analytics

app.py

@@ -12,10 +12,11 @@ TIME SERIES ANALYTICS
 '''
 import yfinance as yf
 import seaborn as sns
+import pandas as pd
 from sklearn.preprocessing import StandardScaler
 
 def trend(t):
-  data = yf.download(t, period="3mo")
+  data = pd.read_parquet("data.parquet") # yf.download(t, period="3mo")
 
   for c in t.split(' '):
       q=data.loc[:,('Close',c)]
@@ -91,6 +92,7 @@ with gr.Blocks() as demo:
   
   1) Semantic Similarity Document Search (SSDS)
   2) Fine Tune LLM
+  3) Using Time Series Data to Identify Growth
   
   #### Data Scientist: Kevin Wong, [email protected], 416-903-7937
 

data.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3eb7b6cec763e37896ac0c1bc31bcf958ea349e7969472714a8973b6996f96d
+size 28749