Earnings per Share (EPS)
Calculate the earnings per share (EPS), a valuation ratio that measures the amount of net income earned per share of outstanding common stock.
The earnings per share (EPS) is a widely used financial metric that helps investors understand the profitability of a company on a per-share basis. It provides insight into the portion of a company’s earnings that is allocated to each outstanding share of its common stock. EPS is an important measure for investors and analysts when assessing a company’s financial performance and comparing it to other companies.
The formula is as follows:
\[\text{Earnings per Share} (\text{EPS}) = (\text{Net Income} - | \text{Preferred Dividends Paid} |) / \text{Weighted Average Shares}\]Also known as: EPS, net income per share.
Earnings per Share (EPS) in Python
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_earnings_per_share as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(["AAPL", "TSLA"], api_key="FINANCIAL_MODELING_PREP_KEY")
eps_ratios = toolkit.ratios.get_earnings_per_share()
Which returns:
| 2021 | 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|---|
| AAPL | 5.614 | 6.1132 | 6.1341 | 6.0836 | 7.465 |
| TSLA | 1.6341 | 3.6213 | 4.3067 | 2.0383 | 1.0754 |
Parameters
The function accepts the following parameters:
- include_dividends (bool, optional): Whether to include dividends in the EPS calculation. Defaults to False.
- diluted (bool, optional): Whether to use diluted earnings per share. Defaults to True.
- rounding (int, optional): The number of decimals to round the results to. Defaults to 4.
- growth (bool, optional): Whether to calculate the growth of the ratios. Defaults to False.
- lag (int | str, optional): The lag to use for the growth calculation. Defaults to 1.
- standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
- trailing (int): Defines whether to select a trailing period. E.g. when selecting 4 with quarterly data, the TTM is calculated.