#!/usr/bin/env python
# coding: utf-8

# # 畫出 個股/大盤 K線圖與成交量

# # Part 0: Import 套件

# In[1]:


# 下載資料套件
import requests as r

#資料處理套件
import pandas as pd
import numpy as np
import json
from datetime import datetime, date

# 畫圖套件
import plotly.graph_objects as go
from plotly.subplots import make_subplots


# # Part 1: 台股個股Ｋ線圖與成交量(成交股數)

# ## 1.1 下載台股個股歷史走勢資料 - 成交股數
# - 股海小英雄youtube影片：[【Python 爬蟲】台股個股資料免費下載｜選擇想要的個股資料！](https://youtu.be/_4CEymrQbV8)
# - 資料來源：[證交所 個股日成交資訊](https://www.twse.com.tw/zh/page/trading/exchange/STOCK_DAY.html)

# In[2]:


def get_tw_stock_data(start_year, start_month, end_year, end_month, stock_code):
    start_date = str(date(start_year, start_month, 1))
    end_date = str(date(end_year, end_month, 1))
    month_list = pd.date_range(start_date, end_date, freq='MS').strftime("%Y%m%d").tolist()
    
    df = pd.DataFrame()
    for month in month_list:
        url = "https://www.twse.com.tw/exchangeReport/STOCK_DAY?response=json&date="+ month + "&stockNo=" + str(stock_code)
        res = r.get(url)
        stock_json = res.json()
        stock_df = pd.DataFrame.from_dict(stock_json['data'])
        df = df.append(stock_df, ignore_index = True)
        
    # 資料轉型
    for col in [0, 1, 2, 3, 4, 5, 6, 8]:
        for row in range(df.shape[0]):
            # 把"日期"從字串(string)換成時間(datetime)，並將民國年換成西元年
            if col == 0:
                day = df.iloc[row,0].split('/')
                df.iloc[row, 0] = datetime(int(day[0]) + 1911, int(day[1]), int(day[2]))
            # 把"開盤價", "最高價", "最低價", "收盤價"帶有逗號的字串(string)換成浮點數(float) 
            elif col != 0:
                df.iloc[row, col] = float(df.iloc[row,col].replace(',', ''))
    
    df.columns = ['日期', '成交股數', '成交金額', '開盤價', '最高價', '最低價', '收盤價', '漲跌價差', '成交筆數']
    return df


# In[3]:


#下載台股台積電:2330
df = get_tw_stock_data(start_year = 2021, 
                       start_month = 9, 
                       end_year = 2021, 
                       end_month = 10, 
                       stock_code = 2330)
df


# ## 1.2 畫出個股Ｋ線圖與成交股數
# - 股海小英雄youtube影片：[【股市分析】用K線預測大盤趨勢](https://youtu.be/FX6YAyOdEaE)

# In[4]:


# 設定子圖
fig = make_subplots(rows = 2, 
                    cols = 1, 
                    shared_xaxes = True, 
                    vertical_spacing = 0.05,  
                    row_width=[0.2, 0.7])

# 畫Ｋ線圖
fig.add_trace(go.Candlestick(x = df['日期'], 
                             open = df['開盤價'], 
                             high = df['最高價'],
                             low = df['最低價'], 
                             close = df['收盤價'], 
                             increasing_line_color = 'red', 
                             decreasing_line_color = 'green',
                             name = 'K線圖'), 
              row = 1, 
              col = 1)
 
# 畫成交量長條圖
fig.add_trace(go.Bar(x = df['日期'], 
                     y = df['成交股數'], 
                     showlegend = False,
                     name = '成交股數'), 
              row = 2, 
              col = 1)
    

# 設x軸標題
fig.update_xaxes(rangebreaks = [{ 'pattern': 'day of week', 'bounds': [6, 1]}])
fig.update_xaxes(title_text = "日期", row = 2, col = 1)

# 設y軸標題
fig.update_yaxes(title_text = "股價", row = 1, col = 1)


# 設圖標及圖長寬
fig.update_layout(
    title_text = "2021/09 - 2021/10 台積電(2330) K線圖",
    width = 800,
    height = 400
)

fig.update(layout_xaxis_rangeslider_visible = False)
fig.show()


# ## 1.3 畫出個股Ｋ線圖與成交股數，標上成交股數的顏色

# In[5]:


df["成交量增減"] = df['成交股數'].diff()
df


# In[6]:


df["成交量顏色"] = np.where(df["成交量增減"] >= 0, 'red', 'green')
df


# In[7]:


# 第一筆資料沒有成交量增減，所以當收盤價>=開盤價標示紅色，收盤價<開盤價標示綠色
if df.iloc[0, 6] - df.iloc[0, 3] >= 0:
    df.iloc[0, 10] = 'red'
else:
    df.iloc[0, 10] = 'green'


