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在使用openpyxl時，坐標(biāo)軸的調(diào)整就難住了小編。經(jīng)過一番資料搜索，不光解決了這個問題還找到了對數(shù)縮放的方法，接下來就讓我們一起看看吧~
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坐標(biāo)軸最小和值
為了在圖表上顯示特定區(qū)域，可以手動設(shè)置坐標(biāo)軸的最小值和值。
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")
在某些情況下，如上面代碼所示，設(shè)置坐標(biāo)軸范圍實際上等同于顯示數(shù)據(jù)的子范圍。對于大型數(shù)據(jù)集，使用Excel或者Open/Libre Office來繪制散點(diǎn)圖（可能還有其他）時，選擇數(shù)據(jù)子集方式要比設(shè)置坐標(biāo)軸范圍的速度更快。
對數(shù)縮放
x軸和y軸都可以對數(shù)縮放。對數(shù)的基可以設(shè)置為任何有效的浮點(diǎn)。如果x軸按對數(shù)縮放，則將丟棄區(qū)域中的負(fù)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")
這將生成五個類似的圖表：
五張圖使用了相同的數(shù)據(jù)。其中，第一個圖未縮放，第二和三張圖分別縮放了X和Y軸，第四張圖XY軸均進(jìn)行了縮放，對數(shù)基數(shù)設(shè)置為10；最后的圖表XY軸均進(jìn)行了縮放，但對數(shù)的底設(shè)置為e。
軸線方向
坐標(biāo)軸可以正常顯示，也可以反向顯示。
軸方向由orientation屬性控制，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")
這將生成四個圖表，其中每個可能的方向組合的軸如下所示：
小伙伴們可以根據(jù)自己的需求，生成不同的圖表~如需了解更多python實用知識，點(diǎn)擊進(jìn)入PyThon學(xué)習(xí)網(wǎng)教學(xué)中心。
名稱欄目：創(chuàng)新互聯(lián)Python教程：Python實用之openpyxl坐標(biāo)軸范圍和對數(shù)縮放
轉(zhuǎn)載源于：http://www.5511xx.com/article/cddgdci.html
