python坐标轴刻度设置对数_Python实用之openpyxl坐标轴范围和对数缩放

在使用openpyxl时，坐标轴的调整就难住了小编。经过一番资料搜索，不光解决了这个问题还找到了对数缩放的方法，接下来就让我们一起看看吧~

坐标轴最小和最大值

为了在图表上显示特定区域，可以手动设置坐标轴的最小值和最大值。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")

在某些情况下，如上面代码所示，设置坐标轴范围实际上等同于显示数据的子范围。对于大型数据集，使用Excel或者Open/Libre Office来绘制散点图(可能还有其他)时，选择数据子集方式要比设置坐标轴范围的速度更快。

对数缩放

x轴和y轴都可以对数缩放。对数的基可以设置为任何有效的浮点。如果x轴按对数缩放，则将丢弃区域中的负值。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")

这将生成五个类似的图表：

五张图使用了相同的数据。其中，第一个图未缩放，第二和三张图分别缩放了X和Y轴，第四张图XY轴均进行了缩放，对数基数设置为10；最后的图表XY轴均进行了缩放，但对数的底设置为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。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")

这将生成四个图表，其中每个可能的方向组合的轴如下所示：

小伙伴们可以根据自己的需求，生成不同的图表~如需了解更多python实用知识，点击进入PyThon学习网教学中心。