Python 使用XlsxWriter操作Excel

2023-11-24 10:43:47 浏览数 (3)

在数据处理和报告生成的领域中，Excel 文件一直是广泛使用的标准格式。为了让 Python 开发者能够轻松创建和修改 Excel 文件，XlsxWriter 库应运而生。XlsxWriter 是一个功能强大的 Python 模块，专门用于生成 Microsoft Excel 2007及以上版本（.xlsx 格式）的电子表格文件。本文将对XlsxWriter进行概述，探讨其主要特点、用法和一些实际应用，并实现绘制各类图例（条形图，柱状图，饼状图）等。

主要特点

  1. .xlsx 格式支持： XlsxWriter 专注于创建 Microsoft Excel 2007 及以上版本的文件，这是一种基于 XML 的格式，允许存储大量数据、样式和图表。
  2. 格式和样式： XlsxWriter 允许开发者以编程方式设置单元格的格式和样式，包括字体、颜色、对齐方式等。这使得生成的 Excel 文件能够呈现出精美的外观。
  3. 图表和图形： XlsxWriter 支持创建各种类型的图表，如折线图、柱状图、饼图等，使用户能够直观地呈现数据。同时，它还支持插入图片、形状和注释等图形元素。
  4. 公式和函数： XlsxWriter 允许在单元格中使用 Excel 公式和函数，这对于进行复杂的计算和数据分析非常有用。
  5. 大数据量处理： XlsxWriter 被设计为高性能的库，能够处理大规模的数据集，同时保持生成的 Excel 文件的高质量。
  6. 图表和条件格式： 除了基本的单元格样式，XlsxWriter 支持添加条件格式，以及在工作表中插入图表，提供更直观的数据可视化。

安装模块

要开始使用 XlsxWriter，首先需要安装该库。可以通过以下命令使用 pip 安装：

代码语言：javascript复制
pip install XlsxWriter

XlsxWriter 提供了一个强大而灵活的工具，使得使用 Python 生成 Excel 文件变得简单而高效。无论是用于数据分析、报告生成还是其他领域，XlsxWriter 都为开发者提供了一种简单而可靠的方法，使他们能够充分利用 Excel 的强大功能。在掌握了基本用法后，开发者可以深入研究 XlsxWriter 的高级特性，以满足更复杂的需求。

单行输出函数

函数WriteSingleArticle()调用时传入文档名称，以及传入表头和数据，写出简单的单行记录。

代码语言：javascript复制
import xlsxwriter

# 写出数据
def WriteSingleArticle(xls_name,header,data):
    workbook = xlsxwriter.Workbook(xls_name)
    worksheet = workbook.add_worksheet()

    # 定义表格样式
    head_style = workbook.add_format({"bold": True, "align": "center", "border": 1, "fg_color": "#D7E4BC"})
    worksheet.set_column("A1:D1", 15)

    # 写出表头
    worksheet.write_row("A1", header, head_style)
    for index in range(0, len(data)):
        worksheet.write_row("A{}".format(index   2), data[index])

    workbook.close()
    return True

if __name__ == "__main__":
    headings = ["用户名", "密码", "地址"]
    data = [["admin","123456","192.168.1.1"],["admin","123456","192.168.1.1"]]

    ref = WriteSingleArticle("lyshark.xlsx",headings,data)
    print("写出状态: {}".format(ref))

输出效果如下所示；

多行表格输出函数

函数CreateTable(address,data,section)实现了输出一个列表格式的Table，只需传入列表序列即可。

先找到表格生成坐标与大小之间的比值关系，这是第一步，如下是简单的实现固定位置生成表格。

代码语言：javascript复制
import xlsxwriter

# 设置表格sheet名称
workbook = xlsxwriter.Workbook('lyshark.xlsx')
worksheet = workbook.add_worksheet("系统磁盘统计")

# 设置头部标题IP地址列
merge_format = workbook.add_format({'bold': True,'border': 1,'align': 'center','valign': 'vcenter','fg_color': '#EEAEEE'})
worksheet.merge_range('A9:B12', '192.168.1.1', merge_format)

