analytics

app.py

@@ -7,6 +7,29 @@ https://huggingface.co/spaces/kevinhug/clientX
 https://hits.seeyoufarm.com/
 '''
 
+'''
+TIME SERIES ANALYTICS
+'''
+import yfinance as yf
+import seaborn as sns
+
+def trend(t):
+  data = yf.download(t, period="3mo")
+
+  for c in t.split(' '):
+      q=data.loc[:,('Close',c)]
+      data.loc[:,('Close_MA',c)]=q.rolling(9).mean() -q.rolling(42).mean()
+      q=data.loc[:,('Volume',c)]
+      data.loc[:,('Volume_MA',c)]=q.rolling(9).mean() -q.rolling(42).mean()
+
+  ma=data.loc[:,["Volume_MA","Close_MA"]].tail(15)
+  from sklearn.preprocessing import StandardScaler
+  std=StandardScaler()
+  result=std.fit_transform(ma)
+  df=pd.DataFrame(result,columns=ma.columns)
+  d=df.tail(1).stack(level=-1).droplevel(0, axis=0)
+  return sns.scatterplot(d, x="Close_MA", y="Volume_MA",hue=d.index.values)
+
 '''
 SIMILAR VECTOR DB SEARCH
 '''
@@ -183,7 +206,14 @@ Use Case:
 - intervene attrition through incentive
 
     """)
-
+  with gr.Tab("Trading Analyics"):
+    in_ts = gr.Textbox(placeholder="QQQM CIF VEGI PJP",
+                            label="Ticker",
+                            info="Identify Industry Trend, (top right is grow trending)"
+                            )
+    plot = gr.Plot(label="Identify Trend/Decline Industry")
+    btn_ts = gr.Button("Find Trending Industry")
+    btn_ts.click(fn=trend, inputs=in_ts, outputs=[plot])
 
 demo.launch()
 

requirements.txt

@@ -1,2 +1,5 @@
 chromadb
-fastai
+fastai
+yfinance
+scikit-learn
+seaborn