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#dataanalysis

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Public
Miki :rstats:

#30DayChartChallenge Día 12: Gov Data Day! 🏛️ Explorando la distribución del spread 10Y-2Y del Tesoro USA (datos de FRED desde 1976).

Este histograma/densidad va más allá del valor diario: muestra la *probabilidad* histórica de cada nivel del spread. ¡Clave para entender expectativas económicas!

Puntos clave:
* Modo principal > 0 (curva normal es lo más común).
* ¡La inversión (<0, línea discontinua) tiene una probabilidad no trivial! ⚠️ Es la famosa señal pre-recesión. La distribución nos dice cuán "normal" es esa señal en perspectiva histórica.
* La forma general revela info sobre la dinámica de tipos.

Una visualización sobre la estructura probabilística de un indicador líder fundamental.

🛠️ #rstats #ggplot2 #quantmod #grid
📂 Código/Repo: t.ly/0RDmK

Histograma superpuesto con una curva de densidad mostrando la distribución del diferencial diario entre los tipos de interés del Tesoro de EE.UU. a 10 años y 2 años, desde 1976 hasta 2025. El eje X muestra el diferencial en puntos porcentuales, el eje Y muestra la densidad. Las barras del histograma tienen un relleno con degradado vertical azul verdoso. La curva de densidad es de color rosa. Una línea vertical discontinua en x=0 indica la inversión de la curva de tipos, con una etiqueta de texto vertical asociada. El pico principal de la distribución se sitúa alrededor de +1%, con una cola izquierda que se extiende por debajo de cero. Fuente: FRED/U.S. Treasury.
#Day12#Distributions#datagov
Public
Nael Shiab

If you work with code and data, there’s one exhilarating rite of passage: cracking open your first one billion rows CSV! 😱

In my latest tutorial, I take on the One Billion Row Challenge using the Simple Data Analysis library.

Ready to make your computer fan go VRRRRRR? Check out the link below! 👇

#DataScience#DataAnalysis#DataViz
Public
Indy Navarro
I have more faith in this place than Linkedln, so let's try it out!

Dear people in the Fediverse I am searching for my next job these days, and I want to find a meaningful position.

About me:

1. Bachelor in engineering science and Master in Industrial Engineering
2. 4 Years working mainly in data analysis/data science rolls for the energy, food manufacturing industry as
non-profit organizations.
3. Experience with dashboard building, data visualization, statistical analysis, machine learning and operation research problems
4. Experience using tools like Python, Julia, R, SQL, Linux, Qlikview and MS office.
5. Native in Spanish, Fluent in English and conversational in Japanese.

What I am looking for:
- Full time IT position (data related highly preferred)
- A remote job (but if it's based in Tokyo can be hybrid)
- A company that has a positive impact in the world

Boost or sharing is highly appreciated

#GetFediHired #LFW #LookingForWork #DataScience #Data #dataanalysis
#dataanalysis
Public
Marcia MacDonald

Know any providers who might host @grist on servers outside the US?

We're a grassroots org starting to use Grist, hoping to collaborate securely to analyze sensitive data in real-time, with more #database and #DataAnalysis functionality than @cryptpad and less surveillance than #Google sheets.

We don't have the tech capacity to self-host, so we could be looking for something like @facil, resist.ca, or nogodsnomasters.org to host for us. Ideas?

#OpenSource #Excel #spreadsheets @JordiGH

Public
Sarah Lea

Everyone knows ggplot2 in R or matplotlib in Python. But what are the differences between theese 2 programming languages and what are the most important R & Python libraries for visualization?

towardsdatascience.com/the-ess

Towards Data Science · The Essential Guide to R and Python Libraries for Data VisualizationBy Sarah Lea
#data#datascience#dataviz
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