# 设置表格头部提示,并将前两个表头合并为1个
header = ["IP地址","IP地址","路径","总容量","剩余容量","利用率"]
merge_format1 = workbook.add_format({'bold': True,'border': 1,'align': 'center','valign': 'vcenter','fg_color': '#AEEEEE'})
worksheet.write_row("A8:B12",header,merge_format1)        # 显示表头
worksheet.merge_range('A8:B8',"IP地址",merge_format1)      # 合并表头(合并第一个元素)

# 写出路径列表
data1 = ["/etc/system/","/proc/","/sys","/var/lyshark"]
merge_format2 = workbook.add_format({'bold': True,'border': 1,'valign': 'vcenter','fg_color': '#D7E4BC','align': 'center'})
worksheet.write_column("C9",data1,merge_format2)
worksheet.set_column("C9:C9",30)

# 写出总容量
data2 = ["1024 GB","2048 GB","111 GB","1111 GB"]
merge_format3 = workbook.add_format({'bold': True,'border': 1,'valign': 'vcenter','fg_color': '#D7E4BC','align': 'center'})
worksheet.write_column("D9",data2,merge_format3)
worksheet.set_column("D9:D9",20)

# 写出剩余容量
data3 = ["1024 GB","2048 GB","111 GB","22 GB"]
merge_format4 = workbook.add_format({'bold': True,'border': 1,'valign': 'vcenter','fg_color': '#D7E4BC','align': 'center'})
worksheet.write_column("E9",data3,merge_format4)
worksheet.set_column("E9:E9",20)

# 写出利用率
data4= ["10%","50%","20%","33%"]
merge_format5 = workbook.add_format({'bold': True,'border': 1,'valign': 'vcenter','fg_color': '#D7E4BC','align': 'center'})
worksheet.write_column("F9",data4,merge_format5)
worksheet.set_column("F9:F9",20)

workbook.close()

输出效果如下所示；

继续封装如上代码，将其封装为CreateTable(address,data,section)函数，用户传入表头地址，数据集，以及从第几行开始写数据，则自动生成表单。

代码语言：javascript复制
import xlsxwriter

workbook = xlsxwriter.Workbook('lyshark.xlsx')
worksheet = workbook.add_worksheet("统计表")

# 创建表结构
def CreateTable(address,data,section):
    # --------------------------------------------------------------------
    # 计算表头列表长度
    header_count = len(data[1])
    print("不带表头的列表长度: {}".format(header_count))

    merge_format1 = workbook.add_format({'bold': True, 'border': 1, 'align': 'center', 'valign': 'vcenter', 'fg_color': '#AEEEEE'})
    # 根据表格列长度 计算出表格大小
    header_range = f"A{section}:B{section header_count}"
    print("表头总长度 header_range = {}".format(header_range))
    # 写出表头到文件
    worksheet.write_row(header_range, data[0], merge_format1)

    # --------------------------------------------------------------------
    # 计算合并表头偏移,并合并
    header_merge_range = f"A{section}:B{section}"
    print("合并表头偏移 header_merge_range = {}".format(header_merge_range))

    # 合并表头(合并第一个元素)
    header_table = data[0][0]
    worksheet.merge_range(header_merge_range, header_table, merge_format1)
    # worksheet.merge_range(header_merge_range, "IP地址", merge_format1)

    # --------------------------------------------------------------------
    # 计算出表头 所占总单元格大小
    remove_header_count = len(data) - 1
    print("除去表头的列表长度: {}".format(remove_header_count))
    # 此处自己调整列长度
    address_merge_range = f"A{section 1}:B{section    len(data[0][1])}"
    print("所占总单元格大小 address_merge_range = {} => {}".format(len(data[0][1]),address_merge_range))

    merge_format = workbook.add_format({'bold': True, 'border': 1, 'align': 'center', 'valign': 'vcenter', 'fg_color': '#EEAEEE'})

