add ECOS, NAVER snap data

README.md

@@ -163,6 +163,13 @@ df = fdr.DataReader('^NYICDX') # ICE U.S. Dollar Index (^NYICDX) 달러인덱스
 # FRED 데이터 여러 항목 한번에 
 df = fdr.DataReader('FRED:M2,HSN1F,NASDAQCOM')  # M2 통화량, HSN1F 주택판매지수, NASDAQCOM 나스닥종합지수
 
+#  KRX지수및 지수 구 성종목
+df = fdr.SnapDataReader('KRX/INDEX/LIST') # KRX 전체 지수목록
+
+df = fdr.SnapDataReader('KRX/INDEX/STOCK/1001') # KOSPI 지수구성종목
+df = fdr.SnapDataReader('KRX/INDEX/STOCK/1028') # 코스피 200
+df = fdr.SnapDataReader('KRX/INDEX/STOCK/5106') # KRX ESG Leaders 150 테마 지수 구성종목
+
 
 # 캔들차트
 df = fdr.DataReader('005930', '2023-01-01', '2023-06-30')
@@ -182,4 +189,4 @@ fdr.chart.plot(df)
 * [S&P500 가격 데이터 수집과 수익률 분석](https://nbviewer.jupyter.org/710b8f0a4bd9a8df91ae1be6c7e838b1) 
 * [S&P500 팩터 데이터 수집과 분석](https://nbviewer.jupyter.org/35a1b0d5248bc9b09513e53be437ac42)
 
-**2018-2023 [FinanceData.KR]()**
+**2018-2024 [FinanceData.KR]()**

__init__.py

@@ -2,9 +2,9 @@
 from .data import (SnapDataReader)
 from .data import (StockListing)
 from .data import (EtfListing)
-from . import (chart)
+from .chart import (plot)
 
-__version__ = '0.9.80'
+__version__ = '0.9.90'
 
