使用set_xlim
时出现问题。 (可能是因为datetime对象?)
这是我的代码(在ipython notebook中执行):
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import datetime
date_list = [datetime.datetime(2015, 6, 20, 0, 0), datetime.datetime(2015, 6, 21, 0, 0), datetime.datetime(2015, 6, 22, 0, 0), datetime.datetime(2015, 6, 23, 0, 0), datetime.datetime(2015, 6, 24, 0, 0), datetime.datetime(2015, 6, 25, 0, 0), datetime.datetime(2015, 6, 26, 0, 0)]
count_list = [11590, 10743, 27369, 31023, 30569, 31937, 30205]
fig=plt.figure(figsize=(10,3.5))
ax=fig.add_subplot(111)
width = 0.8
tickLocations = np.arange(7)
ax.set_title("Turnstiles Totals for Lexington Station C/A A002 Unit R051 from 6/20/15-6/26-15")
ax.bar(date_list, count_list, width, color='wheat', edgecolor='#8B7E66', linewidth=4.0)
ax.set_xticklabels(date_list, rotation = 315, horizontalalignment = 'left')
这给了我:
但是当我尝试用这段代码在最左边和最右边做一些额外的空间时:
ax.set_xlim(xmin=-0.6, xmax=0.6)
我收到了这个巨大的错误(这只是底部片段):
223 tz = _get_rc_timezone()
224 ix = int(x)
--> 225 dt = datetime.datetime.fromordinal(ix)
226 remainder = float(x) - ix
227 hour, remainder = divmod(24 * remainder, 1)
ValueError: ordinal must be >= 1
知道发生了什么事吗?谢谢!
答案 0 :(得分:4)
由于各种历史原因,matplotlib在幕后使用内部数字日期格式。实际的x值是这种数据格式,其中0.0是1900年1月1日,差值1.0对应于1天。不允许使用负值。
您获得的错误是因为您尝试将x限制设置为包含负范围。尽管如此,即使没有负数,它也将是1900年1月1日的范围。
无论如何,听起来你想要的并不是ax.set_xlim
。尝试ax.margins(x=0.05)
在x方向上添加5%的填充。
举个例子:
import matplotlib.pyplot as plt
import numpy as np
import datetime
count_list = [11590, 10743, 27369, 31023, 30569, 31937, 30205]
date_list = [datetime.datetime(2015, 6, 20, 0, 0),
datetime.datetime(2015, 6, 21, 0, 0),
datetime.datetime(2015, 6, 22, 0, 0),
datetime.datetime(2015, 6, 23, 0, 0),
datetime.datetime(2015, 6, 24, 0, 0),
datetime.datetime(2015, 6, 25, 0, 0),
datetime.datetime(2015, 6, 26, 0, 0)]
fig, ax = plt.subplots(figsize=(10,3.5))
ax.set_title("Turnstiles Totals for Lexington Station C/A A002 Unit R051 from "
"6/20/15-6/26-15")
# The only difference is the align kwarg: I've centered the bars on each date
ax.bar(date_list, count_list, align='center', color='wheat',
edgecolor='#8B7E66', linewidth=4.0)
# This essentially just rotates the x-tick labels. We could have done
# "fig.autofmt_xdate(rotation=315, ha='left')" to match what you had.
fig.autofmt_xdate()
# Add the padding that you're after. This is 5% of the data limits.
ax.margins(x=0.05)
plt.show()
请注意,如果您想在每个方向上将x限制扩展到0.6,那么您可以执行以下操作:
xmin, xmax = ax.get_xlim()
ax.set_xlim([xmin - 0.6, xmax + 0.6])
但是,ax.margins(percentage)
只要您对“当前轴限制的比率”中的“填充”没问题就会更容易。