CentOs Python Pandas ideas to install quickly

Install pandas on CentOs. Pandas is a Python Library where you can manipulate or filter your data. When I tried yum install pandas not worked. Then I followed below idea or method to install pandas quickly

Pandas big use case is in data analytics to take decisions. Normally you will get error while installing Pandas with yum install in Centos. I arched google but I did not get correct method or idea. Below is the correct procedure and ideas or tips to install ‘pandas’ on CentOs.

How to install quickly…

An introduction…what is pandas..

pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

pandas is a NumFOCUS sponsored project. This will help ensure the success of development of pandas as a world-class open-source project, and makes it possible to donate to the project.

Pandas Python

Pandas is a library on Python for data analysis. CentOs is Linux flavor where you can install by following procedure as given below:
Step:1 Login into CentOs

CentOs login
Step:2 Identity where your Python Pandas package is located on the web.

Do google search as below…

Pandas website

You will get information on which Pandas package is suitable for your CentOs. Here, I have used CentOs 7, so the link is:
epel link: http://dl.fedoraproject.org/pub/epel/7/x86_64/
Step:3 Then in CentOS, issue ‘su’ command.

$su   .....>enter

Give Password

Step:4 Afterwords you logged into ‘Super user’ directory.

[root@localhost srini]#

Step:5 You need to issue ‘dhclient’ command.

Dhclient
Step:6 Then you need to install epel package by giving the below command

[root@localhost srini]# rpm -Uvh 
http://dl.fedoraproject.org/pub/epel/Packages/e/7/x86_64/epel-release*rpm

Note: Whatever is latest package, you can install that package. The ‘*’ means any latest package.

Import pandas in Python a video

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Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.