Raphael-Blaize/python-project-for-MTN-Cote-d-Ivoire--to-help-in-upgrade-of-its-infrastructure-strategy

Cleaning and Analyzing datasets provided by MTN Cote d'Ivoire # MTN Cote d'Ivoire Analysing and Cleaning of Datasets to provide insights Python Project for MTN Cote d'Ivoire. Cleaning and Analyzing the datasets in-order to provide insights to technology imporvements #### -- Project Status: [Completed] ## Project Intro/Objective The purpose of this project is to help MTN Cote d'Ivoire figure out ways to go about upgrading its infrastructure within the given cities, MTN Cote d'Ivoire would like to upgrade it's technology to the mobile user's across Ivory Coast ### Partner * [Moringa School] * moringaschool.com ### Methods Used * Descriptive Statistics * Data Visualistaion Techniques * Data Analysis ### Technologies * Python * Pandas,Numpy,Gooogle Colab * Tableau ```python import pandas as pd # python library that import datasets into a working env and does so much more such as helping in cleaning datasets etc import numpy as np # offers comprehensive mathematical functions etc ``` ## Data Used * Data Soruces used * cells_geo_description.xlsx Link * cells_geo.csv [Link] (drive.google.com) * CDR_description.xlsx [Link] (drive.google.com) * CDR 20120507 [bit.ly] * CDR 20120508 [bit.ly] * CDR 20120509 [bit.ly] * Exported Dataset used for visulisation in Tableau * MTNfinal.csv [Link] (drive.google.com) * Data Analysis used * Frequency in cities and Values * Grouping by columns to find maxmimum and minimum of columns * Descriptive statistics to understand more about the measures of spread and to understand the Quartile ranges * Mean of the Values column and how it is spread * Descriptive statistics of the Product value measured against the Cities * Questions to be able to solve the challenge * 1. Which Citites had the highest billing * 2. The city with the most cells * 3. Which …