Difference between revisions of "Bokeh: Plot Stock dengan Axis Datetime"
Jump to navigation
Jump to search
Onnowpurbo (talk | contribs) (New page: import time from numpy import cumprod, linspace, random from bokeh.plotting import figure, show, output_file, vplot, output_server num_points = 300 now = time.time() dt = 24*3600 # days ...) |
Onnowpurbo (talk | contribs) |
||
Line 1: | Line 1: | ||
− | + | Sumber: http://bokeh.pydata.org/en/latest/docs/gallery/correlation.html | |
− | |||
− | |||
− | num_points = 300 | + | import time |
+ | from numpy import cumprod, linspace, random | ||
+ | from bokeh.plotting import figure, show, output_file, vplot, output_server | ||
+ | |||
+ | num_points = 300 | ||
+ | |||
+ | now = time.time() | ||
+ | dt = 24*3600 # days in seconds | ||
+ | dates = linspace(now, now + num_points*dt, num_points) * 1000 # times in ms | ||
+ | acme = cumprod(random.lognormal(0.0, 0.04, size=num_points)) | ||
+ | choam = cumprod(random.lognormal(0.0, 0.04, size=num_points)) | ||
+ | TOOLS = "pan,wheel_zoom,box_zoom,reset,save" | ||
+ | |||
+ | output_file("correlation.html", title="correlation.py example") | ||
+ | |||
+ | r = figure(x_axis_type = "datetime", tools=TOOLS) | ||
+ | r.line(dates, acme, color='#1F78B4', legend='ACME') | ||
+ | r.line(dates, choam, color='#FB9A99', legend='CHOAM') | ||
+ | r.title = "Stock Returns" | ||
+ | r.grid.grid_line_alpha=0.3 | ||
+ | |||
+ | c = figure(tools=TOOLS) | ||
+ | c.circle(acme, choam, color='#A6CEE3', legend='close') | ||
+ | c.title = "ACME / CHOAM Correlations" | ||
+ | c.grid.grid_line_alpha=0.3 | ||
+ | |||
+ | # show(vplot(r, c)) # open a browser | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | + | ==Referensi== | |
− | + | * http://bokeh.pydata.org/en/latest/docs/gallery/correlation.html | |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− |
Latest revision as of 07:26, 30 November 2015
Sumber: http://bokeh.pydata.org/en/latest/docs/gallery/correlation.html
import time from numpy import cumprod, linspace, random from bokeh.plotting import figure, show, output_file, vplot, output_server num_points = 300 now = time.time() dt = 24*3600 # days in seconds dates = linspace(now, now + num_points*dt, num_points) * 1000 # times in ms acme = cumprod(random.lognormal(0.0, 0.04, size=num_points)) choam = cumprod(random.lognormal(0.0, 0.04, size=num_points)) TOOLS = "pan,wheel_zoom,box_zoom,reset,save" output_file("correlation.html", title="correlation.py example") r = figure(x_axis_type = "datetime", tools=TOOLS) r.line(dates, acme, color='#1F78B4', legend='ACME') r.line(dates, choam, color='#FB9A99', legend='CHOAM') r.title = "Stock Returns" r.grid.grid_line_alpha=0.3 c = figure(tools=TOOLS) c.circle(acme, choam, color='#A6CEE3', legend='close') c.title = "ACME / CHOAM Correlations" c.grid.grid_line_alpha=0.3 # show(vplot(r, c)) # open a browser