Next, we want to calculate the change of the closing price with regard to the previous day's close. The pct_change() function in Pandas makes this task very easy:

import numpy as np


# Calculate percentage change versus the previous close
stock_df["Close_change"] = stock_df["Close"].pct_change()
# Since the DataFrame contain multiple companies' stock data, 
# the first record in the "Close_change" should be changed to
# NaN in order to prevent referencing the price of incorrect company.
stock_df.loc[stock_df["Date"]=="2017-01-03", "Close_change"] = np.NaN
stock_df.head()