    # 写出单元格合并大小
    worksheet.merge_range(address_merge_range, address , merge_format)

    # --------------------------------------------------------------------
    # 循环填充数据
    merge_format_index = workbook.add_format(
        {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC', 'align': 'center'})

    letter_list = ['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O',
                   'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z']

    # 循环填充数据 最大字段长度为24
    for index in range(0, remove_header_count):
        index_range = f"{letter_list[index]}{section 1}"
        worksheet.write_column(index_range, data[index 1], merge_format_index)

        index_range = f"{letter_list[index]}{section 1}:{letter_list[index]}{section 1}"
        worksheet.set_column(index_range, 30)

    """
        #  不使用循环逐条填充
        merge_format2 = workbook.add_format( {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC', 'align': 'center'})

        index_range = "C{}".format(section 1)
        worksheet.write_column(index_range, data[1], merge_format2)
        index_range = "C{}:C{}".format(section 1,section 1)
        worksheet.set_column(index_range, 30)

        index_range = "D{}".format(section 1)
        worksheet.write_column(index_range, data[2], merge_format2)
        index_range = "D{}:D{}".format(section 1,section 1)
        worksheet.set_column(index_range, 30)

        index_range = "E{}".format(section 1)
        worksheet.write_column(index_range, data[2], merge_format2)
        index_range = "E{}:E{}".format(section 1,section 1)
        worksheet.set_column(index_range, 30)
    """
    # 返回计算后的表格的下两个单元的实际偏移位置
    return section   remove_header_count   3

# 测试恒矩阵
def Test():
    val = 
    [
        ["测试地址", "测试地址","磁盘路径", "总容量", "剩余容量"],
        ["/etc/system/", "/proc/", "/sys", "/user"],
        ["1024 GB", "2048 GB", "12 GB","98 GB"],
        ["1345 GB", "1124 GB", "341 GB", "55 GB"]
    ]

    ref = CreateTable("192.168.1.1",val,1)
    print("返回下一个表格索引: {}".format(ref))

    ref = CreateTable("192.168.1.1",val,ref)
    print("返回下一个表格索引: {}".format(ref))

    workbook.close()

# 测试竖矩阵
def Test2():

    header = ["测试地址", "测试地址","磁盘路径", "总容量", "剩余容量"]

    val = 
    [
        ["/etc/system/", "1024 GB", "256 GB"],
        ["/etc/passwd/", "104 GB", "345GB"],
        ["/etc/username/", "12 GB", "56 GB"],
        ["/etc/lyshark/", "12 GB", "56 GB"]
    ]

    # 横向矩阵转竖向矩阵
    ref_xor = list ( map(list,zip(*val)) )

    # 追加头部
    ref_xor.insert(0, header)
    print(ref_xor)

    ref = CreateTable("192.168.1.1",ref_xor,1)
    print("返回下一个表格索引: {}".format(ref))

    workbook.close()

if __name__ == "__main__":
    Test2()

输出效果如下所示；

柱状图输出函数

简单实现CreateChart(headings,data)柱状图生成函数，通过传入头部标题和数据集列表即可完成表单生成。

代码语言：javascript复制
import xlsxwriter

workbook = xlsxwriter.Workbook('lyshark.xlsx')
worksheet = workbook.add_worksheet("统计表")

def CreateChart(headings,data):
    # 定义表格样式
    head_style = workbook.add_format({"bold": True, "align": "center", "font": 13})

    # 逐条写入数据
    worksheet.write_row("A1", headings, head_style)
    for i in range(0, len(data)):
        worksheet.write_row("A{}".format(i   2), data[i])

