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@@ -95,8 +95,8 @@ def smallValues(df):
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def avgPerMarkerNo(df, markerNo):
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- print(f"\naverage time for {markerNo} markers")
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- print("number of measurements")
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+ print(f"\nresult of {markerNo} markers\n")
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+ print("number of measurements:")
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df = df.loc[df["markers"] == markerNo]
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resDf = pd.DataFrame(columns=["id", "timeMean", "rating"])
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for mapId, mapDf in df.groupby(["id"]):
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@@ -109,7 +109,9 @@ def avgPerMarkerNo(df, markerNo):
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resDf = resDf.append({"id": "mapbox_" + markerType, "timeMean": typeDf["time"].mean()}, ignore_index=True)
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resDf = resDf.assign(rating=lambda x: (round(4-((4-0)/(max(resDf["timeMean"])-min(resDf["timeMean"]))*(x["timeMean"]-max(resDf["timeMean"]))+4))))
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+ print("\naverage time:")
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print(resDf)
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+ print("--------------------------------------")
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def timeMapsHighlight(df, plotTitle="mapsHightlight.png"):
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