preface

Today I choose to simply and casually analyze some data of the college entrance examination ~~~

The development tools

**Python version: **3.6.4

Related modules:

Pyecharts module;

And some modules that come with Python.

Environment set up

Install Python and add it to the environment variables. PIP installs the required related modules.

The pyecharts module can be installed by:

Python simple analysis of wechat friends

Analysis with a straight face

First of all, let’s take a look at the trend of the total number of college entrance examination applicants since the resumption of the college entrance examination (1977).

T_T it seems that the student party is indeed more and more.

But this does not seem to be very intuitive to see the annual enrollment ratio, right? Ok, let’s look at it visually:

It seems that the idea that college is getting “easier” is not unfounded. The overall admission rate is terrifically high

What about the provinces?

Due to the different statistical standards of the final enrollment of college entrance examination in each province, some are only for undergraduate students, and some are all. In order to avoid unfair comparison caused by different statistical standards, we only analyze the number of applicants for college entrance examination in each province.

From 2010 to this year (2018), the distribution of gaokao examinees in different provinces is as follows:

T_T Henan’s number of college entrance examination candidates is really unique.

How is the number of universities distributed among provinces? Taking the number of public undergraduate universities as the statistical standard, the distribution map is roughly like this:

Emmm. Beijing and Jiangsu ranked first and second, respectively. Think of it as T_T

Then how about the distribution of 985&211 universities?

“That’s it, love is over.” I stopped talking when I saw this.

Take province as the X-axis, year as the Y-axis, and the number of candidates applying for examination in that year as the Z-axis to have a more intuitive look at the change of the number of candidates in each province.

The order of the provinces is this:

Beijing, sichuan, shaanxi, jiangxi, jilin, ningxia, guangxi, Inner Mongolia, gansu, Tibet, fujian, Shanghai, guangdong, shandong, zhejiang, henan, anhui, jiangsu, hebei, heilongjiang, hunan, hubei, shanxi, yunnan, guizhou, hainan, liaoning, qinghai, xinjiang, chongqing, tianjin, Taiwan because there is no data, so not to join.

T_T The number of college entrance examination candidates in Henan is really terrible.

Emmm, because the available data is not much, and then analysis is probably a fancy graph game, think or forget it. As for personal views, it is better not to publish them. After all, everyone’s Hamlet is different.

I share Python data crawler cases every day. The next article is to share Python simple analysis of Chrome browser browsing records

All done~ Complete source code see personal profile or private letter to obtain relevant files.