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Pandas in Python Library that is used for Data Manipulation and Analysis. It came from terms “Panel Data”. It’s open source under three-clause BSD License. Original developer was Wes McKinney in 2008 while he worked at AQR Capital Management to process Quantitative Analysis on financial data. It was written in Python, Cython and C.

Pandas in mainly used for Machine Learning.

There a lot of features available that you can used for:
-reading and writing various data format, csv, MS excel, json, html, SAS, SPSS, SQL, Google Big Query, Stata, Msgpack etc.
-Group, Join, Merge, Filter, Pivot, Reshaping data set.
-Time series function and so many more.

Installation
In this tutorial I use Python 3.6.9 (default, Nov 7 2019, 10:44:02), so the installation command will be: pip3 install pandas.
From Linux terminal type:

$ pip3 install pandas
Collecting pandas
  Downloading https://files.pythonhosted.org/packages/bb/71/8f53bdbcbc67c912b888b40def255767e475402e9df64050019149b1a943/pandas-1.0.3-cp36-cp36m-manylinux1_x86_64.whl (10.0MB)
    100% |████████████████████████████████| 10.0MB 48kB/s 
Collecting python-dateutil>=2.6.1 (from pandas)
  Using cached https://files.pythonhosted.org/packages/d4/70/d60450c3dd48ef87586924207ae8907090de0b306af2bce5d134d78615cb/python_dateutil-2.8.1-py2.py3-none-any.whl
Collecting numpy>=1.13.3 (from pandas)
  Downloading https://files.pythonhosted.org/packages/07/08/a549ba8b061005bb629b76adc000f3caaaf881028b963c2e18f811c6edc1/numpy-1.18.2-cp36-cp36m-manylinux1_x86_64.whl (20.2MB)
    100% |████████████████████████████████| 20.2MB 45kB/s 
Collecting pytz>=2017.2 (from pandas)
  Using cached https://files.pythonhosted.org/packages/e7/f9/f0b53f88060247251bf481fa6ea62cd0d25bf1b11a87888e53ce5b7c8ad2/pytz-2019.3-py2.py3-none-any.whl
Collecting six>=1.5 (from python-dateutil>=2.6.1->pandas)
  Using cached https://files.pythonhosted.org/packages/65/eb/1f97cb97bfc2390a276969c6fae16075da282f5058082d4cb10c6c5c1dba/six-1.14.0-py2.py3-none-any.whl
Installing collected packages: six, python-dateutil, numpy, pytz, pandas
Successfully installed numpy-1.18.2 pandas-1.0.3 python-dateutil-2.8.1 pytz-2019.3 six-1.14.0
$

pandas01
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