Welcome to Datanovia, your all-in-one destination to master data science, machine learning, deep learning, data visualization, statistical analysis, and tools like Git, Docker, and VSCode. Learn Python and R programming with tutorials, eBooks, and interactive projects for all levels.
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Learn and apply Python in data science with our interactive tutorials. From basic programming to advanced machine learning, we provide a comprehensive path to mastering Python in data science.
Embrace the power of R in data science with our structured courses. Learn to analyze, visualize, and model data effectively using R, with practical projects to solidify your skills.
---
title: "ggplot2 demo"
author: "Norah Jones"
date: "5/22/2021"
format:
html:
fig-width: 8
fig-height: 4
code-fold: true
---
## Air Quality
@fig-airquality further explores the impact of temperature on ozone level.
```{r}
#| label: fig-airquality
#| fig-cap: "Temperature and ozone level."
#| warning: false
library(ggplot2)
ggplot(airquality, aes(Temp, Ozone)) +
geom_point() +
geom_smooth(method = "loess")
```
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Unlock the power of Python for data analysis. Learn how to manipulate and analyze data using pandas, visualize data with Matplotlib, and apply statistical techniques with SciPy.
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Master fundamental machine learning concepts using Python and R. From linear regression to neural networks, start your journey in predictive modeling and AI.
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Datanovia website is really incredible. They understand the tools relevant to modern advanced scientific analysis—but teach it at the level of someone trying to build these skills from scratch. Incredible attention to detail.
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Zahra H FranceI have never used any machine learning things before, so Datanovia was extremely useful in introducing the basics of working with clustering in R! What a nice and "down to earth" way of explaining such complex things! Thank you again!
Kate USAMy field is functional genomics, and i have found this site just recently. This is an absolutely terrific resource for cluster analysis using R. Great way to get some insights into ggplot2 too. Thank you very much!
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