Part 0: Import packages¶

In [26]:

import yfinance as yf
import matplotlib.pyplot as plt
%matplotlib inline

Part 1: Download stock data from Yahoo Finance¶

In [27]:

stock = yf.download("GOOG", "2019-09-15", "2019-09-25")
stock.head()

[*********************100%***********************]  1 of 1 downloaded

Out[27]:

	Open	High	Low	Close	Adj Close	Volume
Date
2019-09-16	1229.52	1239.56	1225.61	1231.30	1231.30	1053300
2019-09-17	1230.40	1235.00	1223.69	1229.15	1229.15	955100
2019-09-18	1227.51	1235.61	1216.53	1232.41	1232.41	1135100
2019-09-19	1232.06	1244.44	1232.02	1238.71	1238.71	996000
2019-09-20	1233.12	1243.32	1223.08	1229.93	1229.93	2270000

Part 2: Save the data as csv file¶

In [21]:

stock.to_csv("stock.csv")

Part 3: Visualize the trend of the stock¶

In [23]:

fig = plt.figure(figsize = (10, 5))
plt.plot(stock["Open"], color = "red")
plt.title("Google open price")
plt.show();

In [25]:

fig = plt.figure(figsize = (10, 5))
plt.plot(stock["Open"], color = "red")
plt.plot(stock["Close"], color = "green")
plt.title("Google open price")
plt.legend()
plt.show();

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