    # 添加柱状图
    chart = workbook.add_chart({"type": "column"})
    chart.add_series({
        "name": "=统计表!$B$1",              # 图例项
        "categories": "=统计表!$A$2:$A$10",  # X轴Item名称
        "values": "=统计表!$B$2:$B$10"       # X轴Item值
    })
    chart.add_series({
        "name": "=统计表!$C$1",
        "categories": "=统计表!$A$2:$A$10",
        "values": "=统计表!$C$2:$C$10"
    })
    chart.add_series({
        "name": "=统计表!$D$1",
        "categories": "=统计表!$A$2:$A$10",
        "values": "=统计表!$D$2:$D$10"
    })

    # 添加柱状图标题
    chart.set_title({"name": "性能统计柱状图"})
    chart.set_style(12)

    # 在G2处绘制
    worksheet.insert_chart("G2", chart)
    workbook.close()

if __name__ == "__main__":
    headings = ["主机地址", "CPU利用率", "内存利用率", "交换分区"]
    data = [["192.168.1.100", 88, 36, 66], ["192.168.1.200", 98, 89, 66], ["192.168.1.220", 88, 100, 32]]

    # 循环添加模拟数据
    for i in range(1, 100):
        s = ["192.168.1.{}".format(i), i, i, i]
        data.append(s)

    CreateChart(headings,data)

输出效果如下所示；

条形图输出函数

封装CreateChart(headings,data)函数实现输出条形图，并将前十的数据绘成图展示在右侧。

代码语言：javascript复制
import xlsxwriter

workbook = xlsxwriter.Workbook('lyshark.xlsx')
worksheet = workbook.add_worksheet("统计表")

def CreateChart(headings,data):
    # 定义表格样式
    head_style = workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
    worksheet.set_column("A1:D1", 15)

    # 逐条写入数据
    worksheet.write_row("A1", headings, head_style)
    for i in range(0, len(data)):
        worksheet.write_row("A{}".format(i   2), data[i])

    # 添加条形图，显示前十个元素
    chart = workbook.add_chart({"type": "line"})
    chart.add_series({
        "name": "=统计表!$B$1",              # 图例项
        "categories": "=统计表!$A$2:$A$10",  # X轴Item名称
        "values": "=统计表!$B$2:$B$10"       # X轴Item值
    })
    chart.add_series({
        "name": "=统计表!$C$1",
        "categories": "=统计表!$A$2:$A$10",
        "values": "=统计表!$C$2:$C$10"
    })
    chart.add_series({
        "name": "=统计表!$D$1",
        "categories": "=统计表!$A$2:$A$10",
        "values": "=统计表!$D$2:$D$10"
    })

    # 添加柱状图标题
    chart.set_title({"name": "负载统计条形图"})
    # chart.set_style(8)

    chart.set_size({'width': 1000, 'height': 500})
    chart.set_legend({'position': 'top'})

    # 在F2处绘制
    worksheet.insert_chart("F2", chart)
    workbook.close()

if __name__ == "__main__":
    headings = ["获取时间", "1分钟负载", "5分钟负载", "15分钟负载"]
    data = [["12:01", 0.05, 0.7, 0.006], ["12:02", 0.5, 0.08, 0.06], ["12:03", 0.7, 1, 2.1]]
    CreateChart(headings,data)

输出效果如下所示；

饼状图输出函数

函数CreateChart(headings,data)用于生成饼状图，实现对主机以及主机数量的图形化展示。

代码语言：javascript复制
import xlsxwriter

workbook = xlsxwriter.Workbook('lyshark.xlsx')
worksheet = workbook.add_worksheet("统计表")

def CreateChart(headings,data):
    # 定义表格样式
    head_style = workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
    worksheet.set_column("A1:D1", 15)

    # 逐条写入数据
    worksheet.write_row("A1", headings, head_style)
    for i in range(0, len(data)):
        worksheet.write_row("A{}".format(i   2), data[i])

    # 添加条形图，显示前十个元素
    chart = workbook.add_chart({"type": "pie"})
    chart.add_series({
        "name": "=统计表!$B$1",             # 图例项
        "categories": "=统计表!$A$2:$A$4",  # X轴 Item名称
        "values": "=统计表!$B$2:$B$4"       # X轴Item值
    })

    # 添加饼状图
    chart.set_title({"name": "系统版本分布"})
    chart.set_size({'width': 600, 'height': 300})
    chart.set_legend({'position': 'right'})

    # 在D2处绘制
    worksheet.insert_chart("D2", chart)
    workbook.close()

if __name__ == "__main__":
    headings = ["系统版本", "数量"]
    data = [["Suse", 30], ["Centos", 25], ["AIX", 15]]
    CreateChart(headings,data)

输出效果如下所示；

实现绘图类

通过调用xlsxwriter第三方库,实现绘制各类通用图形,并保存为XLS文档格式.

