import numpy as np import matplotlib.pyplot as plt import pandas as…
Question Answered step-by-step import numpy as np import matplotlib.pyplot as plt import pandas as… import numpy as npimport matplotlib.pyplot as pltimport pandas as pdimport pandas_datareader as webimport datetime as dtimport tensorflow as tfimport matplotlib.dates as mdates from mpl_finance import candlestick2_ohlcfrom sklearn.preprocessing import MinMaxScalerfrom keras.models import Sequentialfrom keras.layers import Dense, Dropout, LSTM #Define Time Framestart = dt.datetime(2021,1,1)end = dt.datetime.now() #Load datacompany = ‘TSLA’ start = dt.datetime(2021,1,1)end = dt.datetime.now() data = web.DataReader(company, ‘yahoo’, start, end) #Restructure Datadata = data[[‘Open’, ‘High’, ‘Low’, ‘Close’]]data.reset_index(inplace=True)data[‘Date’] = data[‘Date’].map(mdates.date2num) #Visualizationax = plt.subplot()ax.grid(True)ax.set_axisbelow(True)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() candlestick2_ohlc(ax, data.values, width=0.5, colorup=’#00ff00′)plt.show()————————————————————————————————————————————–Traceback (most recent call last): File “c:UsersuserDesktopprediction stock1121.py”, line 46, in
