Hi! I have made the updates we discussed:

Sorry forgot to push all the final changes to github last night, but just did that! See if it will run if you follow the instructions above!

Hi team! I have updated github with a number of edits:

Here are the line charts:

Oh yes, I made some changes to the code and forgot to update Unique Devices comparison to 3 years instead of 1 year. Here is the fixed chart @Mayakp.wiki

Hi! I have updated map charts here. I used the old plasma colormap — let me know how you feel / if it's too uniform. I looked at it again and thought it was okay but can play around with seeing if I can add in white too.

Yes that's what I get:

I just realized the Percent of Totals shouldn't have +/- signs!

I made the requested updates.

Here are views for content quality!

I'll work on some of the other changes we talked about for Monday including —

Hi! I made some of the changes we discussed. I didn't have time to implement everything requested. The main thing is that I added YoY of 3 month Rolling Averages as Miriam suggested.— it should be more stable but is it harder to interpret?

@Miriam in response to your comment in the google invitation — The plots have different numbers from the line plots because these are using March data and the line plots before were using February data fyi!

Here are versions of the chart with the reader and editor data and percentage and Month over Month change values. I flipped the color palette as well.

Hi! I did a first pass at the map in matplotlib. Please let me know any feedback you have and I will make versions with the other data (editor growth, unique devices etc.) tomorrow.

Here are versions of the multi-chart figures with the yaxis bolded to highlight the different values:

Hi! Wanted to provide some updated view options. Everything below is for Active Editors — maybe we can decided which ones we prefer based on these and I will also apply the changes to Unique Devices.

Hi! I have updated versions of the regional view charts here:

• The charts are now sorted by their total value over the time period.
• The multi-figure generation is done programmatically and can adjust to however many columns the input dataset is, putting at most four charts per figure (in matplotlib, each "image" is a figure).
• The y axis standardization is done so that all charts have the same y axis range of ticks and number of ticks. It centers the chart as much as possible while keeping the same tick intervals (by finding the closest median divisible by the standard tick interval). It sets the minimum possible tick to 0. Right now it doesn't add a 2/3rds buffer on largest range, and this may take me a little longer to implement because it is a bit complicated.

Here is an updated version. Let me know how you think the white padding looks around the labels:

Hi! How does this look?

My thoughts on highlight is whether it should be done for more zoomed in versions or individual region graphs? I already think the charts put together can look a bit cluttered.

I have these updated graphs for Active Editors with standardized yaxis intervals but different ranges:

Here is the Regional Unique Devices charts — with normalized yaxes:

Hi! I did a first pass on these. Here is a version of the Regional Active Editors Data on a 2x2 graph:

Here is the New vs. Returning Editors chart:

Sorry for the deleted comments, fixed a few formatting issues! Here are the charts with February data and y-axis buffering:

Sorry! Made a small math error. Here is the chart with the 2/3rds ylimits.

Hi @Miriam I wanted to share this ticket which has some examples of charts we made for looking at country-level data: https://phabricator.wikimedia.org/T329588

Wanted to make a quick update to say this is what the Active Editors chart looks like with y-axis padding so that the line's peak and trough take up approximately 2/3. How do we feel about it? Should I add in more gridlines now that the line is taking up less space? Does it look too spaced out?

I wasn't sure if you wanted highlight circles on the unique devices chart but here is a version just in case:

Here are updated charts. I added in some code to automatically update the date created section. I want to set aside some time next week to go in and do some code cleanup so all the charts pull from the same functions, which will ensure better consistency (right now they're all just separate files).

Here is the updated chart:

Here it is with the same color gradient used in the table:

I made a new version that I think is easier to digest. It is a triple bar chart version of the original table.

A quick update - I'm working on some different ways of visualizing this and hope to post some more options tomorrow.

Here are updated visuals. Let me know if you want me to post them into each individual associated Phabricator task:

Here are some initial charts I made:

I didn't get this fully worked out earlier this week, but this is a version with year and month tick labels stacked. I changed the month to March so you can see bit more clearly the differentiation — even though the last piece of data is for January:

Here is the white box version with monthly dots and January data included:

Here are two initial charts:

Here are updated versions of the chart, revised based on feedback:

Hi! I tried a few different methods for presenting the unreliable data area:

I finished converting the code to ipynb. It all runs fine on Jupyter notebooks now on the server. The ipynb files will save the chart images after running. Here are the charts generated with Jupyter notebook compared with those generated locally. They look the same, as far as I can tell.