代码语言：javascript复制
import xlsxwriter

class DrawChart():
    def __init__(self,workbook):
        self.workbook = xlsxwriter.Workbook(workbook)

    # 排序函数,以第三列为条件排列
    def cpu_takeSecond(self,elem):
        return int(elem[3])
    def mem_taskSecond(self,elem):
        return int(elem[1])

    # 封装统计主机磁盘使用情况
    def CreateDiskTable(self,worksheet,address,data,section):
        # 添加统计名称 例如: 磁盘统计
        worksheet = self.workbook.add_worksheet(worksheet)
        merge_format = self.workbook.add_format(
            {'bold': True, 'border': 1, 'align': 'center', 'valign': 'vcenter', 'fg_color': '#EEAEEE'})

        header_count = len(data[1])
        merge_format1 = self.workbook.add_format(
            {'bold': True, 'border': 1, 'align': 'center', 'valign': 'vcenter', 'fg_color': '#AEEEEE'})

        # 根据磁盘路径计算出表格大小
        header_range = "A{}:B{}".format(section,section header_count)
        worksheet.write_row(header_range, data[0], merge_format1)  # 显示表头

        # 计算合并表头偏移
        header_merge_range = "A{}:B{}".format(section,section)
        worksheet.merge_range(header_merge_range, "巡检IP地址", merge_format1)  # 合并表头(合并第一个元素)

        # 计算出地址所占总单元格大小
        address_merge_range = "A{}:B{}".format(section 1,section header_count)
        worksheet.merge_range(address_merge_range, address , merge_format)  #需要计算出来，根据传入分区数量

        # 通过计算得到磁盘路径所对应到表中的位置
        merge_format2 = self.workbook.add_format(
            {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC'})

        index_range = "C{}".format(section 1)
        worksheet.write_column(index_range, data[1], merge_format2)
        index_range = "C{}:C{}".format(section 1,section 1)
        worksheet.set_column(index_range, 30)

        # 计算出总容量对应到表中的位置
        merge_format3 = self.workbook.add_format(
            {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC', 'align': 'center'})

        index_range = "D{}".format(section   1)
        worksheet.write_column(index_range, data[2], merge_format3)

        index_range = "D{}:D{}".format(section   1, section   1)
        worksheet.set_column(index_range, 20)

        # 计算出剩余容量对应到表中的位置
        merge_format4 = self.workbook.add_format(
            {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC', 'align': 'center'})
        index_range = "E{}".format(section   1)
        worksheet.write_column(index_range, data[3], merge_format4)
        index_range = "E{}:E{}".format(section   1, section   1)
        worksheet.set_column(index_range, 20)

        # 计算出利用率对应到表中的位置
        merge_format5 = self.workbook.add_format(
            {'bold': True, 'border': 1, 'valign': 'vcenter', 'fg_color': '#D7E4BC', 'align': 'center'})

        index_range = "F{}".format(section   1)
        worksheet.write_column(index_range, data[4], merge_format5)
        index_range = "F{}:F{}".format(section   1, section   1)
        worksheet.set_column(index_range, 20)

        # 返回计算后的表格的下两个单元的实际偏移位置
        return section   header_count   3

    # 创建CPU利用率百分比,并统计前十
    def CreateCpuUsedTable(self,worksheet,header,data):
        worksheet = self.workbook.add_worksheet(worksheet)

