导语：
本文主要介绍了关于Python实用之openpyxl坐标轴范围和对数缩放的相关知识，包括四坐标对数，以及origin对数坐标轴刻度这些编程知识，希望对大家有参考作用。
使用openpyxl时，坐标轴的调整对编辑器来说比较困难。经过一番数据搜索，我不仅解决了这个问题，还找到了一种对数缩放的方法。一起来看看吧~
坐标轴最小和值
为了在图表上显示特定区域，你可以手动设置轴的最小值和值。
<p><span> from openpyxl import Workbook
from openpyxl.chart import (
ScatterChart,
Reference,
Series,
)
wb = Workbook()
ws = wb.active
ws.append(['X', '1/X'])
for x in range(-10, 11):
if x:
ws.append([x, 1.0 / x])
chart1 = ScatterChart()
chart1.title = "Full Axes"
chart1.x_axis.title = 'x'
chart1.y_axis.title = '1/x'
chart1.legend = None
chart2 = ScatterChart()
chart2.title = "Clipped Axes"
chart2.x_axis.title = 'x'
chart2.y_axis.title = '1/x'
chart2.legend = None
chart2.x_axis.scaling.min = 0
chart2.y_axis.scaling.min = 0
chart2.x_axis.scaling.max = 11
chart2.y_axis.scaling.max = 1.5
x = Reference(ws, min_col=1, min_row=2, max_row=22)
y = Reference(ws, min_col=2, min_row=2, max_row=22)
s = Series(y, xvalues=x)
chart1.append(s)
chart2.append(s)
ws.add_chart(chart1, "C1")
ws.add_chart(chart2, "C15")
wb.save("minmax.xlsx")<br/></span></p>
在某些情况下，如上面的代码所示，设置一个轴范围实际上相当于显示数据的一个子范围。对于大型数据集，当使用 Excel 或 Open/Libre Office 绘制散点图（可能还有其他）时，选择数据子集比设置轴限制更快。
对数缩放
x 和 y 轴都可以对数缩放。对数的底数可以设置为任何有效的浮点数。如果 x 轴是对数缩放的，则该区域的负值将被丢弃。
<p><span> from openpyxl import Workbook
from openpyxl.chart import (
ScatterChart,
Reference,
Series,
)
import math
wb = Workbook()
ws = wb.active
ws.append(['X', 'Gaussian'])
for i, x in enumerate(range(-10, 11)):
ws.append([x, "=EXP(-(($A${row}/6)^2))".format(row = i + 2)])
chart1 = ScatterChart()
chart1.title = "No Scaling"
chart1.x_axis.title = 'x'
chart1.y_axis.title = 'y'
chart1.legend = None
chart2 = ScatterChart()
chart2.title = "X Log Scale"
chart2.x_axis.title = 'x (log10)'
chart2.y_axis.title = 'y'
chart2.legend = None
chart2.x_axis.scaling.logBase = 10
chart3 = ScatterChart()
chart3.title = "Y Log Scale"
chart3.x_axis.title = 'x'
chart3.y_axis.title = 'y (log10)'
chart3.legend = None
chart3.y_axis.scaling.logBase = 10
chart4 = ScatterChart()
chart4.title = "Both Log Scale"
chart4.x_axis.title = 'x (log10)'
chart4.y_axis.title = 'y (log10)'
chart4.legend = None
chart4.x_axis.scaling.logBase = 10
chart4.y_axis.scaling.logBase = 10
chart5 = ScatterChart()
chart5.title = "Log Scale Base e"
chart5.x_axis.title = 'x (ln)'
chart5.y_axis.title = 'y (ln)'
chart5.legend = None
chart5.x_axis.scaling.logBase = math.e
chart5.y_axis.scaling.logBase = math.e
x = Reference(ws, min_col=1, min_row=2, max_row=22)
y = Reference(ws, min_col=2, min_row=2, max_row=22)
s = Series(y, xvalues=x)
chart1.append(s)
chart2.append(s)
chart3.append(s)
chart4.append(s)
chart5.append(s)
ws.add_chart(chart1, "C1")
ws.add_chart(chart2, "I1")
ws.add_chart(chart3, "C15")
ws.add_chart(chart4, "I15")
ws.add_chart(chart5, "F30")
wb.save("log.xlsx")<br/></span></p>
这将生成五个类似的图表：
五张图使用相同的数据。其中，第一张图不缩放，第二张和第三张图分别在X和Y轴上缩放，第四张图的XY轴被缩放，对数底设置为10；最后一张图 XY 轴已缩放，但对数的底数设置为 e。
轴线方向
坐标轴可以
正常显示
，也可以
反向显示
。
轴方向由
orientation
属性控制，
minMax
表示正向，
maxMin
表示反向。
<p><span> from openpyxl import Workbook
from openpyxl.chart import (
ScatterChart,
Reference,
Series,
)
wb = Workbook()
ws = wb.active
ws["A1"] = "Archimedean Spiral"
ws.append(["T", "X", "Y"])
for i, t in enumerate(range(100)):
ws.append([t / 16.0, "=$A${row}*COS($A${row})".format(row = i + 3),
"=$A${row}*SIN($A${row})".format(row = i + 3)])
chart1 = ScatterChart()
chart1.title = "Default Orientation"
chart1.x_axis.title = 'x'
chart1.y_axis.title = 'y'
chart1.legend = None
chart2 = ScatterChart()
chart2.title = "Flip X"
chart2.x_axis.title = 'x'
chart2.y_axis.title = 'y'
chart2.legend = None
chart2.x_axis.scaling.orientation = "maxMin"
chart2.y_axis.scaling.orientation = "minMax"
chart3 = ScatterChart()
chart3.title = "Flip Y"
chart3.x_axis.title = 'x'
chart3.y_axis.title = 'y'
chart3.legend = None
chart3.x_axis.scaling.orientation = "minMax"
chart3.y_axis.scaling.orientation = "maxMin"
chart4 = ScatterChart()
chart4.title = "Flip Both"
chart4.x_axis.title = 'x'
chart4.y_axis.title = 'y'
chart4.legend = None
chart4.x_axis.scaling.orientation = "maxMin"
chart4.y_axis.scaling.orientation = "maxMin"
x = Reference(ws, min_col=2, min_row=2, max_row=102)
y = Reference(ws, min_col=3, min_row=2, max_row=102)
s = Series(y, xvalues=x)
chart1.append(s)
chart2.append(s)
chart3.append(s)
chart4.append(s)
ws.add_chart(chart1, "D1")
ws.add_chart(chart2, "J1")
ws.add_chart(chart3, "D15")
ws.add_chart(chart4, "J15")
wb.save("orientation.xlsx")<br/></span></p>这将为每个可能的方向组合生成四个带有轴的图表，如下所示：
小伙伴们可以根据自己的需求生成不同的图表~更多python实用知识点击进入
。
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