Python利用xlsxwriter读写Excel文件(持续补充)

文章目录

    • 前言
    • 例子
      • 读取文本数据
      • 数据写入Excel
        • 1. 简化Demo
        • 2. 设置单元格格式
        • 3. 调用Excel自身的公式
        • 4. 设置数据格式为百分比
        • 5. 插入Excel图表
        • 6. 插入本地图片(如matplotlib画的图)
        • 7. 冻结指定窗口单元格
        • 8. 完整代码
        • 9. Excel文件内容
    • 总结

前言

有时我们要针对一些数据做统计报告,在文件过多亦或数据量大,excel操作重复操作又过多等情况下,我们可以利用Python进行数据分析处理。

例子

读取文本数据

假设有文本数据如下:

201801136 61.0 68.0 60.0
201801137 94.0 64.0 75.0
201801138 88.0 77.0 82.0
201801139 87.0 84.0 72.0
201801140 93.0 69.0 74.0

我们利用python读取并将除了第一列学号外的数据,整理到numpy矩阵中,代码如下:

def read_data(file):
    with open(file, "r") as f:
        id, subject_1, subject_2, subject_3 =[], [], [], []
        for line in f.readlines():
            line = line.strip('\n')  # 去掉列表中每一个元素的换行符
            line = line.split(' ')
            id.append((line[0]))
            subject_1.append(float(line[1]))
            subject_2.append(float(line[2]))
            subject_3.append(float(line[3]))
        row, col = len(subject_1), 3
        table = np.zeros((row, col))
        table[:, 0], table[:, 1], table[:, 2] = subject_1, subject_2, subject_3
        # head = ['subject_1', 'subject_2', 'subject_3']
        # data = pd.DataFrame(table)
        # data.columns = head
        return table

数据写入Excel

1. 简化Demo
def write_excel(file_name):
    workbook = xlsxwriter.Workbook(file_name)
    # 在文件中创建一个名为TEST的sheet,不加名字默认为sheet1
    worksheet = workbook.add_worksheet(u'Score')  
    worksheet.write(0, 0, '数学')
    worksheet.write(1, 1, 521.1314)
    workbook.close()
2. 设置单元格格式
    style = workbook.add_format({
        "fg_color": "yellow",  # 单元格的背景颜色
        "bold": 1,             # 字体加粗
        "align": "center",     # 对齐方式
        "valign": "vcenter",   # 字体对齐方式
        "font_color": "red"    # 字体颜色
    })
    # 在Excel的第r行第c列以style格式写入data[r][c]数据
    worksheet.write(r, c, data[r][c], style)
    worksheet.write_row('B1', head, style_more)  # 写入表头
    # 设置单元格宽度
    width = 20
    worksheet.set_column(0, col, width)
3. 调用Excel自身的公式
    worksheet.write(row, col+1, '=SUM(B6:D6)')
4. 设置数据格式为百分比
    # 设置数据格式为百分比
    style_pre = workbook.add_format({'num_format': '0.000%'})
5. 插入Excel图表
    chart = workbook.add_chart({"type": "column"})
    # column 柱状图
    # area面积图
    # bar 条形图
    # line折现图
    # radar雷达图
    # 5为图表添加数据
    chart.add_series(
        {"name": "成绩",  # 标题
         "categories": "=Score!$b$1:$d$1",  # 统计项名称 工作簿名称+数据
         "values": "=Score!$b$2:$d$2",  # 统计值 工作簿名称+数据
         "line": {"color": "black", "bold": True}  # 柱子边颜色
         }
    )
    worksheet.insert_chart("A11", chart)
6. 插入本地图片(如matplotlib画的图)
    # 6) 插入本地图片(例如用matplotlib画的图)
    x = np.linspace(0, np.pi)
    y = np.sin(x)
    plt.plot(x, y, color='red', marker='+')
    plt.savefig('sin.png')  # 保存图片
    plt.show()
    worksheet.insert_image('D16', 'sin.png')
    