        # 设置头部颜色,并写入头部数据
        head_style = self.workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
        worksheet.write_row("A1", header, head_style)

        # 设置头部列宽
        worksheet.set_column("A1:D1", 15)

        # 排序,统计第三列数据，将最大的放在最前面，以此向下
        data.sort(key=self.cpu_takeSecond, reverse=True)

        # 将数据批量添加到表格中
        for x in range(0,len(data)):
            worksheet.write_row("A{}".format(x   2), data[x])

        # --------------------------------------------------------------
        # 添加柱状图(开始绘图)
        chart = self.workbook.add_chart({"type": "column"})
        chart.add_series({
            "name": "=CPU利用率!$B$1",              # 图例项(也就是CPU内核态)
            "categories": "=CPU利用率!$A$2:$A$10",  # X轴 Item名称
            "values": "=CPU利用率!$B$2:$B$10"       # X轴Item值
        })
        chart.add_series({
            "name": "=CPU利用率!$C$1",
            "categories": "=CPU利用率!$A$2:$A$10",
            "values": "=CPU利用率!$C$2:$C$10"
        })
        chart.add_series({
            "name": "=CPU利用率!$D$1",
            "categories": "=CPU利用率!$A$2:$A$10",
            "values": "=CPU利用率!$D$2:$D$10"
        })

        # 添加柱状图标题
        chart.set_title({"name": "CPU 性能统计柱状图"})
        # chart.set_style(8)

        chart.set_x_axis({
            'major_gridlines': {
                'visible': True,
                'line': {'width': 1.25, 'dash_type': 'dash'}
            },
        })

        chart.set_size({'width': 900, 'height': 500})
        chart.set_legend({'position': 'top'})
        chart.set_table({'show_keys': True})

        # 在F2处绘制
        worksheet.insert_chart("F2", chart)

    # 内存利用率统计
    def CreateMemoryTable(self, worksheet, header, data):
        worksheet = self.workbook.add_worksheet(worksheet)

        # 设置头部颜色,并写入头部数据
        head_style = self.workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
        worksheet.write_row("A1", header, head_style)

        # 设置头部列宽
        worksheet.set_column("A1:D1", 15)

        # 排序,统计第三列数据，将最大的放在最前面，以此向下
        data.sort(key=self.mem_taskSecond, reverse=True)

        # 将数据批量添加到表格中
        for x in range(0,len(data)):
            worksheet.write_row("A{}".format(x   2), data[x])

        # --------------------------------------------------------------
        # 添加柱状图(横向图)
        chart = self.workbook.add_chart({"type": "bar"})
        chart.add_series({
            "name": "=内存利用率!$B$1",
            "categories": "=内存利用率!$A$2:$A$10",
            "values": "=内存利用率!$B$2:$B$10"
        })
        chart.add_series({
            "name": "=内存利用率!$C$1",
            "categories": "=内存利用率!$A$2:$A$10",
            "values": "=内存利用率!$C$2:$C$10"
        })
        # 添加柱状图标题
        chart.set_title({"name": "内存利用率统计图"})
        chart.set_x_axis({
            'major_gridlines': {
                'visible': True,
                'line': {'width': 1.25, 'dash_type': 'dash'}
            },
        })
        chart.set_size({'width': 900, 'height': 400})
        chart.set_legend({'position': 'top'})
        # 在F2处绘制
        worksheet.insert_chart("F2", chart)

    # --------------------------------------------------------------
    # 统计CPU Load 负载情况 注意: 只能指定单独的主机
    def CreateCpuLoadAvgTable(self, address,worksheet, header, data):
        worksheet = self.workbook.add_worksheet(worksheet)

        # 设置头部颜色,并写入头部数据
        head_style = self.workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
        worksheet.write_row("A1", header, head_style)

        # 设置头部列宽
        worksheet.set_column("A1:D1", 15)

        # 将数据批量添加到表格中
        for x in range(0,len(data)):
            worksheet.write_row("A{}".format(x   2), data[x])

        # 定义表格样式
        head_style = self.workbook.add_format({"bold": True, "align": "center", "fg_color": "#D7E4BC"})
        worksheet.set_column("A1:D1", 15)

