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analysis_2023_总分分析.py
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# -*- coding: utf-8 -*-
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei'] #设置字体，设置了字体后，负号会变成乱码
plt.rcParams['axes.unicode_minus'] = False
x_index_chushi = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
x_index_fushi = [0, 1, 2, 3, 4, 5, 6, 7, 8]
bins_chushi = [330, 340, 350, 360, 370, 380, 390, 400, 410, 420]
bins_fushi = [210, 220, 230, 240, 250, 260, 270, 280, 290]
title_chushi = "熊二(2024南航计算机考研群：717645993)：2023录取结果分析 - 初试总分分析"
title_fushi = "熊二(2024南航计算机考研群：717645993)：2023录取结果分析 - 复试总分分析"
def load_total_score_dataframe():
"""加载 2023录取数据-总分.txt"""
file = "source_data/2023录取结果.txt"
with open(file, 'r', encoding="utf8") as fr:
lines = fr.readlines()
data = []
for line in lines:
infos = line.strip().split(" ")
data.append({
"专业": infos[0],
"初试": int(infos[1]),
"复试": float(infos[2]),
"总分": float(infos[3]),
})
pd_data = pd.DataFrame(data)
return pd_data
def analysis_total_score():
"""已经剔除了退伍大学生计划的数据"""
pd_data = load_total_score_dataframe()
pd_data_group_describe = pd_data.groupby(["专业"]).describe()
pd_data_group_describe.to_csv("2023-初复试总分分析.csv", encoding="utf8")
print(pd_data_group_describe)
def analysis_chushi():
pd_data = load_total_score_dataframe()
series_电子信息 = pd_data[pd_data.专业 == "专硕-电子信息"]["初试"]
series_学硕_计科 = pd_data[pd_data.专业 == "学硕-计科"]["初试"]
series_学硕_软工 = pd_data[pd_data.专业 == "学硕-软工"]["初试"]
series_学硕_网安 = pd_data[pd_data.专业 == "学硕-网安"]["初试"]
pd_analysis_电子信息 = pd.value_counts(series_电子信息, bins=bins_chushi, sort=False)
print(pd_analysis_电子信息)
pd_analysis_学硕_计科 = pd.value_counts(series_学硕_计科, bins=bins_chushi, sort=False)
pd_analysis_学硕_软工 = pd.value_counts(series_学硕_软工, bins=bins_chushi, sort=False)
pd_analysis_学硕_网安 = pd.value_counts(series_学硕_网安, bins=bins_chushi, sort=False)
pd_merge = pd.concat([pd_analysis_电子信息, pd_analysis_学硕_计科, pd_analysis_学硕_软工, pd_analysis_学硕_网安], axis=1)
pd_merge.columns = ["电子信息", "学硕_计科", "学硕_软工", "学硕_网安"]
print(pd_merge)
ax = pd_merge.plot(figsize=(15, 15),
kind='bar',
title=title_chushi,
width=0.8,
xlabel="分数区间",
ylabel="录取人数",
fontsize=15)
for x, y in zip(x_index_chushi, pd_analysis_电子信息.tolist()):
ax.text(x-0.3, y, y, ha = 'center',va = 'bottom',fontsize=15)
for x, y in zip(x_index_chushi, pd_analysis_学硕_计科.tolist()):
ax.text(x-0.1, y, y, ha = 'center',va = 'bottom',fontsize=15)
for x, y in zip(x_index_chushi, pd_analysis_学硕_软工.tolist()):
ax.text(x+0.1, y, y, ha = 'center',va = 'bottom',fontsize=15)
for x, y in zip(x_index_chushi, pd_analysis_学硕_网安.tolist()):
ax.text(x+0.3, y, y, ha = 'center',va = 'bottom',fontsize=15)
ax.text(2, 18, "熊二(2024南航计算机考研群：717645993) \n 2023录取结果分析 - 初试总分分析", fontsize=25, color="red")
fig = ax.get_figure()
plt.show()
fig.savefig('2023初试.png', dip=500)
# print(pd_data_电子信息_cut.unique())
pass
def analysis_fushi():
pd_data = load_total_score_dataframe()
series_电子信息 = pd_data[pd_data.专业 == "专硕-电子信息"]["复试"]
series_学硕_计科 = pd_data[pd_data.专业 == "学硕-计科"]["复试"]
series_学硕_软工 = pd_data[pd_data.专业 == "学硕-软工"]["复试"]
series_学硕_网安 = pd_data[pd_data.专业 == "学硕-网安"]["复试"]
pd_analysis_电子信息 = pd.value_counts(series_电子信息, bins=bins_fushi, sort=False)
print(pd_analysis_电子信息)
pd_analysis_学硕_计科 = pd.value_counts(series_学硕_计科, bins=bins_fushi, sort=False)
pd_analysis_学硕_软工 = pd.value_counts(series_学硕_软工, bins=bins_fushi, sort=False)
pd_analysis_学硕_网安 = pd.value_counts(series_学硕_网安, bins=bins_fushi, sort=False)
pd_merge = pd.concat([pd_analysis_电子信息, pd_analysis_学硕_计科, pd_analysis_学硕_软工, pd_analysis_学硕_网安], axis=1)
pd_merge.columns = ["电子信息", "学硕_计科", "学硕_软工", "学硕_网安"]
print(pd_merge)
ax = pd_merge.plot(figsize=(15, 15),
kind='bar',
title=title_fushi,
width=0.8,
xlabel="分数区间",
ylabel="录取人数",
fontsize=15)
for x, y in zip(x_index_fushi, pd_analysis_电子信息.tolist()):
ax.text(x - 0.3, y, y, ha='center', va='bottom', fontsize=15)
for x, y in zip(x_index_fushi, pd_analysis_学硕_计科.tolist()):
ax.text(x - 0.1, y, y, ha='center', va='bottom', fontsize=15)
for x, y in zip(x_index_fushi, pd_analysis_学硕_软工.tolist()):
ax.text(x + 0.1, y, y, ha='center', va='bottom', fontsize=15)
for x, y in zip(x_index_fushi, pd_analysis_学硕_网安.tolist()):
ax.text(x + 0.3, y, y, ha='center', va='bottom', fontsize=15)
ax.text(2, 18, "熊二(2024南航计算机考研群：717645993) \n 2023录取结果分析 - 复试总分分析", fontsize=25, color="red")
fig = ax.get_figure()
plt.show()
fig.savefig('2023复试.png', dip=500)
pass
if __name__ == "__main__":
analysis_total_score()
analysis_chushi()
analysis_fushi()
pass