Build Technical Indicators In Python - ROC

Rate of Change.py

# Rate of Change code

# Load the necessary packages and modules
from pandas_datareader import data as pdr
import matplotlib.pyplot as plt
import yfinance
import pandas as pd

# Rate of Change (ROC)
def ROC(data,n):
 N = data['Close'].diff(n)
 D = data['Close'].shift(n)
 ROC = pd.Series(N/D,name='Rate of Change')
 data = data.join(ROC)
 return data 
 
# Retrieve the NIFTY data from Yahoo finance:
data = pdr.get_data_yahoo("^NSEI", start="2015-06-01", end="2016-01-01") 
data = pd.DataFrame(data)

# Compute the 5-period Rate of Change for NIFTY
n = 5
NIFTY_ROC = ROC(data,n)
ROC = NIFTY_ROC['Rate of Change']

# Plotting the Price Series chart and the Ease Of Movement below
fig = plt.figure(figsize=(7,5))
ax = fig.add_subplot(2, 1, 1)
ax.set_xticklabels([])
plt.plot(data['Close'],lw=1)
plt.title('NSE Price Chart')
plt.ylabel('Close Price')
plt.grid(True)
bx = fig.add_subplot(2, 1, 2)
plt.plot(ROC,'k',lw=0.75,linestyle='-',label='ROC')
plt.legend(loc=2,prop={'size':9})
plt.ylabel('ROC values')
plt.grid(True)
plt.setp(plt.gca().get_xticklabels(), rotation=30)