 __all__ = [
     '__version__', 

back_chart.py

@@ -0,0 +1,254 @@
+#-*- coding: utf-8 -*-
+#
+# FinaceDataReader chart.py
+# (c)2018-2024 FinaceData.KR
+
+from FinanceDataReader.chart import (plot, candle, line)
+
+# import numpy as np
+# import pandas as pd
+# from datetime import datetime, date
+# import itertools
+
+# plotly_install_msg = f'''
+#     {'-' * 80}
+#     FinanceDataReade.chart.plot() dependen on plotly
+#     plotly not installed please install as follows
+
+#     pip install plotly
+
+#     FinanceDataReade.chart.plot()는 plotly에 의존성이 있습니다.
+#     명령창에서 다음과 같이 plotly를 설치하세요
+
+#     pip install plotly
+#     '''
+
+# try:
+#     import plotly.graph_objects as go
+#     from plotly.subplots import make_subplots
+# except ModuleNotFoundError as e:
+#     raise ModuleNotFoundError(plotly_install_msg)
+
+# ## holiday Calendar
+# holidays_url_base = 'https://raw.githubusercontent.com/FinanceData/FinanceDataReader/master/calendars'
+
+# holidays_krx,holidays_hyse = None, None 
+
+# ## Chart plot
+# def plot(df, tools=None, layout=None):
+#     '''
+#     plot candle chart with DataFrame
+#     * df: OHLCV data(DataFrame)
+#     * updates: additional chart configurations
+#     '''
+#     global holidays_krx, holidays_hyse
+
+#     if holidays_krx is None:
+#         holidays_krx = pd.read_csv(f'{holidays_url_base}/holidays-krx.csv')['date'].values
+#     if holidays_hyse is None:
+#         holidays_hyse = pd.read_csv(f'{holidays_url_base}/holidays-nyse.csv')['date'].values
+
+
+#     tools = {'SMA': [10, 20, 60]} if not tools else tools
+#     layout = dict() if not layout else layout
+
+#     x_ticks = df.index
+
+#     change = df["Close"].pct_change()
+#     oc_ratio = (df["Close"]-df["Open"])/df["Open"]
+#     oh_ratio = (df["High"]-df["Open"])/df["Open"]
+#     hover_text = [f'DoD: {chg:.1%} OC: {oc:.1%}, OH: {oh:.1%}' for chg, oc, oh in zip(change, oc_ratio, oh_ratio)]
+
+#     # OHLC candle chart
+#     candle = go.Candlestick(
+#         x=x_ticks, 
+#         open=df["Open"], high=df["High"], low=df["Low"], close=df["Close"], 
+#         name='',
+#         text = hover_text,
+#         increasing_fillcolor = 'red',
+#         decreasing_fillcolor = 'blue',
+#         increasing_line_color = 'red',
+#         decreasing_line_color = 'blue',
+#         increasing_line_width = 1.5,
+#         decreasing_line_width = 1.5,
+#         showlegend = False, 
+#         opacity=0.75,
+#     )
+
+#     # volume bar chart
+#     vol_colors = np.where(df['Close'].shift(1) > df['Close'], 'blue', 'red')
+#     vol_bar = go.Bar(
+#         x=x_ticks, 
+#         y=df['Volume'],
+#         showlegend=False,
+#         name='', 
+#         opacity = 0.5,
+#         marker={'color': vol_colors},
+#     )
+
+#     fig = make_subplots(rows=2, cols=1, 
+#                         shared_xaxes=True, 
+#                         vertical_spacing=0,
+#                         row_width=[0.3, 0.7])
+
+#     fig.add_trace(candle, row=1, col=1)
+#     fig.add_trace(vol_bar, row=2, col=1)
+
+#     # hide rangeslider
+#     fig.update_xaxes(rangeslider_visible=False)
+
+#     # holidays
+#     holidays = holidays_krx
+#     if df.attrs.get('exchange') != 'KRX':
+#         holidays = holidays_hyse
+
+#     # Remove non-business days 
+#     fig.update_xaxes(rangebreaks = [ 
+#         dict(bounds=['sat','mon']), # remove weekend
+#         dict(values=holidays), # remove non biz days
+#         # dict(bounds=[15.5, 9], pattern='hour'), # remove non biz hours
+#     ])
+
+#     # draw axes and grid
+#     fig.update_xaxes(showline=True, linewidth=1, linecolor='black', gridcolor='lightgray')
+#     fig.update_yaxes(showline=True, linewidth=1, linecolor='black', gridcolor='lightgray')
+
+#     # x-axis tick format
+#     fig.update_xaxes(tickformat='%Y-%m-%d', row=2, col=1)
+#     fig.update_xaxes(tickangle=45)
+
+#     # y-axis tick format
+#     fig.update_yaxes(tickformat=',', row='all', col=1)
+
+#     # spikes
+#     fig.update_xaxes(showspikes=True, spikethickness=1, spikedash="dot", spikecolor="lightgray", spikemode="across", spikesnap='cursor')
+#     # fig.update_traces(xaxis="x2") # binding x-axis
+
+#     # bgcolor
+#     fig.update_layout(plot_bgcolor='white')
+#     fig.update_layout(paper_bgcolor='white')
+
+#     ## tools (tools: indicators and annotations)
+
+#     # available_tools  
+#     available_tools = ['SMA', 'EMA', 'HLINE', 'VLINE', 'VRECT']
+
+#     for key in tools:
+#         if key.upper() not in available_tools:
+#             raise ValueError(f"Unsupport tool: {key}") 
+
+#     tools = {key.upper(): tools[key] for key in tools} # keys to upper case 
+
+#     # default tools
+#     # default_ma_params = [10, 20, 60] # default moving averages params
+#     # if all(x not in tools.keys() for x in ['SMA', 'EMA']):
+#     #     tools['SMA'] = default_ma_params
+
+#     line_dashes = ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot']
+#     line_colors = ['darkmagenta', 'gold', 'limegreen', 'maroon', 'chocolate', 'seagreen', 'coral']
+#     line_style_cycler = itertools.cycle(itertools.product(line_dashes, line_colors))
+
+#     default_line_width = 0.75
+
+#     if 'SMA' in tools: # SMA: simple moving average 
+#         args = tools.pop('SMA')
+#         for arg in args:
+#             line_dash, line_color = next(line_style_cycler)
+#             ma_args = dict()
+#             ma_args['line_width'] = default_line_width
+#             if type(arg) == int:
+#                 window = arg
+#                 ma_args['line_dash'] = line_dash
+#                 ma_args['line_color'] = line_color
+#                 ma_args['line_width'] = default_line_width
+#             elif type(arg) == dict:
+#                 window = arg['window']
+#                 ma_args['line_dash'] = arg['line_dash'] if 'line_dash' in arg else line_dash
+#                 ma_args['line_color'] = arg['line_color'] if 'line_color' in arg else line_color
+#                 ma_args['line_width'] = arg['line_width'] if 'line_width' in arg else default_line_width
+#             ma_price = df['Close'].rolling(window).mean().round(0)
+#             ma_args['x'] = ma_price.index
+#             ma_args['y'] = ma_price
+#             ma_args['name'] = f'SMA_{window}'
+#             fig.add_trace(go.Scatter(**ma_args), row=1, col=1)
+
+#     if 'EMA' in tools: # EMA: exponential moving average
+#         args = tools.pop('EMA')
+#         for arg in args:
+#             line_dash, line_color = next(line_style_cycler)
+#             ma_args = dict()
+#             ma_args['line_width'] = default_line_width
+#             if type(arg) == int:
+#                 window = arg
+#                 ma_args['line_dash'] = line_dash
+#                 ma_args['line_color'] = line_color
+#                 ma_args['line_width'] = default_line_width
+#             elif type(arg) == dict:
+#                 window = arg['window']
+#                 ma_args.update(arg)
+#                 ma_args['line_dash'] = arg['line_dash'] if 'line_dash' in arg else line_dash
+#                 ma_args['line_color'] = arg['line_color'] if 'line_color' in arg else line_color
+#                 ma_args['line_width'] = arg['line_width'] if 'line_width' in arg else default_line_width
+#             ma_price = df['Close'].ewm(span=window).mean()
+#             ma_args['x'] = ma_price.index
+#             ma_args['y'] = ma_price
+#             ma_args['name'] = f'EMA_{window}'
+#             fig.add_trace(go.Scatter(**ma_args), row=1, col=1)
+
+#     if 'HLINE' in tools: # HLINE: Horizontal line
+#         hline_args = dict(line_width=1.5, line_dash="dot", line_color="tomato", layer="below")
+#         hline_value = tools.pop('HLINE')
+#         if hasattr(hline_value, '__iter__'):
+#             for hline in hline_value:
+#                 if type(hline) in [int, float]:
+#                     hline_args['y'] = hline
+#                 elif type(hline) == dict:
+#                     hline_args.update(hline)
+#                 else:
+#                     raise ValueError("'HLINE' must be list of str or list of dict")
+#                 fig.add_hline(**hline_args)
+#         else:
+#             hline_args['y'] = hline_value
+#             fig.add_hline(**hline_args) # just one value
+
+#     if 'VLINE' in tools: # VLINE: vertical line
+#         vline_args = dict(line_width=1.5, line_dash="dot", line_color="tomato", layer="below")
+#         vline_value = tools.pop('VLINE')
+#         if hasattr(vline_value, '__iter__'):
+#             for vline in vline_value:
+#                 if type(vline) in [pd.Timestamp, str, datetime, date]:
+#                     vline_args['x'] = pd.to_datetime(vline).timestamp() * 1000
+#                 elif type(vline) == dict:
+#                     vline_args.update(vline)
+#                     vline_args['x'] = pd.to_datetime(vline_args['x']).timestamp() * 1000
+#                 else:
+#                     raise ValueError("'VLINE' must be list of str or list of dict")
+#                 fig.add_vline(**vline_args)
+#         else:
+#             vline_args['y'] = vline_value
+#             fig.add_hline(**vline_args) # just one value
+
+#     if 'VRECT' in tools: # VRECT: highlighting period
+#         vrect_list = tools.pop('VRECT') if 'VRECT' in tools else {}
+#         for vrect in vrect_list:
+#             vrect_args = dict(fillcolor="LightSalmon", opacity=0.3, layer="below", line_width=0)
+#             if type(vrect) == tuple:
+#                 vrect_args['x0'] = str(vrect[0])
+#                 vrect_args['x1'] = str(vrect[1])
+#             elif type(vrect) == dict:
+#                 vrect_args.update(vrect)
+#             else:
+#                 raise ValueError("'vrect' must be list of tuple or list of dict")
+#             fig.add_vrect(**vrect_args)
+
+#     ## update_layout
+#     layout_defaults = {
+#         'hovermode': 'x', # available hovermodes: 'closest', 'x', 'x unified', 'y', 'y unified'
+#         'margin': go.layout.Margin(l=0, r=0, b=0, t=0), # margins
+#         'width': 1280,
+#         'height': 640,
+#     }
+#     layout.update(layout_defaults)
+#     fig.update_layout(layout)
+#     return fig
+

