avoid spurious downturns and 'spamming' of top-10-censorship list

top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Starting from the top, Christmas Island has a median user count of one in 2016 with the third quartile being two. Also, Netherlands Antilles have a median of two connections, Kiribati, British Indian Ocean Territory, Norfolk Island, and Tokelau each a 2016 user count median of one.

Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attached a simple patch.

added component::metrics/website owner::metrics-team priority::medium resolution::fixed severity::normal status::closed type::defect labels

Trac:

Trac:

Trac:
Description: top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attache a simple path.

to

top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attache a simple path.

Please review my branch.

Trac:
Status: new to needs_review

Trac:
Description: top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attache a simple path.

to

top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Starting from the top, Christmas Island has a median user count of one in 2016 with the third quartile being two. Also, Netherlands Antilles have a median of two connections, Kiribati, British Indian Ocean Territory, Norfolk Island, and Tokelau each a 2016 user count median of one.

Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attached a simple path.

Trac:
Description: top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Starting from the top, Christmas Island has a median user count of one in 2016 with the third quartile being two. Also, Netherlands Antilles have a median of two connections, Kiribati, British Indian Ocean Territory, Norfolk Island, and Tokelau each a 2016 user count median of one.

Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attached a simple path.

to

top 10 list for 2016 The marked countries have a very low client count and the predicted lower value is zero. Starting from the top, Christmas Island has a median user count of one in 2016 with the third quartile being two. Also, Netherlands Antilles have a median of two connections, Kiribati, British Indian Ocean Territory, Norfolk Island, and Tokelau each a 2016 user count median of one.

Similarly, the downturns in country specific censorship events, for example Netherlands Antilles in 2016

I attached a simple patch.

Oh, very good catch! Your fix above only removes false dots from graphs, but it doesn't reduce false table entries which is done in website/rserve/tables.R. I extended your patch, cherry-picked it, merged it to master, and deployed it. Closing. Thanks!

Trac:
Status: needs_review to closed
Resolution: N/A to fixed

closed