init

stockpredictor/analysis/Stochastic.py

@@ -13,31 +13,6 @@ class Stochastic:
         self.common = Common()
         return
 
-    def draw(self, stock):
-        item_name = stock["NAME"]
-        item_code = stock["CODE"]
-
-        df = pd.DataFrame(stock["PRICE"])
-        slow_k = go.Scatter(x=df.DATE, y=df['slow_k'], name="Slow%K")
-        slow_d = go.Scatter(x=df.DATE, y=df['slow_d'], name="Slow%D")
-        trade_volume = go.Bar(x=df.DATE, y=df['volume'], name="volume")
-
-        data1 = [slow_k, slow_d]
-        data2 = [trade_volume]
-        fig = subplots.make_subplots(rows=2, cols=1, shared_xaxes=True)
-
-        for trace in data1:
-            fig.append_trace(trace, 1, 1)
-
-        for trace in data2:
-            fig.append_trace(trace, 2, 1)
-
-        fig['layout'].update(title='{} MACD 그래프'.format(item_name))
-
-        path = "/Users/dsyoon/workspace/StockPredictor/resources/analysis/html"
-        po.write_html(fig, file=path + "/stochastic_" + item_code+'.html', auto_open=False)
-        return fig
-
     # 일자(n,m,t)에 따른 Stochastic(KDJ)의 값을 구하기 위해 함수형태로 만듬
     # n=15 (%k), m=5 (%d), t=3
     def apply(self, df, n=10, m=6, t=6):