Python for R Users
This course is for R users who want to get up to speed with Python!
Comience El Curso Gratis5 Horas15 Videos57 Ejercicios
Crea Tu Cuenta Gratuita
o
Al continuar, acepta nuestros Términos de uso, nuestra Política de privacidad y que sus datos se almacenan en los EE. UU.¿Entrenar a 2 o más personas?Pruebe DataCamp para empresas
Preferido por estudiantes en miles de empresas
Descripción del curso
Python and R have seen immense growth in popularity in the "Machine Learning Age". They both are high-level languages that are easy to learn and write. The language you use will depend on your background and field of study and work. R is a language made by and for statisticians, whereas Python is a more general purpose programming language. Regardless of the background, there will be times when a particular algorithm is implemented in one language and not the other, a feature is better documented, or simply, the tutorial you found online uses Python instead of R.
In either case, this would require the R user to work in Python to get his/her work done, or try to understand how something is implemented in Python for it to be translated into R. This course helps you cross the R-Python language barrier.
Empresas
¿Entrenar a 2 o más personas?
Obtenga acceso de su equipo a la biblioteca completa de DataCamp, con informes centralizados, tareas, proyectos y más- 1
The Basics
GratuitoLearn about some of the most important data types (integers, floats, strings, and booleans) and data structures (lists, dictionaries, numpy arrays, and pandas DataFrames) in Python and how they compare to the ones in R.
- 2
Control flow, Loops, and Functions
This chapter covers control flow statements (if-else if-else), for loops and shows you how to write your own functions in Python!
- 3
Pandas
In this chapter you will learn more about one of the most important Python libraries, Pandas. In addition to DataFrames, pandas provides several data manipulation functions and methods.
- 4
Plotting
You will learn about the rich ecosystem of visualization libraries in Python. This chapter covers matplotlib, the core visualization library in Python along with the pandas and seaborn libraries.
Plotting directly using pandas50 xpUnivariate plots in pandas100 xpBivariate plots in pandas100 xpSeaborn50 xpUnivariate plots in seaborn100 xpBivariate plots in seaborn100 xpFacet plots in seaborn100 xpMatplotlib50 xpUnivariate and bivariate plots in matplotlib100 xpSubfigures in matplotlib100 xpWorking with axes100 xpPolishing up a figure100 xp - 5
Capstone
As a final capstone, you will apply your Python skills on the NYC Flights 2013 dataset.
Empresas
¿Entrenar a 2 o más personas?
Obtenga acceso de su equipo a la biblioteca completa de DataCamp, con informes centralizados, tareas, proyectos y másColaboradores
Requisitos Previos
Introduction to Writing Functions in RDaniel Chen
Ver Mas
Data Science Consultant at Lander Analytics
¿Qué tienen que decir otros alumnos?
Únete a 13 millones de estudiantes y empeza Python for R Users hoy!
Crea Tu Cuenta Gratuita
o
Al continuar, acepta nuestros Términos de uso, nuestra Política de privacidad y que sus datos se almacenan en los EE. UU.