.. currentmodule:: pandas
Since pandas aims to provide a lot of the data manipulation and analysis
functionality that people use R for, this page
was started to provide a more detailed look at the R language and its many third
party libraries as they relate to pandas. In comparisons with R and CRAN
libraries, we care about the following things:
- Functionality / flexibility: what can/cannot be done with each tool
- Performance: how fast are operations. Hard numbers/benchmarks are preferable
- Ease-of-use: Is one tool easier/harder to use (you may have to be the judge of this, given side-by-side code comparisons)
This page is also here to offer a bit of a translation guide for users of these R packages.
.. versionadded:: 0.13
The :meth:`~pandas.DataFrame.query` method is similar to the base R subset
function. In R you might want to get the rows of a data.frame where one
column's values are less than another column's values:
df <- data.frame(a=rnorm(10), b=rnorm(10)) subset(df, a <= b) df[df$a <= df$b,] # note the comma
In pandas, there are a few ways to perform subsetting. You can use
:meth:`~pandas.DataFrame.query` or pass an expression as if it were an
index/slice as well as standard boolean indexing:
.. ipython:: python
from pandas import DataFrame
from numpy.random import randn
df = DataFrame({'a': randn(10), 'b': randn(10)})
df.query('a <= b')
df[df.a <= df.b]
df.loc[df.a <= df.b]
For more details and examples see :ref:`the query documentation <indexing.query>`.
.. versionadded:: 0.13
An expression using a data.frame called df in R with the columns a and
b would be evaluated using with like so:
df <- data.frame(a=rnorm(10), b=rnorm(10)) with(df, a + b) df$a + df$b # same as the previous expression
In pandas the equivalent expression, using the
:meth:`~pandas.DataFrame.eval` method, would be:
.. ipython:: python
df = DataFrame({'a': randn(10), 'b': randn(10)})
df.eval('a + b')
df.a + df.b # same as the previous expression
In certain cases :meth:`~pandas.DataFrame.eval` will be much faster than evaluation in pure Python. For more details and examples see :ref:`the eval documentation <enhancingperf.eval>`.