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1.IntroductionOfPandas.py
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1.IntroductionOfPandas.py
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##--------------------------------
##Created By:Ravishankar Chavare
##version:python 3.7
##Date:24/12/18
##File_des:Introduction of Pandas
##--------------------------------
##Pandas:-
##**********************************************************************************************************************************
# ----About----
##**********************************************************************************************************************************
'''
-pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or
“labeled” data both easy and intuitive.
It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python
-pandas is a software library written for the Python programming language for data manipulation and analysis.
In particular, it offers data structures and operations for manipulating numerical tables and time series.
-Tools for reading and writing data between in-memory data structures and different formats: CSV and text files,
Microsoft Excel, SQL databases, and the fast HDF5 format;
'''
##**********************************************************************************************************************************
# ----Why Pandas---
##**********************************************************************************************************************************
'''
-Pandas is arguably the most important Python package for data science
-pandas is an opensource
-Its can work with data from different type of data sources like,csv,excel,dat,text and much more
-It gives productivity and performance according to others
-It allows fast analasys and data cleaning preparation
-Some Builtin Visualization Features
-High performance merging and joining of data sets;
-optimized for performance
'''
##**********************************************************************************************************************************
# ---Benifits of using pandas---
##**********************************************************************************************************************************
'''
-Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data
-Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects
-Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or
the user can simply ignore the labels and let Series, DataFrame, etc. automatically align the data for you in computations
-Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data
-Make it easy to convert ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects
'''
##******************************************************************************************************************************##
# --Operation on pandas--
##******************************************************************************************************************************##
'''
1.Data Slicing
2.Changing the index
3.Data Conversion
4.Concatnation
5.Joining And Merging
6.Changing The Columns Headers
7.And More
'''
##**********************************************************************************************************************************
# ----Insallation and Setup----
##**********************************************************************************************************************************
'''
You can simply install pandas using command line on terminal
in windows just open your command prompt and type:
pip install pandas
press enter key and wait unitll pandas to be install on your machine
For Upgrading pandas using pip
python3 -m pip install --upgrade pandas
'''
##**********************************************************************************************************************************
# ---Import Use in Pandas---
##**********************************************************************************************************************************
'''
import pandas as pd
import numpy as np
'''
import pandas as pd
import numpy as np