如何用 Python 将 Excel 表格转成可视化图形？

小白学视觉

发布于 2021-05-07 11:28:53

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发布于 2021-05-07 11:28:53

文章被收录于专栏：深度学习和计算机视觉深度学习和计算机视觉

前言

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")
)