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Pandas in Python - Dataframe Tutorial(With examples)

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Creating Data Frames In the previous post we looked the tutorial on basic of Series in Pandas.In this part of tutorial we will be looking building one of the important data structure in pandas "The DataFrame" .Pandas has an abundance of functionality, far too much for me to cover in this introduction.We will cover more functions of dataframe in the example sections which will be coming in next post!
Hope you are enjoying by learning, our Suggestion would be to practice by writing and calling the functions and understanding it.


Lets get Started! DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it
like a spreadsheet or SQL table, or a dict of Series objects.
The Important
You can create a data frame using:
Dict of 1D ndarrays, lists, dicts, or Series2-D numpy.ndarrayStructured or record ndarrayA SeriesAnother DataFrame
Data Frame attributes
Importing numpy and pandas librabry In [61]: importpandasaspdimportnum…

Pandas in Python for Data Analysis with Example(Step-by-Step guide)

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Beginners Pandas Getting Started Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables.
If you're new to this first get the enviroment Setup in our previous postGetting Started with Jupyter [Part -1] http://www.androidxu.com/2017/04/guide-On-Jupyter-Notebook.htmlGetting Started with Jupyter [Part -2] http://www.androidxu.com/2017/04/the-ultimate-guide-on-jupyter-ipython-mardown.html#.WPJOBYVOL4g


pandas is well suited for:
Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheetOrdered and unordered (not necessarily fixed-frequency) time series data.Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labelsAny other form of observational / statistical data sets. The data actually need not be labeled at all to be pl…

The Ultimate guide On Jupyter Notebook[Part-2]-The Markdown

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What is Markdown ? Markdown is a way to style text on the web. You control the display of the document; formatting words as bold or italic, adding images, and creating lists are just a few of the things we can do with Markdown. Mostly, Markdown is just regular text with a few non-alphabetic characters thrown in, like # or *.
Markdown is a text-to-HTML conversion tool for web writers. Markdown allows you to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML).
Thus, “Markdown” is two things: (1) a plain text formatting syntax; and (2) a software tool, written in Perl, that converts the plain text formatting to HTML. See the Syntax page for details pertaining to Markdown’s formatting syntax. You can try it out, right now, using the online Dingus.
The overriding design goal for Markdown’s formatting syntax is to make it as readable as possible. The idea is that a Markdown-formatted document should be publishable as-is, as p…