What time-series-specific EDA should you do?

medium

Answer

$(1) Plot the raw series and its rolling mean / median at multiple window sizes.$
$(2) Decompose into trend + seasonality + residual (STL).$
$(3) Autocorrelation (ACF) and partial autocorrelation (PACF) plots to detect lag structure.$
$(4) Stationarity tests (ADF, KPSS).$
$(5) Change-point detection.$
$(6) Frequency-domain view (spectrogram) for periodic components.$
$(7) Compare series across shared time windows and groups.$
$Foundation for choosing between ARIMA / Prophet / Bayesian structural time series.$

Check yourself — multiple choice

Same as tabular
Rolling stats + STL decomp + ACF/PACF + stationarity tests + change points + spectrogram + cross-series comparison
Only mean/variance
Impossible

Time-series EDA: rolling stats / decomposition / ACF-PACF / stationarity / change points.

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