Concise notes¶

Data Structures

Python provides a variety of useful data structures, such as lists, sets, and dictionaries, and a new structure define by programmer which called class.

How to save all objects

import dill
# to save session
dill.dump_session('backup_2021_10_22.db')
# to load 
backup_restore = dill.load_session('backup_2021_10_22.db')

Generating frequency

Here we demonstrate how generate frequency table from the data.

Function

In the context of programming, a function is a sequence of statements that performs a computation. Functions has three parts; argument, script, and output. Python has two kinds of function: built-in function that is in the core of Python or are collected as package. User-defined function that is written by user.

Iteration

Python is equipped with strong tools for the repeat of some commands or produce sequence number.

Manipulating data-frame

To select the data use the name of variable, or specify the indices via .iloc and .loc (link)[http://pandas.pydata.org/pandas-docs/version/0.22/indexing.html]. .iloc is an integer-based select and should be used with integer indies. On contrary, .loc is primarily label based, and may also be used with a boolean array.

Merging data-frames

Panada is very useful for merging dataset; to merging data consider the following data sets, where 'id1' and 'id2' include the ids of data.

How find most most unique item

If you need to count of each unique item from an object, use module collections module, the following code return the 3 most common items from the given object:

from collections import Counter
c = Counter(l)
c.most_common(3)

Adding new column to data-frame

A column can easily be added to data-frame

Pipeline

Pipeline in Pandas allows to build a sequence of function to run in order on data-frame.