stock market prediction python code example

Example 1: predict stock price python

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM, Dense, Dropout, Bidirectional
from tensorflow.keras.callbacks import ModelCheckpoint, TensorBoard
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from yahoo_fin import stock_info as si
from collections import deque

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import time
import os
import random

Example 2: live stock market data python

import urllib.request import json  class GoogleFinanceAPI:     def __init__(self):         self.prefix = "http://finance.google.com/finance/info?client=ig&q="          def get(self,symbol,exchange):         url = self.prefix+"%s:%s"%(exchange,symbol)         u = urllib.request.urlopen(url)         content = u.read().decode('utf-8')         obj = json.loads(content[3:])         return obj[0]                   if __name__ == "__main__":     c = GoogleFinanceAPI()     quote = c.get("RELIANCE","NSE")     print(quote)

Example 3: python stock prediction code

# Make sure that you have all these libaries available to run the code successfully
from pandas_datareader import data
import matplotlib.pyplot as plt
import pandas as pd
import datetime as dt
import urllib.request, json
import os
import numpy as np
import tensorflow as tf # This code has been tested with TensorFlow 1.6
from sklearn.preprocessing import MinMaxScaler