7. 冻结指定窗口单元格
# 冻结第一行和第一列
worksheet.freeze_panes(1, 1)
8. 完整代码
import os
import numpy as np
import pandas as pd
import xlrd
import xlwt
import xlsxwriter
import matplotlib.pyplot as plt


def read_data(file):
    with open(file, "r") as f:
        id, subject_1, subject_2, subject_3 =[], [], [], []
        for line in f.readlines():
            line = line.strip('\n')  # 去掉列表中每一个元素的换行符
            line = line.split(' ')
            id.append((line[0]))
            subject_1.append(float(line[1]))
            subject_2.append(float(line[2]))
            subject_3.append(float(line[3]))
        row, col = len(subject_1), 3
        table = np.zeros((row, col))
        table[:, 0], table[:, 1], table[:, 2] = subject_1, subject_2, subject_3
        # head = ['subject_1', 'subject_2', 'subject_3']
        # data = pd.DataFrame(table)
        # data.columns = head
        return table


def write_excel_demo(file_name):
    workbook = xlsxwriter.Workbook(file_name)
    # 在文件中创建一个名为TEST的sheet,不加名字默认为sheet1
    worksheet = workbook.add_worksheet(u'Test')
    worksheet.write(0, 0, '数学')
    workbook.close()

def write_excel(file_name, data):
    workbook = xlsxwriter.Workbook(file_name)
    # 1)设置单元格格式
    style = workbook.add_format({
        "align": "center",    # 对齐方式
        "valign": "vcenter",  # 字体对齐方式
    })
    style_more = workbook.add_format({
        "fg_color": "yellow",  # 单元格的背景颜色
        "bold": 1,             # 字体加粗
        "align": "center",     # 对齐方式
        "valign": "vcenter",   # 字体对齐方式
        "font_color": "red"    # 字体颜色
    })

    # 2)设置数据格式为百分比
    style_pre = workbook.add_format({'num_format': '0.000%'})

    worksheet = workbook.add_worksheet(u'Score')  # 在文件中创建一个名为Score的sheet,不加名字默认为sheet1
    row, col = len(data), len(data[0, :])
    width = 20
    # 3) 设置单元格宽度
    worksheet.set_column(0, col, width)
    head = ['subject_1', 'subject_2', 'subject_3']
    '''
    for i in range(len(head)):
        worksheet.write(0, i+1, head[i], style_more) 
    '''
    worksheet.write_row('B1', head, style_more)  # 写入表头

    # 7) 冻结第一行和第一列
    worksheet.freeze_panes(1, 1)

    for i in range(row):
        for j in range(col):
            worksheet.write(i+1, j+1, data[i][j], style)
    # 4) 调用Excel自身的公式
    worksheet.write(row, col+1, '=SUM(B6:D6)')

    # 5) 插入Excel图表
    chart = workbook.add_chart({"type": "column"})
    # column 柱状图
    # area面积图
    # bar 条形图
    # line折现图
    # radar雷达图
    # 5为图表添加数据
    chart.add_series(
        {"name": "成绩",  # 标题
         "categories": "=Score!$b$1:$d$1",  # 统计项名称 工作簿名称+数据
         "values": "=Score!$b$2:$d$2",  # 统计值 工作簿名称+数据
         "line": {"color": "black", "bold": True}  # 柱子边颜色
         }
    )
    worksheet.insert_chart("A11", chart)
        
    # 6) 插入本地图片(例如用matplotlib画的图)
    x = np.linspace(0, np.pi)
    y = np.sin(x)
    plt.plot(x, y, color='red', marker='+')
    plt.savefig('sin.png')  # 保存图片
    plt.show()
    worksheet.insert_image('D16', 'sin.png')
    workbook.close()


if __name__ == '__main__':
    file_name = "test.xlsx"
    write_excel_demo(file_name)
    data = read_data("data/score.txt")
    file_name = 'result.xlsx'
    write_excel(file_name, data)
9. Excel文件内容

总结

本文分节详细,一是为了后续查寻方便,二是后续在学习工作中也会持续总结,毕竟熟能生巧,万一一段时间不用,不熟练了也可以回来查找。以上代码和数据都可以去我的GitHub下载。

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