Many 'Fitbit' users, and R-friendly 'Fitbit' users
    especially, have found themselves curious about their 'Fitbit' data.
    'Fitbit' aggregates a large amount of personal data, much of which is
    interesting for personal research and to satisfy curiosity, and is
    even potentially useful in medical settings. The goal of 'fitbitr' is
    to make interfacing with the 'Fitbit' API as streamlined as possible,
    to make it simple for R users of all backgrounds and comfort levels to
    analyze their 'Fitbit' data and do whatever they want with it!
    Currently, 'fitbitr' includes methods for pulling data on activity,
    sleep, and heart rate, but this list is likely to grow in the future
    as the package gains more traction and more requests for new methods
    to be implemented come in.  You can find details on the 'Fitbit' API
    at <https://dev.fitbit.com/build/reference/web-api/>.

Scrapes data from Fitbit <http://www.fitbit.com>. This does not use the official
    API, but instead uses the API that the web dashboard uses to generate the graphs
    displayed on the dashboard after login at <http://www.fitbit.com>.

Connection to the 'Fitbit' Web API <https://dev.fitbit.com/build/reference/web-api/> by including 'ggplot2' Visualizations, 'Leaflet' and 3-dimensional 'Rayshader' Maps. The 3-dimensional 'Rayshader' Map requires the installation of the 'CopernicusDEM' R package which includes the 30- and 90-meter elevation data.

Fit data to an ellipse, hyperbola, or parabola. Bootstrapping is available when needed. The conic curve can be rotated through an  arbitrary angle and the fit will still succeed. Helper functions are  provided to convert generator coefficients from one style to another, generate test data sets, rotate conic section parameters, and so on. References include Nikolai Chernov (2014) "Fitting ellipses, circles, and lines by  least squares" <https://people.cas.uab.edu/~mosya/cl/>; A. W. Fitzgibbon, M. Pilu, R. B. Fisher (1999) "Direct Least Squares Fitting of Ellipses" IEEE Trans. PAMI,  Vol. 21, pages 476-48; N. Chernov, Q. Huang, and H. Ma (2014) "Fitting quadratic curves to data points", British Journal of Mathematics & Computer Science, 4, 33-60; N. Chernov and H. Ma  (2011) "Least squares fitting of quadratic curves and surfaces", Computer Vision, Editor S. R. Yoshida, Nova Science Publishers, pp. 285-302.