def plot_bokeh(df, ticker):
p = figure(width=800, height=400, title=ticker.upper(), tools="")
hover = HoverTool(tooltips="""
<div>
<table>
<tr><td class="ttlab">Date:</td><td>@date_str</td></tr>
<tr><td class="ttlab">Close:</td><td>@close_str</td></tr>
</table>
</div>
""")
hover.mode = 'vline'
hover.line_policy = 'nearest'
p.add_tools(hover)
crosshair = CrosshairTool()
crosshair.dimensions = 'height'
crosshair.line_color = "#ffffff"
p.add_tools(crosshair)
dfcds = ColumnDataSource(df)
p.line('date', 'close', source=dfcds, color="#44ddaa")
p.xaxis.formatter = DatetimeTickFormatter(days=["%d %b"])
p.x_range = Range1d(df['date'].min(), df['date'].max())
p.toolbar.logo = None
p.toolbar_location = None
return p
def bokehplot(df_1, ticker):
"""Create a time-series line plot in Bokeh."""
p = figure(width=600, height=300, title=ticker.upper(), tools="")
hover = HoverTool(tooltips="""
<div>
<table>
<tr><td class="ttlab">Date:</td><td>@date_str</td></tr>
<tr><td class="ttlab">Close:</td><td>@close</td></tr>
</table>
</div>
""")
hover.mode = 'vline'
hover.line_policy = 'nearest'
p.add_tools(hover)
crosshair = CrosshairTool()
crosshair.dimensions = 'height'
crosshair.line_color = "#ffffff"
p.add_tools(crosshair)
dfcds = ColumnDataSource(df_1)
p.line('date', 'close', source=dfcds, color="#44ddaa")
p.xaxis.formatter = DatetimeTickFormatter(days=["%d %b"])
p.x_range = Range1d(df_1['date'].min(), df_1['date'].max())
p.toolbar.logo = None
p.toolbar_location = None
# Style plot
p.background_fill_color = "#234567"
p.border_fill_color = "#234567"
p.title.text_color = "#ffffff"
p.title.text_font_size = "1.25em"
p.axis.major_label_text_color = "#ffffff"
p.axis.major_label_text_font_size = "0.875em"
p.axis.axis_line_color = "#ffffff"
p.axis.major_tick_line_color = "#ffffff"
p.axis.minor_tick_line_color = "#ffffff"
p.xgrid.grid_line_color = None
p.ygrid.grid_line_alpha = 0.5
p.ygrid.grid_line_dash = [4, 6]
p.outline_line_color = None
p.yaxis.axis_label = "Closing price"
p.yaxis.axis_label_text_color = "#ffffff"
p.yaxis.axis_label_text_font_size = "1em"
p.yaxis.axis_label_text_font_style = "normal"
p.yaxis.axis_label_standoff = 12
return p
def plot_ticker(ticker):
# Retrieve and process data:
url = urlhead + ticker + urltail
page = requests.get(url)
json = page.json()
df = pd.DataFrame(json['Time Series (Daily)'])
# New DataFrame to append values:
df_1 = pd.DataFrame()
close = np.asarray(df.iloc[3])
df_1['date'] = pd.to_datetime(list(df))
df_1['close'] = close
# Last 30 days:
df_1 = df_1[0:30]
# Create a new column with dates as string:
df_1['date_str'] = df_1['date'].map(lambda x: x.strftime("%Y-%m-%d"))
dfcds = ColumnDataSource(df_1)
# Create Bokeh plot:
p = figure(width=600, height=300, title=ticker.upper(), tools="")
hover = HoverTool(tooltips = [
('Date', '@date_str'),
('Close', '@close')])
hover.mode = 'vline'
hover.line_policy = 'nearest'
p.add_tools(hover)
crosshair = CrosshairTool()
crosshair.dimensions = 'height'
p.add_tools(crosshair)
p.line('date', 'close', source = dfcds)
p.xaxis.formatter=DatetimeTickFormatter(days=["%d %b"])
p.x_range=Range1d(df_1['date'].min(), df_1['date'].max())
p.toolbar.logo = None
p.toolbar_location = None
return p
