  We present the pyerrors python package for statistical error analysis of
Monte Carlo data. Linear error propagation using automatic differentiation in
an object oriented framework is combined with the $\Gamma$-method for a
reliable estimation of autocorrelation times. Data from different sources can
easily be combined, keeping the information on the origin of error components
intact throughout the analysis. pyerrors can be smoothly integrated into the
existing scientific python ecosystem which allows for efficient and compact
analyses.
