Calculates and collects all Efficiency Ratios based on the provided data.

All Efficiency Ratios in Python

collect_efficiency_ratios is part of the Ratios module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call collect_efficiency_ratios as shown below.

from financetoolkit import Toolkit

toolkit = Toolkit(["AAPL", "TSLA"], api_key="FINANCIAL_MODELING_PREP_KEY")

toolkit.ratios.collect_efficiency_ratios().loc['AAPL']

Which returns:

  2021 2022 2023 2024 2025
Accounts Payable Turnover Ratio 4.3887 3.7609 3.3795 3.1975 3.1834
SGA-to-Revenue Ratio 0.0601 0.0636 0.065 0.0667 0.0663
Fixed Asset Turnover 1.846 1.8192 1.7979 1.8576 1.9664
Asset Turnover Ratio 1.0841 1.1206 1.0868 1.0899 1.1493
Operating Ratio 0.7022 0.6971 0.7018 0.6849 0.6803
R&D Intensity Ratio 0.0599 0.0666 0.078 0.0802 0.083
S&M to Revenue Ratio 0 0 0 0.0477 0
G&A to Revenue Ratio 0 0 0 0.0191 0.0663
SBC to Revenue Ratio 0.0216 0.0229 0.0283 0.0299 0.0309
Deferred Revenue Ratio 0.0208 0.0201 0.021 0.0211 0.0218

Parameters

collect_efficiency_ratios accepts the following parameters:

  • days (int, optional): The number of days to use for the calculation. Defaults to 365.
  • 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.
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