Python快速生成可视化，Excel数据再多也不怕！

一.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。

有了 Excel，那我们就可以为所欲为了！

二.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)

三.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！

End.

作者：Waao666

来源：CSDN

https://blog.csdn.net/weixin_40973138/article/details/106190092

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