# 完整的程式加上註解

# -*- coding: UTF-8 -*-

import pandas as pd

import matplotlib.pyplot as plt
import os
import time

import numpy as np


dict_year = {}

temp04 = []
temp01 = []
temp02 = None


myfile = './學習紀錄.csv'
data = pd.read_csv(myfile, encoding='utf-8')
col_names = data.columns.values.tolist()
# print(col_names)
# print(len(col_names))
lists = data.values.tolist()
rows_num = len(lists)
# print(rows_num)

# 去除重複的年度
for i in range(rows_num):
    temp01.append(lists[i][0])
    temp02 = set(temp01)

temp01 = list(temp02)

# print(temp01)
# print(lists)

# 依據年度建立字典
for year in temp01:
    temp03 = []
    for i in range(rows_num):
        myyears = lists[i][0]
        if myyears == year:
            temp03.append(lists[i][0:])

    dict_year[year] = temp03

print(dict_year)

# col_lens = len(col_names)
# print(col_lens)

# 去掉中文字
for string01 in col_names[17:]:
    print(string01.split('.')[1][2:-3])
    temp04.append(string01.split('.')[1][2:-3])

for school_year in temp01:
    # 依據建立年度建立資料夾
    path_name = str(school_year)
    print(path_name)
    if not os.path.exists(path_name):
        os.makedirs(path_name)

    years_len = len(dict_year[school_year])
    for allyear in range(years_len):

        # print(col_names[6])
        # print(dict_year[108][allyear][6])
        # print(col_names[17:-1])
        # print(dict_year[108][allyear][17:-1])
        # print(len(col_names[17:-1]))
        # print(len(dict_year[108][allyear][17:-1]))

        # 在windows 10 底下先將字型安裝在Python安裝路徑\Lib\site-packages\matplotlib\mpl-data\fonts\ttf底下；
        # 刪除C:\Users\本機帳戶\.matplotlib\fontlist-v330.json
        # 設定中文字型以免亂碼□□
        plt.rcParams['font.sans-serif'] = ['Taipei Sans TC Beta']
        # 把存檔的figure size 放大兩倍
        plt.rcParams["figure.figsize"] = (16, 12)

        plt.plot(temp04, dict_year[school_year][allyear][17:],
                 linestyle='--', marker='o', color='b')

        name = dict_year[school_year][allyear][6]+'-' + \
            str(dict_year[school_year][allyear][0]) + \
            '('+str(dict_year[school_year][allyear][1])+') 科目'

        # 打開grid
        plt.grid(True)
        # 將y軸定義
        y_axis = np.arange(0, 100, 1.0)

        plt.title(name)
        plt.yticks(y_axis)
        plt.ylabel('比例(%)')
        plt.xticks(temp04, rotation=90)
        plt.autoscale(True)
        plt.xlabel('本科目分數級距分布')
        plt.savefig(os.path.join(path_name, name+'.png'), dpi=300)
        plt.close()
    # time.sleep(5)
    # plt.show()