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Python openpyxl 插入折线图实例

【字号: 日期:2022-07-29 15:41:41浏览:4作者:猪猪

我就废话不多说了,还是直接看代码吧!

import osimport openpyxlfrom datetime import datefrom openpyxl import Workbookfrom openpyxl.chart import ( Series, LineChart, Reference,)def add_line_chart(title, wss, min_col, min_row, max_col, max_row): c1 = LineChart() c1.title = title # 图的标题 c1.style = 12 # 线条的style c1.y_axis.title = ’percent’ # y坐标的标题 if ’IDC’ not in title: c1.x_axis.number_format = ’d-mmm’ # 规定日期格式 这是月,年格式 c1.x_axis.majorTimeUnit = 'Months' # 规定日期间隔 注意days;Months大写 c1.x_axis.title = 'Date' # x坐标的标题 data = Reference(wss, min_col=min_col, min_row=min_row, max_col=max_col, max_row=max_row) # 图像的数据 起始行、起始列、终止行、终止列 c1.add_data(data, titles_from_data=True, from_rows=True) dates = Reference(wss, min_col=2, min_row=1, max_col=max_col) c1.set_categories(dates) wss.add_chart(c1, 'A6') # 将图表添加到 sheet中def save_data_to_excel(file_name, target_sheet_name): select_cursor = connect.cursor() select_sql = 'select phone_company, record_date, record_percent from phone_statistics where record_company = ’%s’' % target_sheet_name if target_sheet_name == 'IDC': select_sql = 'select phone_company, record_q, record_percent from phone_statistics where record_company = ’%s’' % target_sheet_name select_cursor.execute(select_sql, ()) data_dic = {} all_date = {} all_phone_company = {} for item in select_cursor: if target_sheet_name == 'IDC': data_dic[item[0] + ’_’ + item[1]] = item[2] else: if type(item[1]) == str: data_dic[item[0] + ’_’ + item[1]] = item[2] else: data_dic[item[0] + ’_’ + item[1].strftime('%Y-%m-%d')] = item[2] all_date[item[1]] = 1 all_phone_company[item[0]] = 1 if os.path.exists(file_name): wb = openpyxl.load_workbook(file_name) else: wb = Workbook() try: wb.remove_sheet(wb[’Sheet’]) except Exception as e: pass try: wb.remove_sheet(wb[target_sheet_name]) except Exception as e: pass try: sheet = wb[target_sheet_name] except Exception as e: sheet = wb.create_sheet() start_date_index = ’B’ for each_date in all_date.keys(): if target_sheet_name == 'IDC': sheet[’%s1’ % start_date_index] = each_date else: if type(each_date) == str: sheet[’%s1’ % start_date_index] = each_date else: sheet[’%s1’ % start_date_index] = each_date.strftime('%Y-%m-%d') start_date_index = chr(ord(start_date_index) + 1) start_name_index = 2 for each_name in all_phone_company.keys(): sheet[’A%d’ % start_name_index] = each_name start_name_index += 1 start_date_index = ’B’ start_name_index = 2 for each_date in all_date.keys(): for each_name in all_phone_company.keys(): if target_sheet_name == 'IDC': key = each_name + ’_’ + each_date if key in data_dic: sheet[’%s%d’ % (start_date_index, start_name_index)] = data_dic[key] else: if type(each_date) == str: key = each_name + ’_’ + each_date else: key = each_name + ’_’ + each_date.strftime('%Y-%m-%d') if key in data_dic: sheet[’%s%d’ % (start_date_index, start_name_index)] = data_dic[key] start_name_index += 1 start_date_index = chr(ord(start_date_index) + 1) start_name_index = 2 sheet.title = target_sheet_name sheet.column_dimensions[’A’].width = 20 start_date_index = ’B’ for each_date in all_date.keys(): sheet.column_dimensions[start_date_index].width = 13 start_date_index = chr(ord(start_date_index) + 1) add_line_chart(target_sheet_name.upper() + '’s Phone Statistics', sheet, 1, 2, len(all_date.keys()) + 1, min(15, len(all_phone_company.keys()) + 1)) wb.save(file_name) pass

Python openpyxl 插入折线图实例

补充知识:python plotly line chart 折线图

我就废话不多说了,还是直接看代码吧!

# 1 折线图数据# trace1 - 基本格式# trace2 - 更多参数trace1 = go.Scatter( x = x1, y = y2,)trace2 = go.Scatter( x = x2, y = y2, mode = ’lines’, # 模式:lines 线,markers 点。可用“+”相连 name = ’line2’, # 折线名,显示于图例 connectgaps = True # 连接缺失点两端 默认False line = dict( color = (’rgb(205, 12, 24)’), # 颜色 width = 4, #线宽 dash = ’dash’) # 虚线: dash 一一,dot ···,dashdot 一·一) )# 2 打包数据data = [trace1,trace2]# 3 格式layout = dict(title = ’折线’, xaxis = dict(title = ’时间’), # 横轴坐标 yaxis = dict(title = ’数量’), # 总轴坐标 legend=dict(x=1.1,y=1) # 图例位置 )# 4 打包数据+格式fig = dict(data=data, layout=layout)# 5 画图py.iplot(fig, filename=’styled-line’)

以上这篇Python openpyxl 插入折线图实例就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持好吧啦网。

标签: Python 编程
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