diff --git a/mlair/plotting/data_insight_plotting.py b/mlair/plotting/data_insight_plotting.py
index 95b482df3c2dd6d04d8b3029a2f9091d551d2829..c0e014fb18d1cd98b945d04e6407dd1cd2b281ca 100644
--- a/mlair/plotting/data_insight_plotting.py
+++ b/mlair/plotting/data_insight_plotting.py
@@ -17,7 +17,7 @@ from matplotlib import lines as mlines, pyplot as plt, patches as mpatches, date
 from astropy.timeseries import LombScargle
 
 from mlair.data_handler import DataCollection
-from mlair.helpers import TimeTrackingWrapper, to_list
+from mlair.helpers import TimeTrackingWrapper, to_list, remove_items
 from mlair.plotting.abstract_plot_class import AbstractPlotClass
 
 
@@ -829,9 +829,13 @@ class PlotPeriodogram(AbstractPlotClass):  # pragma: no cover
         plt.close('all')
 
 
-def f_proc(var, d_var, f_index):  # pragma: no cover
+def f_proc(var, d_var, f_index, time_dim="datetime"):  # pragma: no cover
     var_str = str(var)
-    t = (d_var.datetime - d_var.datetime[0]).astype("timedelta64[h]").values / np.timedelta64(1, "D")
+    t = (d_var[time_dim] - d_var[time_dim][0]).astype("timedelta64[h]").values / np.timedelta64(1, "D")
+    if len(d_var.shape) > 1:  # use only max value if dimensions are remaining (e.g. max(window) -> latest value)
+        to_remove = remove_items(d_var.coords.dims, time_dim)
+        for e in to_list(to_remove):
+            d_var = d_var.sel({e: d_var[e].max()})
     pgram = LombScargle(t, d_var.values.flatten(), nterms=1, normalization="psd").power(f_index)
     # f, pgram = LombScargle(t, d_var.values.flatten(), nterms=1, normalization="psd").autopower()
     return var_str, f_index, pgram
diff --git a/test/test_configuration/test_defaults.py b/test/test_configuration/test_defaults.py
index 16606d8f72c36b0d7eee852ef233b4373436e2f8..b6bdd9556f73ff711003b01c3a2b65a1c20c66d3 100644
--- a/test/test_configuration/test_defaults.py
+++ b/test/test_configuration/test_defaults.py
@@ -68,4 +68,4 @@ class TestAllDefaults:
         assert DEFAULT_PLOT_LIST == ["PlotMonthlySummary", "PlotStationMap", "PlotClimatologicalSkillScore",
                                      "PlotTimeSeries", "PlotCompetitiveSkillScore", "PlotBootstrapSkillScore",
                                      "PlotConditionalQuantiles", "PlotAvailability", "PlotAvailabilityHistogram",
-                                     "PlotDataHistogram"]
+                                     "PlotDataHistogram", "PlotPeriodogram"]