通過 matplotlib 圖表繪制 python pandas 數據框並在圖表上繪制點

Question

想在 matplotlib 圖表上繪制以下date和close列，並僅從圖表上的act列繪制BUY和SELL點

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

Answer 1

讀出的數據為pandas數據幀然后刪除不包含所有行BUY或SELL

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()