init
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@@ -1,9 +1,6 @@
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import pandas as pd
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from stockpredictor.analysis.Common import Common
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from plotly import tools, subplots
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import numpy as np
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import plotly.graph_objs as go
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import plotly.io as po
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# [청송촌놈] 파생을 알아야 시장이 보인다. 청송이 종목 고르는법! https://www.youtube.com/watch?v=weABtgZDeGg
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# 6. Pandas와 Plotly를 이용한 MACD 차트 그리기 https://excelsior-cjh.tistory.com/110
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@@ -20,27 +17,6 @@ class RSI:
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self.common = Common()
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return
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def draw(self, stock):
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item_name = stock["NAME"]
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item_code = stock["CODE"]
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df = pd.DataFrame(stock["PRICE"])
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rsi = go.Scatter(x=df.DATE, y=df['rsi'], name="RSI")
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signal = go.Scatter(x=df.DATE, y=df['rsis'], name="RSI Signal")
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data = [rsi, signal]
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layout = go.Layout(title='{} RSI 그래프'.format(item_name))
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fig = subplots.make_subplots(rows=2, cols=1, shared_xaxes=True)
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for trace in data:
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fig.append_trace(trace, 1,1)
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fig = go.Figure(data=data, layout=layout)
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path = "/Users/dsyoon/workspace/StockPredictor/resources/analysis/html"
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po.write_html(fig, file=path + "/rsi" + item_code+'.html', auto_open=False)
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return fig
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def apply(sefl, df, period=14):
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# df.diff를 통해 (기준일 종가 - 기준일 전일 종가)를 계산하여 0보다 크면 증가분을 감소했으면 0을 넣어줌
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U = np.where(df.close.diff(1) > 0, df.close.diff(1), 0)
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