API Price and Volume graphs

 API Price and Volume graphs

The following programs leverage the finance API to retrieve price and volume for 1 year period and build graphs from the data.

Need project name set (your project

PROJECT_ID = 'consummate-tine-433617-f0'

Need bucket name set (note need your bucket and needs to be public)

bucket_name = "yahoostocks"

Need yfinance installed

pip install yfinance --upgrade --no-cache-dir

Need mathplotlib installed

pip install matplotlib

Need pandas library installed

pip3 install pandas

Send me links to the graphs from the buckets

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import pandas as pd                  # Data frame

import yfinance as yf                # yfinance API

from datetime import date, timedelta # Date / time modules

from matplotlib import pyplot as plt # Plotting Library

from google.cloud import storage     # Leverage Google Storage Buckets

#Google Cloud project ID

# use  your project ID from Google cloud

PROJECT_ID = 'consummate-tine-433617-f0'

# The ID of your GCS bucket (bucket name)

bucket_name = "yahoostocks"

storage_client = storage.Client()

bucket = storage_client.bucket(bucket_name)

#calculate starting and ending date of range you wish to retrieve

Start = date.today() - timedelta(365)

Start.strftime('%Y-%m-%d')

End = date.today() + timedelta(2)

End.strftime('%Y-%m-%d')

# function to get daily stock volume of shares traded

def closing_volume(ticker):

    Asset = pd.DataFrame(yf.download(ticker, start=Start,

      end=End)['Volume'])    

    return Asset

# call function for the symbol AMZN

AMAZON = closing_volume('AMZN')

# plot AMZN volume graph

plt.plot(AMAZON, color='purple', linewidth=2)

plt.title('AMAZON Shares Traded Daily')

plt.ylabel('Volume (#)')

plt.xlabel('Date')

plt.show()

plt.savefig('amzn_vol.png')

# send plot file to your bucket

plot_filename = 'amzn_vol.png'

destination_blob_name = f'stocks/{plot_filename}'

source_file_name = 'amzn_vol.png'

blob = bucket.blob(destination_blob_name)

blob.upload_from_filename(source_file_name)  #upload file to specified destination

print(f'File {source_file_name} uploaded to {destination_blob_name}.')

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import pandas as pd

import yfinance as yf

from datetime import date, timedelta

from matplotlib import pyplot as plt

from google.cloud import storage

#Google Cloud project ID

PROJECT_ID = 'consummate-tine-433617-f0'

# The ID of your GCS bucket

bucket_name = "yahoostocks"

storage_client = storage.Client()

bucket = storage_client.bucket(bucket_name)

Start = date.today() - timedelta(365)

Start.strftime('%Y-%m-%d')

End = date.today() + timedelta(2)

End.strftime('%Y-%m-%d')

def closing_price(ticker):

    Asset = pd.DataFrame(yf.download(ticker, start=Start,

      end=End)['Adj Close'])    

    return Asset

AMAZON = closing_price('AMZN')

plt.plot(AMAZON, color='purple', linewidth=2)

plt.title('AMAZON Performance')

plt.ylabel('Price ($)')

plt.xlabel('Date')

plt.show()

plt.savefig('amzn_prc.png')

plot_filename = 'amzn_prc.png'

destination_blob_name = f'stocks/{plot_filename}'

source_file_name = 'amzn_prc.png'

blob = bucket.blob(destination_blob_name)

blob.upload_from_filename(source_file_name)  #upload file to specified destination

print(f'File {source_file_name} uploaded to {destination_blob_name}.')