In T358095#9676136, @Mary_agiamah wrote:Hello,
My Boxplots for pred_qual are like this. It doesn't seem right to me. I merged my tables correctly, created a months columns from the revision_timestamp. I am plotting the box_plot with my x as pre_qual column and y as the month column. Can anyone shed light on how to make my plot show better?. By the way, the subplots are for different articles for the year 2019 monthly
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Apr 1 2024
Apr 1 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Mar 31 2024
Mar 31 2024
Ansha_Pashine added a comment to T356498: Outreachy Project: Build a data visualization tool for the evolution of Wikipedia articles maintained by WikiProjects.
In T356498#9674794, @Jenniemeka wrote:please what link are we to submit for the contribution since the project doesn't have a Github repository?
I have both the netlify link and a github link I dot know which one to submit
Mar 27 2024
Mar 27 2024
Ansha_Pashine added a comment to T356498: Outreachy Project: Build a data visualization tool for the evolution of Wikipedia articles maintained by WikiProjects.
In T356498#9665558, @Pablo wrote:@Ansha_Pashine: the dataset we have provided for this task only contains articles maintained by WikiProject Climate change, so there is no need to explore other Wikiprojects at this time.
Ansha_Pashine added a comment to T356498: Outreachy Project: Build a data visualization tool for the evolution of Wikipedia articles maintained by WikiProjects.
Hello, @Pablo @Isaac @CMyrick-WMF Can you all please tell me about the categorization of Wikiprojects: Active, Defunct, Inactive, Semi-active, Uncategorized in detail? Which types of projects are good for performing data visualization and analysis?
Mar 26 2024
Mar 26 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9660332, @GonzaGertrude wrote:In T358095#9653903, @CMyrick-WMF wrote:Reminder from the project mentors: deadline to submit initial notebook today
We will be closing this project to new contributors today, March 22, at 9:00 PM UTC. Please see our previous message for details.
After today's deadline,
- If you have specific questions about your notebook you are welcome to ask.
- You may continue working on your notebook/final applications until the Outreachy deadline of April 2.
NOTE: Please email the link to your public PAWS notebook to all three of the mentors. Our email addresses are available on the Outeachy project page, in the contact info for "Isaac Johnson", "Caroline Myrick", and "Pablo Aragón".Hello @CMyrick-WMF
Can I ask questions about my notebook if I received feedback?
Mar 20 2024
Mar 20 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9644034, @Shruti799 wrote:
Mar 17 2024
Mar 17 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9636001, @PromzyBA wrote:Please I did that maybe am not doing it right. Can you walk me through how to do that?
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9635995, @PromzyBA wrote:
Mar 16 2024
Mar 16 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9635610, @Udonels wrote:In T358095#9635564, @Ansha_Pashine wrote:Do we necessarily need to include the revision timestamps or pageview counts in our visualization?
It's not specified but we accessed the data for the pageview counts and this made me think over itYou can include what you want in as much as it buttresses your thought process. However, only include it after you've accomplished the main tasks specified in the description.
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9635575, @Shruti799 wrote:In T358095#9635564, @Ansha_Pashine wrote:Do we necessarily need to include the revision timestamps or pageview counts in our visualization?
It's not specified but we accessed the data for the pageview counts and this made me think over itWe need to visualize and plot for feature values(page_length, num_refs, num_wikilinks, num_categories, num_media, num_headings) and quality score (pred_qual) by choosing different granularities and not for pageviews count.
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Do we necessarily need to include the revision timestamps or pageview counts in our visualization?
It's not specified but we accessed the data for the pageview counts and this made me think over it
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9635410, @Shruti799 wrote:In T358095#9635406, @Ansha_Pashine wrote:What exactly are your start and end dates?
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Hello Everyone!! I'm having an error with one date :
I tried setting the start and end dates after (2010-06-07) but still it throws the same error. I have also tried to print the output for different articles but the issue persists. Can someone please have a look at this?
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9634498, @CMyrick-WMF wrote:Message from the project mentors regarding pageviews
We've seen some questions regarding the pageviews component and wanted to share a few general tips:
- The data is only available starting from July 2015.
- If you want to use the data to understand how quality trends relate to article popularity, you can always just use a sample, such as pageviews from February 2024 only.
- If you're getting missing counts, it can be useful to look at the detailed result from the API to understand why (e.g., https://wikimedia.org/api/rest_v1/metrics/pageviews/per-article/en.wikipedia/...) or read the documentation.
Mar 11 2024
Mar 11 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Hello Everyone, I'm getting an error after running the try except block. I've tried implementing other codes and have also tried to change the start and end dates as well as article names. But still, the issue persists. Any help here would certainly enhance my task completion, Thank you.
Mar 9 2024
Mar 9 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9615694, @Satoshi_Sh wrote:In T358095#9615135, @Ansha_Pashine wrote:Hello Everyone!!
I'm stuck with a Key error of 'revision_timestamp' column. As you all might get to know the dataset contains this column, still its throwing an error. I have tried printing column names but still, the output didn't print this column.
can anyone plz help me a bit about this or anyone got the same issue ?I'm not 100% sure unless I check your whole notebook, but does that "df" data frame contain the "revision_timestamp" column? You might have another data frame.
You can double-check it with something like this.
`# Check dataframe columns
columns =df.columns
print(columns)`
Mar 8 2024
Mar 8 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Hello Everyone!!
I'm stuck with a Key error of 'revision_timestamp' column. As you all might get to know the dataset contains this column, still its throwing an error. I have tried printing column names but still, the output didn't print this column.
Mar 7 2024
Mar 7 2024
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
In T358095#9610961, @MahimaSinghal wrote:In T358095#9610845, @Thembo42 wrote:In T358095#9610306, @MahimaSinghal wrote:Hi @Pablo @Isaac @CMyrick-WMF
I hope you're all doing well. I've been working on the microtask T358095 and I'm now at the stage where I need to submit my work for review. Could you please let me know where I can submit my work for review?Just to provide some context, here's an overview of the work I've done:
- Extracted page view counts for Wikipedia articles.
- Explored and visualized the evolution of individual articles and a sample of Climate change articles by visualizing feature values and quality scores over time.
- Analyzed the distribution of quality scores by year using boxplots.
I'm looking forward to receiving feedback on my work.
Thank you!
Mahima Agarwalweldone, The details how to send are explicit in the task description.
It is mentioned to mail the mentors directly. However, I realized that I don't have access to the email addresses of the mentors to send my submission.
Would it be possible for someone to provide me with the email addresses of the mentors? I would greatly appreciate it.
Ansha_Pashine added a comment to T358095: Outreachy Application Task: Tutorial for Wikipedia language-agnostic article quality modeling data.
Hello Everyone!!
While performing the first task I got some queries:
- Do we need to extract pageview counts for some selected articles?
- Or can we randomly choose any article to demonstrate and extract counts?
any help or clarification will prove to be beneficial for me.
Thank You.
Mar 6 2024
Mar 6 2024
Ansha_Pashine added a comment to T356498: Outreachy Project: Build a data visualization tool for the evolution of Wikipedia articles maintained by WikiProjects.
Hello everyone. I'm Ansha from India and I would like to join the Wikimedia community and contribute to the projects by learning and engaging most efficiently.
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