advanced-algorithmic-trading

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[
"Open", "High", "Low",
"Close", "Volume", "Adj Close"
],
axis=1, inplace=True
)
return df
The following function plot_candlesticks makes use of the Matplotlib candlestick_ohlc
method to create a financial candlestick chart of the provided price series. The majority of
the function involves specific Matplotlib formatting to achieve correct data formatting. The
comments explain each setting in more depth:
def plot_candlesticks(data, since):
"""
Plot a candlestick chart of the prices,
appropriately formatted for dates
"""
# Copy and reset the index of the dataframe
# to only use a subset of the data for plotting
df = copy.deepcopy(data)
df = df[df.index >= since]
df.reset_index(inplace=True)
df[’date_fmt’] = df[’Date’].apply(
lambda date: mdates.date2num(date.to_pydatetime())
)
# Set the axis formatting correctly for dates
# with Mondays highlighted as a "major" tick
mondays = WeekdayLocator(MONDAY)
alldays = DayLocator()
weekFormatter = DateFormatter(’%b %d’)
fig, ax = plt.subplots(figsize=(16,4))
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
# Plot the candlestick OHLC chart using black for
# up days and red for down days
csticks = candlestick_ohlc(
ax, df[
[’date_fmt’, ’Open’, ’High’, ’Low’, ’Close’]
].values, width=0.6,
colorup=’#000000’, colordown=’#ff0000’
)