diff --git a/MachineLearning Projects/Stock-Analysis/README.md b/MachineLearning Projects/Stock-Analysis/README.md
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+StockAnalysis
+
+This program has ability to analyse stock and compare its price over today,yesterday,lastmonth,lastyear and plot the trend.
+Program allows to input stock tickers explcitly or get 'n' stock based on S&P index.
+
+Sample Output
+
+For eg: Here it can analyse how AAPL is performed over yesterday,lastmonth,lastyear and plot
+
+
+
+![image](https://user-images.githubusercontent.com/16798480/225775468-f9332a85-8181-47eb-a48f-8d36f85e9d5a.png)
diff --git a/MachineLearning Projects/Stock-Analysis/StockAnalysis.py b/MachineLearning Projects/Stock-Analysis/StockAnalysis.py
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+import yfinance as yf
+import pandas as pd
+import datetime
+from datetime import date
+from pandas_datareader import data as pdr
+import pandas as pd
+import matplotlib.pyplot as plt
+
+stocknum=10
+option=1
+tickerlist = []
+while True:
+  try:
+    option = int(input("You have 2 options 1: Do you want to analyse top stocks in S&P index 2: Specific Stocks, 1/2 ?"))
+    
+    if option==1:
+        stocknum=int(input("How many stocks you want to analyse? give a number"))
+        toptickers = pd.read_html('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')[0]
+        tickerlist= toptickers.head(stocknum).Symbol.to_list()
+        print(tickerlist)
+    elif option==2:
+        inputstr = input("Enter comma separated ticker symbols of interested stocks ")
+        print("Input string: ", inputstr)
+
+        # conver to the list
+        tickerlist = inputstr.upper().split (",")
+        print("list: ", list)
+    else:
+        raise ValueError
+    break
+  except ValueError:
+      print("Please input valid integer only...")  
+      continue
+
+data = pd.DataFrame(columns=tickerlist)
+
+for ticker in tickerlist:
+    y = yf.Ticker(ticker)
+    if(y==0):
+        print("No data found for ",ticker)
+        break
+try:    
+    today=date.today()
+    yesterday=today + datetime.timedelta(days=-1)
+    lastmonth=today + datetime.timedelta(days=-30)
+    lastyear=today + datetime.timedelta(days=-365)
+    df2=yf.download(tickerlist,today,today+datetime.timedelta(days=1), auto_adjust=True)['Close']
+    df3=yf.download(tickerlist,yesterday,yesterday+datetime.timedelta(days=1), auto_adjust=True)['Close']
+    df4=yf.download(tickerlist,lastmonth,lastmonth+datetime.timedelta(days=1), auto_adjust=True)['Close']
+    df5=yf.download(tickerlist,lastyear,lastyear+datetime.timedelta(days=1), auto_adjust=True)['Close']
+    data=data.append(df2)
+    data=data.append(df3)
+    data=data.append(df4)
+    data=data.append(df5)
+    data.plot()
+
+    print(data.head())
+except:
+      print("Error occured while processing. Please try again.") 
+
+
+
+  
+