Facete | Widgets for browsing spatial data in SPARQL endpoints

I have a data series consisting of monthly sales for individual fiscal years. I am using a pandas dataframe to store the data. Each fiscal year starts on the first day of March and ends on the last day of the February in the following year. I am using a plotly facet plot to show the months of the year vertically aligned, so that March 2021 is below March 2020, and so on.

Despite using a categorical variable for the x-axis the ordering is slightly off. I have tried sorting using a 'yearmon' variable with unique values, but that doesn't work either. Specifically, in the plot below the values for Jan and Feb in 2018 are blank, and Jan and Feb 2021 are also out of place. How can I get the facet to show contiguous data without these problems? Edit: I have a feeling it is related to the ordering of the categories, but haven't managed to pin it down yet.

I have this sample dataset for three labeled images:

I have a dataset of academic journals and various related measures. One measure is a Tier, 0-15, that represents "how important" a journal is to our campus (imperfectly, but still).

I want to make a series of scatter plots listing the usage (y) vs. cost (x), but then Facet them by Tier. I can get a Faceted chart to work, but it makes 16 separate charts. I found a way to specify the Sort order, but that seems to only take strings (the GOOG, MSFT example).

What I want is to specify Faceting based on groups of Tiers, which are numeric values - have one graph showing the scatterplot of datapoints, but only with data from those journals in Tiers 1-4. Then another with only Tiers 5-8, then Tiers 9-12, and then 13-15. I can't seem to find a way to specify a grouping of continuous values.

i am trying to add a column 'Number' in my report, so far all i can do is use row_number()

I'm trying to add set of markers with text above the top of a faceted chart to indicate certain points of interest in the value of x. Its important that they appear in the right position left to right (as per the main scale), including when the overall ggplot changes size.

Something like this...

However, I'm struggling to:

• place it in the right vertical position (above the facets). In my reprex below (a simplified version of the original), I tried using a value of the factor (Merc450 SLC), but this causes issues such as adding that to every facet including when it is not part of that facet and doesn't actually go high enough. I also tried converting the factor to a number using as.integer, but this causes every facet to include all factor values, when they obviously shouldn't
• apply to the chart as a whole, not each facet

Note that in the full solution, the marker x values are independent of the main data.

I have tried using cowplot to draw it separately and overlay it, but that seems to: affect the overall scale of the main plot, with the facet titles on the right being cropped is not reliable in placing the markers at the exact location along the x scale

Any pointers welcome.

Does anyone have suggestions to avoid the error?

ValueError: Faceted charts cannot be layered.

With this Pandas Dataframe

I am trying to refactor our ElasticSearch backend and right now, we are using a different index, per language. Which means we have to do a lot of excess insertions (since we have 8 that we need to support).

The problem is that languages will be added / removed dynamically sometimes. Furthermore, a lot of static data is attached to the items as well, think about prices, feature ids, availability, statuses, etc. These are all used in combination with aggregations for faceted search.

To have all this data duplicated for each language, in a separate index, seems rather cumbersome. Therefore I am wondering if there is a better solution (perhaps using properties), to index the name of the item, in the same index, for different languages with the according analyzer for each property.

If so, I would like to be able to delete a defined language, and insert a defined language as well. Which I now do by by creating / dropping indices accordingly.

I have tried a number of approaches (multiple indexes, language detection, etc) but I have not yet found something that felt like 'the right way'. In short, the current approach works for now, but it just feels awkward.

The actual mapping is as follows, and an index documents-%lang% is used:

I am trying to follow the steps given in this post to make a faceted pie chart plot.

I'm working on a gene expression profile plot where I've faceted the profiles by cluster number. I've been able to get the plot pretty close to what I'm looking for, but I would like to be able to make this with the panel labels in the upper right-hand corner of each respective plotting area.

Here are my data: