIT 28/11/2018 4.73 SIT 27/11/2018 4.84 SIT 26/11/2018 4.93 SIT 25/11/2018 4.84 SIT 24/11/2018 4.88 SIT 23/11/2018 4.9 SIT 22/11/2018 4.89 SIT 21/11/2018 5.04 SCLOSE 20/11/2018 4.99 SELL 点图表

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Answer 1

将数据作为pandas数据帧读取，然后删除所有不包含BUY或SELL的行

df = pd.read_csv(data, sep=';')
df['close'] = df['close'].apply(lambda x: float(x))
df = df[df.act.isin(['BUY', 'SELL'])]

plt.plot(df['date'], df['close'])
plt.show()