        # 逐条写入数据
        worksheet.write_row("A1", header, head_style)
        for i in range(0, len(data)):
            worksheet.write_row("A{}".format(i   2), data[i])

        # 添加条形图，显示前十个元素
        chart = self.workbook.add_chart({"type": "line"})
        chart.add_series({
            "name": "=CPU负载数据统计!$B$1",  # 图例项
            "categories": "=CPU负载数据统计!$A$2:$A$10",  # X轴 Item名称
            "values": "=CPU负载数据统计!$B$2:$B$10"  # X轴Item值
        })
        chart.add_series({
            "name": "=CPU负载数据统计!$C$1",  # 第一个线条（图例）
            "categories": "=CPU负载数据统计!$A$2:$A$10",
            "values": "=CPU负载数据统计!$C$2:$C$10"
        })
        chart.add_series({
            "name": "=CPU负载数据统计!$D$1",  # 第二个线条（图例）
            "categories": "=CPU负载数据统计!$A$2:$A$10",
            "values": "=CPU负载数据统计!$D$2:$D$10"
        })

        # 添加柱状图标题
        chart.set_title({"name": "统计地址: {}".format(address)})
        chart.set_size({'width': 900, 'height': 500})
        chart.set_legend({'position': 'top'})

        # 在F2处绘制
        worksheet.insert_chart("F2", chart)

    # 关闭并保存绘制结果
    def Save(self):
        self.workbook.close()

if __name__ == "__main__":
    work = DrawChart("lyshark.xlsx")
    # ------------------------------------------------------------------
    # 统计系统磁盘容量
    disk_val = [
        ["IP地址", "IP地址", "磁盘路径", "总容量", "剩余容量", "利用率"],
        ["/etc/system/", "/proc/", "/sys", "/abc/lyshark"],
        ["1024GG", "2048GB", "111GB", "1111GB"],
        ["1024GG", "2048GB", "111GB", "22GB"],
        ["10%", "50%", "20%", "33%"]
    ]
    ref = work.CreateDiskTable("磁盘分区统计","127.0.0.1",disk_val,3)
    print("下个表格开头位置: {}".format(ref))
    print("[ ] 磁盘数据统计完成")

    # -------------------------------------------------------------------
    # 统计系统CPU负载情况
    header = ["主机地址", "CPU内核态", "CPU用户态", "总利用率"]
    cpu_val = [
        ["192.168.1.100", 88, 36, 100],
        ["192.168.1.200", 98, 89, 128],
        ["192.168.1.220", 88, 100, 190]
    ]
    ref = work.CreateCpuUsedTable("CPU利用率",header,cpu_val)
    print("[ ] CPU利用率统计已完成")

    # -------------------------------------------------------------------
    # 统计系统内存利用率数据
    header = ["主机地址", "通用内存利用率", "交换内存利用率"]
    mem_val = [
        ["192.168.1.100", 25, 35],
        ["192.168.1.200", 44, 57],
        ["192.168.1.200", 24, 21],
        ["192.168.1.200", 78, 89]
    ]
    ref = work.CreateMemoryTable("内存利用率",header,mem_val)
    print("[ ] 内存利用率统计已完成")

    # -------------------------------------------------------------------
    # 获取CPU LoadAvg负载情况
    header = ["拉取日期","1分钟负载","5分钟负载","15分钟负载"]
    cpu_avg_val = [
        ["12:11",0.1,0.2,1.3],
        ["12:12",1.4,3.3,6.9],
        ["12:13",2.6,3.2,6.9]
    ]
    ref = work.CreateCpuLoadAvgTable("127.0.0.1","CPU负载数据统计",header,cpu_avg_val)
    print("[ ] CPU负载统计完成")
    work.Save()

输出效果如下所示；

python excel xlsxwriter 数据 统计

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