My first Notebook on Data with Python

I will be exploring pandas, since it's the one I have been recommended for quite some time now. I am choosing this over R mainly because I do not require the data visualization part that it gives you. I intend to do the data visualization part later with D3.js. In any case, this will document my experiences learning Python.

I also found this amazing resource

Pandas cookbook

##API reference that concerns me Pandas API ###JSON

read_json([path_or_buf, orient, typ, dtype, ...]) #Convert a JSON string to pandas object
json_normalize(data[, record_path, meta, ...])  #“Normalize” semi-structured JSON data into a flat table

###HTML

read_html(io[, match, flavor, header, ...]) #Read HTML tables into a list of DataFrame objects.

###STATA

read_stata(filepath_or_buffer[, ...]) #Read Stata file into DataFrame
StataReader.data(**kwargs) #DEPRECATED: Reads observations from Stata file, converting them into a dataframe
StataReader.data_label()  # Returns data label of Stata file
StataReader.value_labels() # Returns a dict, associating each variable name a dict, associating
StataReader.variable_labels() # Returns variable labels as a dict, associating each variable name
StataWriter.write_file()

Installing Relevant Software

For Officially Python 2.7, 3.4, and 3.5, for some reason everyone warns against using Python 3, Do not use Python 3!

###Guide of this Repo:

Notes and miscellaneous

Section	Description
Introduction to Python	Cheat sheet of Python commands and short descriptions.
Introduction to Pandas	Basic Pandas and Data Structures.

Current Analysis

Section	Description
Exploratory Analysis for Taxis	Cheat sheet of Python commands and short descriptions.
Introduction to Pandas	Basic Pandas and Data Structures.