@@ -9,7 +9,7 @@ Python is frequently used for high-performance scientific applications. Python
99is widely used in academia and scientific projects because it is easy to write,
1010and it performs really well.
1111
12- Due to its high performance nature, scientific computing in python often refers
12+ Due to its high performance nature, scientific computing in Python often refers
1313to external libraries, typically written in faster languages (like C, or
1414FORTRAN for matrix operations). The main libraries used are `NumPy `_, `SciPy `_
1515and `Matplotlib `_. Going into detail about these libraries is beyond the scope
@@ -24,11 +24,11 @@ Tools
2424IPython
2525-------
2626
27- `IPytthon <http://ipython.org/ >`_ is an enhanced version of Python interpreter.
27+ `IPython <http://ipython.org/ >`_ is an enhanced version of Python interpreter.
2828The features it provides are of great interest for the scientists. The `inline mode `
2929allow graphics and plots to be displayed in the terminal (Qt based version).
3030Moreover the `notebook ` mode supports literate programming and reproducible science
31- generating a web-based python notebook. This notebook allowing to store chunk of
31+ generating a web-based Python notebook. This notebook allowing to store chunk of
3232Python code along side to the results and additional comments (HTML, LaTeX, Markdown).
3333The notebook could be shared and exported in various file formats.
3434
6464
6565`SciPy <http://scipy.org/ >`_ is a library that uses Numpy for more mathematical
6666functions. SciPy uses NumPy arrays as the basic data structure. SciPy comes
67- with modules for various commonly used tasks in scientific programing , for
67+ with modules for various commonly used tasks in scientific programming , for
6868example: linear algebra, integration (calculus), ordinary differential equation
6969solvers and signal processing.
7070
@@ -86,7 +86,7 @@ based on Numpy and which provides many useful functions for accessing,
8686indexing, merging and grouping data easily. The main data structure (DataFrame)
8787is close to what could be found in the R statistical package, that is
8888an heterogeneous data tables with name indexing, time series operations
89- and auto-alignement of data.
89+ and auto-alignment of data.
9090
9191Rpy2
9292----
@@ -120,7 +120,7 @@ Many people who do scientific computing are on Windows. And yet many of the
120120scientific computing packages are notoriously difficult to build and install.
121121`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/pythonlibs/ >`_ however, has
122122compiled a list of Windows binaries for many useful Python packages. The list
123- of packages has grown from a mainly scientific python resource to a more
123+ of packages has grown from a mainly scientific Python resource to a more
124124general list. It might be a good idea to check it out if you're on Windows.
125125
126126Enthought Python Distribution (EPD)
0 commit comments