x轴刻度的格式在不同的子图之间不一致。我通过增加空间和格式化日期来尝试操作,但没有任何工作。日期列中的所有记录实际上都是日期。
fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(10,10), sharey='all')
plt.subplots_adjust(hspace = 0.3)
daily_performance[0].plot(x='date', y='return 1 day', kind='line', ax=ax[0,0])
daily_performance[1].plot(x='date', y='return 1 day', kind='line', ax=ax[0,1])
daily_performance[2].plot(x='date', y='return 1 day', kind='line', ax=ax[1,0])
daily_performance[3].plot(x='date', y='return 1 day', kind='line', ax=ax[1,1])
plt.show()
示例数据如下所示:
[ date open hi lo close return 1 day return 3 day \
0 2014-01-13 71.27 71.6000 69.49 70.12 -0.018340 -0.119869
1 2014-01-14 69.90 72.8200 69.58 72.67 0.036366 -0.013038
2 2014-01-15 72.74 73.4100 72.18 73.22 0.007568 0.025059
3 2014-01-16 73.16 73.4975 72.23 73.10 -0.001639 0.042499
4 2014-01-17 73.34 75.4500 73.06 75.42 0.031737 0.037842
return 5 day
0 -0.115986
1 -0.092306
2 -0.080959
3 -0.007198
4 0.055859 ,
date open hi lo close return 1 day return 3 day \
5 2016-02-08 104.67 105.750 98.15 100.44 -0.045066 -0.097817
6 2016-02-09 99.70 101.160 94.01 96.28 -0.041418 -0.123293
7 2016-02-10 97.06 99.495 96.15 96.91 0.006543 -0.078627
8 2016-02-11 95.00 96.570 93.45 94.71 -0.022701 -0.057049
9 2016-02-12 95.51 99.040 94.36 98.63 0.041390 0.024408
return 5 day
5 -0.167302
6 -0.164164
7 -0.129525
8 -0.137589
9 -0.062274 ,
date open hi lo close return 1 day return 3 day \
10 2016-02-09 99.70 101.160 94.01 96.28 -0.041418 -0.123293
11 2016-02-10 97.06 99.495 96.15 96.91 0.006543 -0.078627
12 2016-02-11 95.00 96.570 93.45 94.71 -0.022701 -0.057049
13 2016-02-12 95.51 99.040 94.36 98.63 0.041390 0.024408
14 2016-02-16 100.10 105.480 100.00 104.15 0.055967 0.074708
return 5 day
10 -0.164164
11 -0.129525
12 -0.137589
13 -0.062274
14 0.036937 ,
date open hi lo close return 1 day return 3 day \
15 2016-02-10 97.06 99.495 96.15 96.91 0.006543 -0.078627
16 2016-02-11 95.00 96.570 93.45 94.71 -0.022701 -0.057049
17 2016-02-12 95.51 99.040 94.36 98.63 0.041390 0.024408
18 2016-02-16 100.10 105.480 100.00 104.15 0.055967 0.074708
19 2016-02-17 105.31 107.570 103.32 105.37 0.011714 0.112554
return 5 day
15 -0.129525
16 -0.137589
17 -0.062274
18 0.036937
19 0.094412 ]