# In[8]:


df


# In[9]:


# 設定子圖
fig = make_subplots(rows = 2, 
                    cols = 1, 
                    shared_xaxes = True, 
                    vertical_spacing = 0.05,  
                    row_width=[0.2, 0.7])

# 畫Ｋ線圖
fig.add_trace(go.Candlestick(x = df['日期'], 
                             open = df['開盤價'], 
                             high = df['最高價'],
                             low = df['最低價'], 
                             close = df['收盤價'], 
                             increasing_line_color = 'red', 
                             decreasing_line_color = 'green',
                             name = 'K線圖'), 
              row = 1, 
              col = 1)
 
# 畫成交量長條圖
fig.add_trace(go.Bar(x = df['日期'], 
                     y = df['成交股數'], 
                     showlegend = False,
                     name = '成交股數',
                     marker_color = df['成交量顏色']), 
              row = 2, 
              col = 1)
    

# 設x軸標題
fig.update_xaxes(rangebreaks = [{ 'pattern': 'day of week', 'bounds': [6, 1]}])
fig.update_xaxes(title_text = "日期", row = 2, col = 1)

# 設y軸標題
fig.update_yaxes(title_text = "股價", row = 1, col = 1)


# 設圖標及圖長寬
fig.update_layout(
    title_text = "2021/09 - 2021/10 台積電(2330) K線圖",
    width = 800,
    height = 400
)

fig.update(layout_xaxis_rangeslider_visible = False)
fig.show()


# # Part 2: 大盤Ｋ線圖與成交量(成交金額)

# ## 2.1 下載大盤指數歷史資料
# - 股海小英雄youtube影片 - 大盤開高低收價：[【Python 爬蟲】台股大盤資料免費下載｜不必再到證交所的網站慢慢下載！](https://youtu.be/taiSnAeTs7Y)

# In[10]:


#下載大盤指數歷史資料
def get_stock_market_price(start_year, start_month, end_year, end_month):
    start_date = str(date(start_year, start_month, 1))
    end_date = str(date(end_year, end_month, 1))
    month_list = pd.date_range(start_date, end_date, freq='MS').strftime("%Y%m%d").tolist()
    
    # 下載大盤資料
    df = pd.DataFrame()
    for month in month_list:
        url = "https://www.twse.com.tw/indicesReport/MI_5MINS_HIST?response=json&date=" + month
        res = r.get(url)
        stock_json = res.json()
        stock_df = pd.DataFrame.from_dict(stock_json['data'])
        df = df.append(stock_df, ignore_index = True)
    
    # 資料轉型
    for col in range(0, 5):
        for row in range(df.shape[0]):
            # 把"日期"從字串(string)換成時間(datetime)，並將民國年換成西元年
            if col == 0:
                day = df.iloc[row,0].split('/')
                df.iloc[row, 0] = datetime(int(day[0]) + 1911, int(day[1]), int(day[2]))  
            # 把"開盤價", "最高價", "最低價", "收盤價"帶有逗號的字串(string)換成浮點數(float) 
            elif col != 0:
                df.iloc[row, col] = float(df.iloc[row,col].replace(',', ''))
    
    # 把日期從字串(string)換成時間(datetime)，並將民國年換成西元年
    df.columns = ['日期', '開盤價', '最高價', '最低價', '收盤價']
    return df


# In[11]:


twse = get_stock_market_price(start_year = 2021, 
                              start_month = 9, 
                              end_year = 2021, 
                              end_month = 10)
twse


# ## 2.2 下載大盤成交歷史資料
# - 股海小英雄youtube影片 - 大盤成交量：[【Python 爬蟲】台股市場成交資訊免費下載｜從成交量判斷大盤進出點](https://youtu.be/JXGl6pfvB-o)

# In[12]:


#下載大盤成交歷史資料
def get_stock_market_volumn(start_year, start_month, end_year, end_month):
    start_date = str(date(start_year, start_month, 1))
    end_date = str(date(end_year, end_month, 1))
    month_list = pd.date_range(start_date, end_date, freq='MS').strftime("%Y%m%d").tolist()
    
    # 下載大盤資料
    df = pd.DataFrame()
    for month in month_list:
        url = "https://www.twse.com.tw/exchangeReport/FMTQIK?response=json&date=" + month
        res = r.get(url)
        stock_json = res.json()
        stock_df = pd.DataFrame.from_dict(stock_json['data'])
        df = df.append(stock_df, ignore_index = True)
    
