I participated in a programming event for the first time on August 23, and another person told me that output is important, so I will write it here.
A summary of libraries that are useful mainly around ipython and when operating operations research.
A discipline that solves problems using mathematics.
The library used this time is as follows.
Library | function |
---|---|
pandas | Mainly pre-processing such as cross tabulation. A child who can be unexpected |
matplotlib | Graph drawing library. It can be pretty clean. |
scikit-learn | Machine learning library. Most of the methods are included. |
pulp | Optimization calculation library. This is for light optimization. |
simpy | Library for simulation. Queue model, etc. |
networkX | Graph drawing library. This is the graph theory. |
sympy | Symbol calculation library. It solves the character expression as it is. |
I also dealt with a library for AWS called boto
, but this time I will omit it.
IPython is like a normal Interactive Shell, A very convenient guy who can set up a server and program from a browser (notebook).
For installation etc., I think that you should refer to other sites.
At the seminar, I used the command ʻipython notebook --pylab inline, but it seems that something is not good. ʻIpython notebook --matplotlib inline
seems to be a good idea.
By the way, it seems that it can be done even after executing with % matplotlib (inline)
.
ʻInline` selects whether to draw a graph or figure in the browser or in a separate window.
Press the Tab
key to complete it.
Add ?
to an object or function to get information.
You can see the source code by adding ??
.
>>> %pylab
>>> prob?
Type: function
String form: <function prod at 0x10bfeb398>
File: /usr/local/lib/python2.7/site-packages/numpy/core/fromnumeric.py
Definition: prod(a, axis=None, dtype=None, out=None, keepdims=False)
Docstring:
Return the product of array elements over a given axis.
Parameters
----------
a : array_like
Input data.
axis : None or int or tuple of ints, optional...
>>> prob??
Type: function
String form: <function prod at 0x10bfeb398>
File: /usr/local/lib/python2.7/site-packages/numpy/core/fromnumeric.py
Definition: prod(a, axis=None, dtype=None, out=None, keepdims=False)
Source:
def prod(a, axis=None, dtype=None, out=None, keepdims=False):
"""
Return the product of array elements over a given axis.
Parameters
----------
a : array_like...
Basically, you can do anything by prefixing the shell command with !
.
As you know, you can use cd
, ls
, mv
, cp
, rm
, less
, and cat
as they are. vim must be ! vim
.
Some useful ones.
% time
: Measure the time once.
% timeit
: Measure the average time multiple times. (Is it better to use this one)
% run python_file
: Execute python_file. (! Python
is also acceptable)
% paste
: Paste (only when running terminal)
Other than those listed here, you should refer to Cheat Sheets.
scikit-learn
pulp in preparation....
simpy in preparation....
networkX in preparation....
sympy in preparation....
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