在工作表上按特定顺序排列列或行中的数据可以在股价图中显示。顾名思义，股价图表最常用来说明股票价格的波动。但此图表也可用于科学数据。例如，可以使用股价图来指示日或年温度的波动。为来创建创建股价图，必须按正确的顺序组织数据。 股价图的数据在工作表中的排列方式非常重要。对于例如，要创建一个简单的盘高-盘低-收盘股价图，您应该按该顺序排列数据，将盘高、盘低和收盘作为列标题输入。 尽管股价图是一种不同的类型，但各种类型只是特定格式选项的快捷方式：
盘高-盘低-收盘图基本上是一个没有直线的折线图，并且标记到XYZ。设置hiLoLines为True。开盘-盘高-盘低-收盘图与盘高-盘低-收盘图相同，每个数据点的标记设置为XZZ和upDownLines。 成交量可以通过组合股价图和成交量条形图来实现。 from datetime import date from openpyxl import Workbook from openpyxl.chart import ( BarChart, StockChart, Reference, Series, ) from openpyxl.chart.axis import DateAxis, ChartLines from openpyxl.chart.updown_bars import UpDownBars wb = Workbook() ws = wb.active rows = [ ['Date', 'Volume','Open', 'High', 'Low', 'Close'], ['2015-01-01', 20000, 26.2, 27.20, 23.49, 25.45, ], ['2015-01-02', 10000, 25.45, 25.03, 19.55, 23.05, ], ['2015-01-03', 15000, 23.05, 24.46, 20.03, 22.42, ], ['2015-01-04', 2000, 22.42, 23.97, 20.07, 21.90, ], ['2015-01-05', 12000, 21.9, 23.65, 19.50, 21.51, ], ] for row in rows: ws.append(row) # High-low-close c1 = StockChart() labels = Reference(ws, min_col=1, min_row=2, max_row=6) data = Reference(ws, min_col=4, max_col=6, min_row=1, max_row=6) c1.add_data(data, titles_from_data=True) c1.set_categories(labels) for s in c1.series: s.graphicalProperties.line.noFill = True # marker for close s.marker.symbol = "dot" s.marker.size = 5 c1.title = "High-low-close" c1.hiLowLines = ChartLines() # Excel is broken and needs a cache of values in order to display hiLoLines :-/ from openpyxl.chart.data_source import NumData, NumVal pts = [NumVal(idx=i) for i in range(len(data) - 1)] cache = NumData(pt=pts) c1.series[-1].val.numRef.numCache = cache ws.add_chart(c1, "A10") # Open-high-low-close c2 = StockChart() data = Reference(ws, min_col=3, max_col=6, min_row=1, max_row=6) c2.add_data(data, titles_from_data=True) c2.set_categories(labels) for s in c2.series: s.graphicalProperties.line.noFill = True c2.hiLowLines = ChartLines() c2.upDownBars = UpDownBars() c2.title = "Open-high-low-close" # add dummy cache c2.series[-1].val.numRef.numCache = cache ws.add_chart(c2, "G10") # Create bar chart for volume bar = BarChart() data = Reference(ws, min_col=2, min_row=1, max_row=6) bar.add_data(data, titles_from_data=True) bar.set_categories(labels) from copy import deepcopy # Volume-high-low-close b1 = deepcopy(bar) c3 = deepcopy(c1) c3.y_axis.majorGridlines = None c3.y_axis.title = "Price" b1.y_axis.axId = 20 b1.z_axis = c3.y_axis b1.y_axis.crosses = "max" b1 += c3 c3.title = "High low close volume" ws.add_chart(b1, "A27") ## Volume-open-high-low-close b2 = deepcopy(bar) c4 = deepcopy(c2) c4.y_axis.majorGridlines = None c4.y_axis.title = "Price" b2.y_axis.axId = 20 b2.z_axis = c4.y_axis b2.y_axis.crosses = "max" b2 += c4 ws.add_chart(b2, "G27") wb.save("stock.xlsx")由于Excel中的问题，只有当至少一个数据系列具有一些伪值时，才会显示高低行。这可以通过以下方法完成：
from openpyxl.chart.data_source import NumData, NumVal pts = [NumVal(idx=i) for i in range(len(data) - 1)] cache = NumData(pt=pts) c1.series[-1].val.numRef.numCache = cache