chart/__init__.py

@@ -0,0 +1,2 @@
+from .plot import plot
+from .candle import candle

chart.py → chart/candle.py

@@ -8,8 +8,11 @@
 from datetime import datetime, date
 import itertools
 
-plotly_install_msg = f'''
-    {'-' * 80}
+try:
+    import plotly.graph_objects as go
+    from plotly.subplots import make_subplots
+except ModuleNotFoundError as e:
+    plotly_install_msg = f'''{'-' * 80}
     FinanceDataReade.chart.plot() dependen on plotly
     plotly not installed please install as follows
 
@@ -20,20 +23,14 @@
 
     pip install plotly
     '''
-
-try:
-    import plotly.graph_objects as go
-    from plotly.subplots import make_subplots
-except ModuleNotFoundError as e:
     raise ModuleNotFoundError(plotly_install_msg)
 
 ## holiday Calendar
 holidays_url_base = 'https://raw.githubusercontent.com/FinanceData/FinanceDataReader/master/calendars'
-
 holidays_krx,holidays_hyse = None, None 
 
 ## Chart plot
-def plot(df, tools=None, layout=None):
+def candle(df, tools=None, layout=None):
     '''
     plot candle chart with DataFrame
     * df: OHLCV data(DataFrame)
@@ -246,7 +243,8 @@ def plot(df, tools=None, layout=None):
         'width': 1280,
         'height': 640,
     }
-    layout.update(layout_defaults)
-    fig.update_layout(layout)
+    new_layout = {}
+    new_layout.update(layout_defaults) 
+    new_layout.update(layout) 
+    fig.update_layout(new_layout)
     return fig
-