A brief update, and will write more tomorrow: I was able to start running the code on Jupyter notebooks. It requires some modifications to the code for pulling in the fonts, saving the files, and other small issues. I was able to have it produce the same chart as the locally run code, I believe.

Thank you so much! I'm able to login now. @BTullis Really appreciate it!

Hi! Sorry just wanted to check in on this again. I am able to ssh, but when I try to sign into Jupyter notebook with my shell username (xihua) and LDAP password (Wikitech password), it tells me username and password not valid. Could there possibly still be some issue? @Aklapper

Hi! I can now connect using xihua as my shell username but I am still not able to sign into Juypter notebook when I go to localhost:8880

Does this blue feel like a brighter color? The Wikimedia style guide doesn't have a bright red or I would use that.

Actually, I was thinking perhaps you want the Wikidata line in front:

Here is an initial version of the charts!

Hi! I noticed the fontsize for the x-axis was smaller than on the other charts I've made — I've fixed that now. Here are the three charts with the updated font size:

Here is a version with inline annotations and the YoY in black to match the other charts we've been making:

Hi! Thanks for the feedback! I made these updated charts:

When I run

I get this result

Please let me know if any of the images aren't showing up again!

Hi! Here are initial versions of the charts we discussed.

Here is a version with the annotations all inline and December data:

Here is the graph updated with December data. Currently, it is combining data from the metrics.tsv sheet which Maya is updating and the corrected_metrics.csv sheets which contains the data loss correction data.

Hi! I put my shell username incorrectly in the original ticket — it is actually xihua

Update: I added the code for these charts and others to this Github repository: https://github.com/wikimedia-research/key_product_metrics

Update: I added the code for these charts and others to this Github repository: https://github.com/wikimedia-research/key_product_metrics

Here is a third option:

Hi! Here is a first pass at this graph. I made two versions because having the YoY annotation and the data label at the end of the graph felt quite crowded together, so here are two potential options?

Yes sorry — I don't know why the image uploads didn't all work last time:

Here is a version with the data labels on the chart. Do you think it looks cluttered with the data label and YoY annotation so close together?

Here is a version with a split y-axis. I'm not sure if we'll want to explore this. I haven't added in the annotations which will need to done differently than with the unsplit chart.

Here is an initial draft of the chart:

A few chart updates per our last meeting. These changes are all implemented now:

• Move Data Loss Correction Area to in back of main blue line
• Take out gray line under Data Loss Correction area
• For programmatically calculated stats, round to tenth of a percent (ex: -0.1% YoY)
• Take out “Month” x-axis label (obvious w tick labels) — for both
• I changed the gray to be one from the Wiki style guide because before it was a black with an alpha.

Here are updated versions of both graphs with all the changes listed in the last comment made.

To Do for Graphs per meeting with Kate:

Here is an updated Active Editors Graph:

• Left-adjusted title
• Increased fonts everywhere
• Cleaned up y-axis and y-tick labels
• Changed vertical grid lines to solid thin instead of dashed

Here is the current version of the Content Interactions graph. A few things I did:

• Changed data to interactions instead of pageviews
• Changed code to matplotlib instead of plotly
• Put in a dictionary of wmf colors and fonts instead of directly referencing hex codes
• Added yellow circles highlighting 2019 and 2022
• Left-adjuseted the title
• Cleaned up vertical axis (removed title, used 100K notation)
• Increased fonts everywhere

Some things to work on or explore:

• Highlighting the calendar years like Mikhail suggested
• Other colorings and line styles for the data loss area
• Currently the plot is labeled with the annotate function, but might be better to have it be a text box with a bounding box so the box size can be adjusted more easily

Here is a version of the Active Editors chart made using matplotlib. @kzimmerman Let me know if there are any changes you want me to look into before Monday: