Merge pull request prathimacode-hub#469 from neelshah2409/main

Stock Visualiser

Author: prathimacode-hub

BasicPythonScripts/Stock Visualiser/Images/output_1(stock).png

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+# Stock Visualiser
+
+## Short description of package/script
+
+-Here firstly using the mpl finance lib we get the stock growth and then read the data through pandas and plotting the graph using matplotlib .Here we also give one feature for user that they can choose the duration for stock analysis we give them this option using tkcalendar.
+- List out the libraries imported: matplotlib ,pandas, tkcalendar,tkinter, date,mpl_finance
+
+## Setup instructions
+
+Here after running the program we need to choose the date from which we need to see the graph then we need to press visualise button and we have to give token/stock number so they graph will be shown for that stock
+
+
+
+## Output
+
+![image](Images/outut_1(stock).png)
+![image](Images/output_2(stock).png)
+![image](Images/output_3(stock).png)
+
+## Author(s)
+
+Neel Shah

BasicPythonScripts/Stock Visualiser/Images/output_2(stock).png

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+Libraries used:
+- matplotlib
+- pandas
+- mpl_finance
+- tkinter
+- date 
+- tkcalendar

BasicPythonScripts/Stock Visualiser/Images/output_3(stock).png

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+from tkinter import *
+from tkcalendar import DateEntry
+import datetime as dt
+
+import pandas_datareader as web
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+from mpl_finance import candlestick_ohlc
+
+'''
+Function for visualizing stock data
+Using Candlestick Charts
+'''
+def visualize():
+
+    # Get Dates From DateEntry and Convert It To Datetime
+    from_date = cal_from.get_date()
+    to_date = cal_to.get_date()
+
+    start = dt.datetime(from_date.year, from_date.month, from_date.day)
+    end = dt.datetime(to_date.year, to_date.month, to_date.day)
+
+    # Load Ticker From Entry And Download Data
+    ticker = text_ticker.get()
+    data = web.DataReader(ticker, 'yahoo', start, end)
+
+    # Restructure Data Into OHLC Format
+    data = data[['Open', 'High', 'Low', 'Close']]
+
+    # Reset Index And Convert Dates Into Numerical Format
+    data.reset_index(inplace=True)
+    data['Date'] = data['Date'].map(mdates.date2num)
+
+    # Adjust Style Of The Plot
+    ax = plt.subplot()
+    ax.grid(True)
+    ax.set_axisbelow(True)
+    ax.set_title('{} Share Price'.format(ticker), color='white')
+    ax.figure.canvas.set_window_title('Stock Visualizer ')
+    ax.set_facecolor('black')
+    ax.figure.set_facecolor('#121212')
+    ax.tick_params(axis='x', colors='white')
+    ax.tick_params(axis='y', colors='white')
+    ax.xaxis_date()
+
+    # Plot The Candlestick Chart
+    candlestick_ohlc(ax, data.values, width=0.5, colorup='#00ff00')
+    plt.show()
+
+# Define Main Window
+root = Tk()
+root.title(" Stock Visualizer ")
+
+# Add Components And Link Function
+label_from = Label(root, text="From:")
+label_from.pack()
+cal_from = DateEntry(root, width=50, year=2015, month=1, day=1)
+cal_from.pack(padx=10, pady=10)
+
+label_to = Label(root, text="To:")
+label_to.pack()
+cal_to = DateEntry(root, width=50)
+cal_to.pack(padx=10, pady=10)
+
+label_ticker = Label(root, text="Ticker Symbol:")
+label_ticker.pack()
+text_ticker = Entry(root)
+text_ticker.pack()
+
+btn_visualize = Button(root, text="Visualize", command=visualize)
+btn_visualize.pack()
+
+root.mainloop()