坐標(biāo)軸最小和最大值?
為了在圖表上顯示特定區(qū)域也颤，可以手動(dòng)設(shè)置坐標(biāo)軸的最小值和最大值博脑。
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")
在這里插入圖片描述
在某些情況下，如上面代碼所示，設(shè)置坐標(biāo)軸范圍實(shí)際上等同于顯示數(shù)據(jù)的子范圍奈嘿。對(duì)于大型數(shù)據(jù)集貌虾，使用使用Excel或者Open/Libre Office來(lái)繪制散點(diǎn)圖（可能還有其他）時(shí)，選擇數(shù)據(jù)子集方式要比設(shè)置坐標(biāo)軸范圍的速度更快裙犹。
對(duì)數(shù)縮放?
x軸和y軸都可以對(duì)數(shù)縮放尽狠。對(duì)數(shù)的基可以設(shè)置為任何有效的浮點(diǎn)。如果x軸按對(duì)數(shù)縮放叶圃，則將丟棄區(qū)域中的負(fù)值袄膏。
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(gè)類(lèi)似的圖表：
在這里插入圖片描述
五張圖使用了相同的數(shù)據(jù)。其中掺冠，第一個(gè)圖未縮放沉馆，第二和三張圖分別縮放了X和Y軸码党，第四張圖XY軸均進(jìn)行了縮放，對(duì)數(shù)基數(shù)設(shè)置為10斥黑；最后的圖表XY軸均進(jìn)行了縮放揖盘，但對(duì)數(shù)的底設(shè)置為e。
軸線方向?
坐標(biāo)軸可以正常顯示锌奴，也可以反向顯示兽狭。軸方向由
orientation屬性控制，minMax表示正向鹿蜀，maxMin表示反向箕慧。
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(gè)圖表，其中每個(gè)可能的方向組合的軸如下所示：
在這里插入圖片描述
