如何强制matplotlib只显示Y轴上的整数

Question

我可视化的数据只有在整数时才有意义。

即。根据我正在分析的信息的背景，记录的0.2不合理。

如何强制matplotlib仅使用Y轴上的整数。即1,100,5等？不是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')

Answer 1

最灵活的方法是将integer=True指定为默认刻度定位器（MaxNLocator）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，您可以手动设置刻度位置/标签，如Marcin和Joel建议（或使用MultipleLocator）。这样做的缺点是你需要确定哪些刻度位置有意义，而不是让matplotlib根据轴限制选择合理的整数刻度间隔。

Answer 2

强制整数刻度的另一种方法是使用pyplot.locator_params。

使用与接受的答案几乎相同的示例：

import numpy as np
import matplotlib.pyplot as plt

# Plot anything (note the non-integer min-max values)...
x = np.linspace(-0.1, np.pi, 100)
plt.plot(0.5 * x, 22.8 * np.cos(3 * x), color='black')

# use axis={'both', 'x', 'y'} to choose axis
plt.locator_params(axis="both", integer=True, tight=True)

# Just for appearance's sake
plt.margins(0.05)
plt.tight_layout()

plt.show()

Answer 3

您可以按如下方式修改刻度标签/数字。这仅是示例，因为您没有提供任何代码，因此不确定它是否适用于您。

import matplotlib.pyplot as plt

fig, ax = plt.subplots()

fig.canvas.draw()

# just the original labels/numbers and modify them, e.g. multiply by 100
# and define new format for them.
labels = ["{:0.0f}".format(float(item.get_text())*100) 
                for item in ax.get_xticklabels()]


ax.set_xticklabels(labels)

plt.show()

不修改x轴：

修改：

Answer 4

如果只是你要改变的yaxis，一个简单的方法是确定你想要的刻度：

tickpos = [0,1,4,6]

py.yticks(tickpos,tickpos)

会将刻度线设为0,1,4和6.更一般地说

py.yticks([0,1,2,3], ['zero', 1, 'two', 3.0])

将第二个列表的标签放在第一个列表中的位置。如果标签将是yvalue，那么最好使用py.yticks(tickpos,tickpos)版本，以确保每当您更改刻度线的位置时，标签都会得到相同的更改。

更一般地说，金顿的答案会让你告诉pylab只是y轴的整数，但是让它选择滴答的位置。