# Era distribution

**URL:** <https://forum.numer.ai/t/era-distribution/3875>\
**Category:** Data Science\
**Created:** [July 29, 2021, 3:38pm UTC](https://forum.numer.ai/t/era-distribution/3875 "2021-07-29T15:38:07Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![marianotir](https://avatars.discourse-cdn.com/v4/letter/m/b19c9b/32.png) [@marianotir](https://forum.numer.ai/u/marianotir)\
**Post date:** [July 29, 2021, 3:38pm UTC](https://forum.numer.ai/t/era-distribution/3875/1 "2021-07-29T15:38:07Z")

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Interesting era distribution. Am I missing something? I was expecting to have continous era. Or maybe the numbers does not matter? I expected a longer train era.

> import pandas as pd  
> import numpy as np  
> import plotly.express as px  
> import plotly.graph\_objects as go  
> import [plotly.io](http://plotly.io) as pio  
> from plotly.subplots import make\_subplots  
> pio.renderers.default = “browser”  
> training\_data = pd.read\_csv(“numerai\_training\_data.csv”)  
> tournament\_data = pd.read\_csv(“numerai\_tournament\_data.csv”)

> df = pd.concat([training\_data, tournament\_data],ignore\_index=True)

> df[‘era\_value’] = df[‘era’].str[3:]  
> df.loc[df[‘era’] == ‘eraX’, ‘era’] = ‘era0’  
> df[‘era\_value’] = df[‘era’].str[3:].astype(int)  
> max\_era = df[‘era\_value’].max()  
> print(max\_era)  
> df.loc[df[‘era\_value’] == 0, ‘era\_value’] = max\_era + 1

> fig = px.scatter(df, x=“era\_value”, y=“data\_type”, color=“data\_type”,  
> title=“Interesting era distribution”)  
> fig.show()

 ![newplot](https://canada1.discourse-cdn.com/flex009/uploads/numerai/original/2X/1/11a22c19fc9c35315311f5390a4582dbb7d4f8f8.png)

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**Author:** ![andy\_shaps](https://avatars.discourse-cdn.com/v4/letter/a/bcef8e/32.png) [@andy\_shaps](https://forum.numer.ai/u/andy_shaps)\
**Post date:** [July 30, 2021, 10:22am UTC](https://forum.numer.ai/t/era-distribution/3875/2 "2021-07-30T10:22:26Z")

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Not all eras are in months. the live, test and val2 eras are done in weeks. this results in more eras in them than would be expected. below is how the data is currently formatted. In the latest fireside chat they have said this will change soon though. They are planning to give us the target values for all train, val and test eras in a weekly format (if i understood correctly). hope this helps

 ![image](https://canada1.discourse-cdn.com/flex009/uploads/numerai/original/2X/d/da34bc8250b52db5f4f6adff4a569f4fba2887a3.png)

edit: ignore the current/proposed titles. this post was from a long time ago so only the “proposed” image is relevant today (but as i said, will probably change soon)