我正在可视化的数据只有当它是整数时才有意义。
就我分析的信息而言，记录的0.2没有意义。
如何强制Matplotlib只使用Y轴上的整数。即1、100、5等？非0.1、0.2等for a in account_list:
f = plt.figure()
f.set_figheight(20)
f.set_figwidth(20)
f.sharex = True
f.sharey=True
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = .8 # the amount of height reserved for white space between subplots
subplots_adjust(left=left, right=right, bottom=bottom, top=top, wspace=wspace, hspace=hspace)
count = 1
for h in headings:
sorted_data[sorted_data.account == a].ix[0:,['month_date',h]].plot(ax=f.add_subplot(7,3,count),legend=True,subplots=True,x='month_date',y=h)
#set bottom Y axis limit to 0 and change number format to 1 dec place.
axis_data = f.gca()
axis_data.set_ylim(bottom=0.)
from matplotlib.ticker import FormatStrFormatter
axis_data.yaxis.set_major_formatter(FormatStrFormatter('%.0f'))
#This was meant to set Y axis to integer???
y_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
axis_data.yaxis.set_major_formatter(y_formatter)
import matplotlib.patches as mpatches
legend_name = mpatches.Patch(color='none', label=h)
plt.xlabel("")
ppl.legend(handles=[legend_name],bbox_to_anchor=(0.,1.2,1.0,.10), loc="center",ncol=2, mode="expand", borderaxespad=0.)
count = count + 1
savefig(a + '.png', bbox_inches='tight')
最佳答案
最灵活的方法是指定默认勾号定位器(integer=True)执行与此类似的操作：import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
fig, ax = plt.subplots()
# Be sure to only pick integer tick locations.
for axis in [ax.xaxis, ax.yaxis]:
axis.set_major_locator(ticker.MaxNLocator(integer=True))
# Plot anything (note the non-integer min-max values)...
x = np.linspace(-0.1, np.pi, 100)
ax.plot(0.5 * x, 22.8 * np.cos(3 * x), color='black')
# Just for appearance's sake
ax.margins(0.05)
ax.axis('tight')
fig.tight_layout()
plt.show()
或者，您可以手动将勾号位置/标签设置为Marcin和Joel Suggest(或使用)。这样做的缺点是，您需要计算出什么记号位置是有意义的，而不是让matplotlib根据轴限制选择一个合理的整数记号间隔。