品易云推流 关闭
文章详情页
文章 > Python基础教程 > Python实用之openpyxl坐标轴范围和对数缩放

Python实用之openpyxl坐标轴范围和对数缩放

头像

2020-10-27 17:15:315073浏览 · 0收藏 · 0评论

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

关注

关注公众号,随时随地在线学习

本教程部分素材来源于网络,版权问题联系站长!

底部广告图