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ajdapretnar avatar ajdapretnar commented on May 25, 2024 2

My requests fall outside the scope of what anyone is willing to implement here. I will do with manual preprocessing in pandas.

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ajdapretnar avatar ajdapretnar commented on May 25, 2024

Please, please, please. 🙏 I really need this for my analysis!

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kernc avatar kernc commented on May 25, 2024

See if it looks ok if you pass it xAxis_ordinal=False.

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ajdapretnar avatar ajdapretnar commented on May 25, 2024

After some troubles I've managed to set this up.

However, @lanzagar pointed out this is a different kind of a problem. Do I understand correctly that Line Chart only plots data points as they are. The main part is done in As Timeseries that transforms sequences in datetime. So if there is no entry for, say, 2018-02-14, this day will never get plotted in Line Chart... Should As Timeseries (or some other widget) add missing dates with 0 or NaN as an entry? 🤔 How would one see phenomenons that are recorded only once in a while? For Text analysis for example?

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kernc avatar kernc commented on May 25, 2024

Do I understand correctly that Line Chart only plots data points as they are.

I don't see how this is unexpected or a problem. Would you prefer it plotted data points not as they are? 😆

If there is no data at a particular point in time, it is just not there. A constant frequency is a very dubious and limiting assumption. xAxis_ordinal=True still might work, but if you need all data points on some interval constantly-spaced, why not make them so. You can do it in pandas:

df = df.resample('D').mean().fillna(0)

Supposing you already have daily values, it will keep them, filling in the missing days with zeros.

Supposing this fits in Orange, I guess Aggregate widget comes closest to resampling, with daily aggregation potentially adequate to filling in missing dates (optionally, on a checked checkbox). Or indeed maybe As Timeseries, optionally, on a checkbox.

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