Financial_Analysis.py

# coding: utf-8

# In[71]:


from pandas_datareader import data
import datetime
from bokeh.plotting import figure,show,output_file
from bokeh.embed import components
from bokeh.resources import CDN
#the start and end parameter should be in "datetime object" format
s = datetime.datetime(2017,7,1)
e = datetime.datetime(2018,1,10)
df = data.DataReader(name="GOOG", data_source="yahoo", start= s, end= e)

p = figure(x_axis_type="datetime", width=1000, height=300, responsive = True)
p.title.text = "Candlestick Chart(Google Stock Prices)"

#a function that determines whether the close price is higher than the open price
def inc_dec(c, o):
    if c > o:
        value = "Rise"
    elif c < o:
        value = "Drop"
    else:
        value = "Tie"
    return value


df["Status"] = [inc_dec(c,o) for c,o in zip(df.Close, df.Open)]  #list comprehension
df["Mid"] = (df.Open + df.Close)/2
df["Height"] = abs(df.Open - df.Close)

#we build two types of rectangles-- one where the close price is higher, another one where the close price is lower
hours_12 = 12*60*60*1000  #convert the width, which is 12 hours, to miliseconds

p.segment(df.index, df.High, df.index, df.Low, color="black")
p.rect(df.index[df.Status == "Rise"], df.Mid[df.Status == "Rise"],hours_12, df.Height[df.Status == "Rise"], 
       fill_color = "red", line_color = "black" )

p.rect(df.index[df.Status == "Drop"], df.Mid[df.Status == "Drop"],hours_12, df.Height[df.Status == "Drop"], 
       fill_color = "#228B22", line_color = "black" )

#load the html elements and JS script that containing all data with "embed" library
script1, div1, = components(p)

#load the bokeh JS and CSS files with "resources" library
cdn_js = CDN.js_files
cdn_css = CDN.css_files



# output_file("Graph.html")
# show(p)


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cdn_js


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cdn_css