How to pull Investment Valuation Ratios using Python

Making an investment decision is as hard as it is important. Using solid investment valuation ratios can help make the decision much easier. In a previous article, we explained what investment valuation is and 5 crucial investment valuation ratios to be familiar with. In this article, we simply explain how to pull these 5 investment valuation ratios from the FMP financial ratio API.

The four ratios we will investigate are:

1. Price to Earnings Ratio
2. Price/Earnings to Growth Ratio
3. Price to Sales Ratio
4. Price to Book Value Ratio

Step 1: Load FMP Developer API Docs Website

From this article go to the top right of the page, click “Developers” and then click "API Docs" from the list below. Make sure you are logged into your account. You should see this in the top right corner:

Otherwise, click login and enter your account credentials.

A key piece of information that'll want to write down in a safely secured location is your API Key. This is located in the second section of the API docs page which is called "Your Details". See in the example below, it should be a long series of letters and numbers. As with any key, this unlocks something and in this case it ensures that you have permission to access the API you are requesting. Make sure to keep your key private and safely secured if you are storing it somewhere on your computer. It is against our terms and conditions to share your API key with anyone - your account will be blocked and investigated if we suspect you are doing this.

Step 2: Copy the URL for the API you want to access

For this example, we are going to pull from the company profile API. So scroll down to the section that says Company Financial Ratios (You can also use the navigation bar on the left hand side of the screen) and you will see the following

Then right click on the box that contains something that looks like a condensed URL. In this case: api/v3/ratios/APPL?limit=40

Step 3: Open Your Python Environment and copy URL

Now you'll need to open up your Python environment to start writing code. To start with, create a variable called “URL” and give the string version of the URL you copied in step 2. You can simply use Ctrl + V (or cmd + V for mac users) to paste the url you copied.

ERROR ALERT: Make sure to add inverted commas (otherwise called quotation marks) around the copied URL to make the URL variable a string.

url = “https://financialmodelingprep.com/api/v3/ratios/AAPL?limit=40&apikey=demo”

If you're copying directly from this page you'll need to make sure that you replace the ‘demo' with your API key

Step 4: Write the Python code to access the Financial Statement

To learn more about exactly what all the following code means and why it works, visit out guide - How to call a Financial Modeling Prep API

try: # For Python 3.0 and later from urllib.request import urlopen except ImportError: # Fall back to Python 2's urllib2 from urllib2 import urlopen import json def get_jsonparsed_data(url): """ Receive the content of ``url``, parse it as JSON and return the object. Parameters ---------- url : str Returns ------- dict """ response = urlopen(url) data = response.read().decode("utf-8") return json.loads(data) url = ("https://financialmodelingprep.com/api/v3/ratios/AAPL?limit=40&apikey=demo") Ratios_APPL = get_jsonparsed_data(url)

The variable that we have created called Ratios_APPL will have all the financial ratios from the last 40 years of Apple Inc's financial statements in the JSON format.

Step 5: Pull out the individual investment ratios

The debt ratios listed at the beginning of this article aren't named exactly the same way in the JSON because we want to keep the code clean and we can't use spaces in python when naming individual variables and objects. The JSON format stores the data as a list of dictionaries for each year. Each dictionary is made up of keys and values. In this case, each key is a financial ratio and the value is the figure for that ratio. The key name of each debt ratio in the JSON file is as follows:

Investment Valuation Ratio	Key Name
Price to Earnings Ratio	'priceEarningsRatio'
Price/earnings to growth ratio	'priceEarningsToGrowthRatio'
Price to sales ratio	'priceToSalesRatio'
Price to book value ratio	'priceBookValueRatio'

Let's say we want to pull out Apple's 2020 Price to Earnings. We would use the following code:

Ratios_APPL[0]['priceEarningsRatio']

It's important to note that the format of this data means that as you index higher, you'll go further back in time. Here's a little bit of code that will help you understand how to index for a specific year:

for i in range(0,len(Ratios_APPL)): print(i, Ratios_APPL[i]['date'])

This will return a print out of each index and its corresponding date taken:

Examples pulling Investment valuation ratios

Pooling Investment Valuation Ratios into a list

To be able to simply loop through all the investment valuation ratios it's useful to make a list with the codified names of each ratio. Here's how:

investmentRatios = [ 'priceEarningsRatio', 'priceEarningsToGrowthRatio', 'priceToSalesRatio', 'priceBookValueRatio', ]

For Loop to list all of the Investment Ratios for a given year

Here's a block of code that will give you the investment valuation ratios for a given year using the indexes shown above:

APPL_2020_Ratios = [] #This is an empty list of that the next for loop will fill for i in range(0,len(investmentRatios)): APPL_2020_Ratios.append(Ratios_APPL[0][investmentRatios[i]]) #This adds the ratio i to the list of Apple's ratios print(f"{investmentRatios[i]} = {APPL_2020_Ratios[i]: .2f}")

Function to print the Investment Valuation Ratios for a specific ticker in a specific year

In this example, we create a function so that you can easily use it to pull the investment valuation ratios for any stock ticker in any year:

def investmentRatio_ticker(ticker , yearindex): url = f"https://financialmodelingprep.com/api/v3/ratios/{ticker}?limit=40&apikey=demo" ticker_ratios = get_jsonparsed_data(url) investmentRatios = [ 'priceEarningsRatio', 'priceEarningsToGrowthRatio', 'priceToSalesRatio', 'priceBookValueRatio', ] Ratios = [] #This is an empty list of that the next for loop will fill for i in range(0,len(investmentRatios)): Ratios.append(ticker_ratios[0][investmentRatios[i]]) #This adds the ratio i to the list of Apple's ratios print(f"{investmentRatios[i]} = {Ratios[i]: .2f}")

As you can see above, in the cell after I created the function I called it to print out the Amazon investment Valuation ratios from 2020.