    # 資料轉型
    for col in range(0, 5):
        for row in range(df.shape[0]):
            # 把"日期"從字串(string)換成時間(datetime)，並將民國年換成西元年
            if col == 0:
                day = df.iloc[row,0].split('/')
                df.iloc[row, 0] = datetime(int(day[0]) + 1911, int(day[1]), int(day[2]))  
            # 把"成交股數", "成交金額", "成交筆數", "發行量加權股價指數"帶有逗號的字串(string)換成浮點數(float) 
            elif col != 0:
                df.iloc[row, col] = float(df.iloc[row,col].replace(',', ''))
    
    # 把日期從字串(string)換成時間(datetime)，並將民國年換成西元年
    df.columns = ['日期', '成交股數', '成交金額', '成交筆數', '發行量加權股價指數', '漲跌點數']
    return df


# In[13]:


twse_vol = get_stock_market_volumn(start_year = 2021, 
                                   start_month = 9, 
                                   end_year = 2021, 
                                   end_month = 10)
twse_vol


# ## 2.3 畫出大盤Ｋ線圖與成交金額

# In[14]:


# 設定子圖
fig = make_subplots(rows = 2, 
                    cols = 1, 
                    shared_xaxes = True, 
                    vertical_spacing = 0.05,  
                    row_width=[0.2, 0.7])

# 畫Ｋ線圖
fig.add_trace(go.Candlestick(x = twse['日期'], 
                             open = twse['開盤價'], 
                             high = twse['最高價'],
                             low = twse['最低價'], 
                             close = twse['收盤價'], 
                             increasing_line_color = 'red', 
                             decreasing_line_color = 'green',
                             name = 'K線圖'), 
              row = 1, 
              col = 1)

# 畫成交量長條圖
fig.add_trace(go.Bar(x = twse_vol['日期'], 
                     y = twse_vol['成交金額'], 
                     showlegend = False,
                     name = '成交金額'), 
              row = 2, 
              col = 1)
    

# 設x軸標題
fig.update_xaxes(rangebreaks = [{ 'pattern': 'day of week', 'bounds': [6, 1]}])
fig.update_xaxes(title_text = "日期", row = 2, col = 1)

# 設y軸標題
fig.update_yaxes(title_text = "指數", row = 1, col = 1)


# 設圖標及圖長寬
fig.update_layout(
    title_text = "2021/09 - 2021/10 大盤K線圖",
    width = 800,
    height = 400
)

fig.update(layout_xaxis_rangeslider_visible = False)
fig.show()


# ## 2.4 畫出大盤Ｋ線圖與成交金額，標上成交金額的顏色

# In[15]:


twse


# In[16]:


twse['成交金額'] = twse_vol['成交金額']
twse


# In[17]:


twse["成交金額增減"] = twse['成交金額'].diff()
twse


# In[18]:


twse["成交金額顏色"] = np.where(twse["成交金額增減"] >= 0, 'red', 'green')
twse


# In[19]:


# 第一筆資料沒有成交金額增減，所以當收盤價>=開盤價標示紅色，收盤價<開盤價標示綠色
if twse.iloc[0, 4] - twse.iloc[0, 1] >= 0:
    twse.iloc[0, 7] = 'red'
else:
    twse.iloc[0, 7] = 'green'


# In[20]:


twse


# In[22]:


# 設定子圖
fig = make_subplots(rows = 2, 
                    cols = 1, 
                    shared_xaxes = True, 
                    vertical_spacing = 0.05,  
                    row_width=[0.2, 0.7])

# 畫Ｋ線圖
fig.add_trace(go.Candlestick(x = twse['日期'], 
                             open = twse['開盤價'], 
                             high = twse['最高價'],
                             low = twse['最低價'], 
                             close = twse['收盤價'], 
                             increasing_line_color = 'red', 
                             decreasing_line_color = 'green',
                             name = 'K線圖'), 
              row = 1, 
              col = 1)
 
# 畫成交量長條圖
fig.add_trace(go.Bar(x = twse['日期'], 
                     y = twse['成交金額'], 
                     showlegend = False,
                     marker_color = twse['成交金額顏色'],
                     name = '成交金額'), 
              row = 2, 
              col = 1)
    

# 設x軸標題
fig.update_xaxes(rangebreaks = [{ 'pattern': 'day of week', 'bounds': [6, 1]}])
fig.update_xaxes(title_text = "日期", row = 2, col = 1)

# 設y軸標題
fig.update_yaxes(title_text = "指數", row = 1, col = 1)


# 設圖標及圖長寬
fig.update_layout(
    title_text = "2021/09 - 2021/10 大盤K線圖",
    width = 800,
    height = 400
)

fig.update(layout_xaxis_rangeslider_visible = False)
fig.show()