用 Python 将 Excel 表格转成可视化图形
< 返回列表时间: 2020-06-17来源:OSCHINA
大家知道,考研很大一部分也是考信息收集能力。每年往往有很多人就是在这上面栽跟头了,不能正确分析各大院校往年的录取信息,进而没能选择合适的报考院校。
至于很多院校的录取信息是以 PDF 形式发布,例如我手上的深大电通录取结果,这就需要我们先把 PDF 转化为 Excel 啦。
(1)PDF
(2)Excel
有了 Excel,那我们就可以为所欲为了!
开始
1. 载入 Excel 表格 #coding=utf8 import xlrd import numpy as np from pyecharts.charts import Bar from pyecharts.charts import Pie, Grid from pyecharts import options as opts #==================== 准备数据 ==================== # 导入Excel 文件 data = xlrd.open_workbook("C:/深圳大学电子与信息工程学院2020年电子信息硕士生拟录取名单.xlsx") # 载入第一个表格 table = data.sheets[0]
2. 提取 Excel 表格数据 tables = def Read_Excel(excel): # 从第4行开始读取数据,因为这个Excel文件里面从第四行开始才是考生信息 for rows in range(3, excel.nrows-1): dict_ = {"id":"", "name":"", "status":"", "preliminary_score":"", "retest_score":"", "total_score":"", "ranking":""} dict_["id"] = table.cell_value(rows, 1) dict_["name"] = table.cell_value(rows, 2) dict_["status"] = table.cell_value(rows, 3) dict_["remarks"] = table.cell_value(rows, 4) dict_["preliminary_score"] = table.cell_value(rows, 5) dict_["retest_score"] = table.cell_value(rows, 6) dict_["total_score"] = table.cell_value(rows, 7) dict_["ranking"] = table.cell_value(rows, 8) # 将未被录取或者非普通计划录取的考生滤除 if dict_["status"] == str("拟录取") and dict_["remarks"] == str("普通计划"): tables.append(dict_)
我们打印一下看看是否正确取出数据: # 执行上面方法 Read_Excel(table) for i in tables: print(i)

可以看到一切顺利。
3. 数据分段统计
这步因人而异,我只是想把各个分数段进行单独统计而已,大家也可以根据自己的喜好做其它的处理。 num_score_300_310 = 0 num_score_310_320 = 0 num_score_320_330 = 0 num_score_330_340 = 0 num_score_340_350 = 0 num_score_350_360 = 0 num_score_360_370 = 0 num_score_370_380 = 0 num_score_380_390 = 0 num_score_390_400 = 0 num_score_400_410 = 0 min_score = 999 max_score = 0 # 将各个分段的数量统计 for i in tables: score = i["preliminary_score"] if score > max_score: max_score = score if score < min_score: min_score = score if score in range(300, 310): num_score_300_310 = num_score_300_310 + 1 elif score in range(310, 320): num_score_310_320 = num_score_310_320 + 1 elif score in range(320, 330): num_score_320_330 = num_score_320_330 + 1 elif score in range(330, 340): num_score_330_340 = num_score_330_340 + 1 elif score in range(340, 350): num_score_340_350 = num_score_340_350 + 1 elif score in range(350, 360): num_score_350_360 = num_score_350_360 + 1 elif score in range(360, 370): num_score_360_370 = num_score_360_370 + 1 elif score in range(370, 380): num_score_370_380 = num_score_370_380 + 1 elif score in range(380, 390): num_score_380_390 = num_score_380_390 + 1 elif score in range(390, 400): num_score_390_400 = num_score_390_400 + 1 elif score in range(400, 410): num_score_400_410 = num_score_400_410 + 1 # 构建两个元组用以后期建表方便 bar_x_axis_data = ("300-310", "310-320", "320-330", "330-340", "340-350", "350-360", "360-370", "370-380", "380-390", "390-400", "400-410") bar_y_axis_data = (num_score_300_310, num_score_310_320, num_score_320_330,\ num_score_330_340, num_score_340_350, num_score_350_360,\ num_score_360_370, num_score_370_380, num_score_380_390,\ num_score_390_400, num_score_400_410)
绘制可视化图形
1、柱状图: #===================== 柱状图 ===================== # 构建柱状图 c = ( Bar .add_xaxis(bar_x_axis_data) .add_yaxis("录取考生", bar_y_axis_data, color="#af00ff") .set_global_opts(title_opts=opts.TitleOpts(title="数量")) .render("C:/录取数据图.html") )
2、饼图: #====================== 饼图 ====================== c = ( Pie(init_opts=opts.InitOpts(height="800px", width="1200px")) .add("录取分数概览", [list(z) for z in zip(bar_x_axis_data, bar_y_axis_data)], center=["35%", "38%"], radius="40%", label_opts=opts.LabelOpts( formatter="{b|{b}: }{c} {per|{d}%} ", rich={ "b": {"fontSize": 16, "lineHeight": 33}, "per": { "color": "#eee", "backgroundColor": "#334455", "padding": [2, 4], "borderRadius": 2, }, } )) .set_global_opts(title_opts=opts.TitleOpts(title="录取", subtitle='Made by 王昊'), legend_opts=opts.LegendOpts(pos_left="0%", pos_top="65%")) .render("C:/录取饼图.html") )


大功告成!!是不是超级直观哈哈!
作者 | Waao666
原文 | https://blog.csdn.net/weixin_40973138/article/details/106190092 文源网络,仅供学习之用,如有侵权请联系删除。
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