I created 3 charts regarding rating distribution in Codeforces.

[Updated] Slightly change chart 2 and 3 to show rating colors.

- Rating distribution in Codeforces

This chart is rating distribution in Codeforcers similar as one shown in TopCoder profile.

Purple markers and lines show cumulative rate. - Coderforces vs TopCoder in Japanese participants

This scatter chart shows Codeforces ratings and TopCoder ratings of who met the following conditions:

- has the same handle name both in Codeforces and TopCoder.

- is listed in Japanese TopCoders

- participates more than or equal to 5 times both in Coderforces and TopCoder

There are 56 samples. Correlation coefficient is 0.87.

Of course, even though they have the same handle names, they could be different person. There should be who uses different handle name between Codeforces and TopCoder. So, this chart is far from complete. However, it could show rough image. - Codeforces vs TopCoder

This scatter chart shows Codeforces ratings and TopCoder ratings of who met the following conditions:

- has the same handle name both in Codeforces and TopCoder.

- participates more than or equal to 5 times both in Coderforces and TopCoder

There are 427 samples. Correlation coefficient is 0.82.

The note for 2nd chart is also applicable to this chart.

Rating distribution looks like TopCoder's. It is good because it means that the probability of bug in rating calculation function is lesser )

Pity that I have another handle on TopCoder, but very similar(Fefer_Ivan)

They are not completely linear. CodeForces rating is based on logistic distribution, while TopCoder rating is based on normal distribution.

The graph that you see here show the market interest rate that up and down within few hours.The australian writings essay service share complete year graph and if you see then you understand where market going. Nice.