Portfolio

  Task :  Performing  Exploratory Data Analysis on a Retail  Company's  'Sample Superstore' dataset. The tool used is  Tableau . Creating  different visualizations to  analyze  the dataset, its trends and statistics and  further   creating  Dashboard to showcase and compare the sales and profit depending on various different aspects. Using this insights from the data,  creating  a  Storyboard  to showcase the areas for improvement in  order  to increase  the   company's  Sales and Profit. Tableau Workbook Link :  The tableau workbook is uploaded on Tableau Public and below is the link to view the same. https://public.tableau.com/app/profile/mohit.pundir/viz/SuperStore_16313465526460/Dashboard1 Tableau Dashboard/Storyboard Image :  Dashboard - Storyboard Video : Sharing a glimpse of my dashboard / storyboard through a small video to showcase some of the insights drawn from a...

OUERY 1 - FINDING TOP TRAFFIC SOURCES SELECT utm_source, utm_campaign, http_referer,  COUNT(website_session_id) AS count_of_sessions FROM website_sessions WHERE created_at < '2012-04-12' GROUP BY 1,2,3 ORDER BY 4 DESC; OUTPUT -  QUERY 2 -TRAFFIC SOURCE CONVERSION RATES SELECT COUNT( DISTINCT website_sessions.website_session_id) AS sessions, COUNT(DISTINCT orders.order_id) AS orders, COUNT(DISTINCT orders.order_id)/COUNT( DISTINCT website_sessions.website_session_id)  AS sess_2_ordr_cnvt FROM website_sessions LEFT JOIN orders ON orders.website_session_id = website_sessions.website_session_id WHERE website_sessions.created_at < '2012-04-14' AND website_sessions.utm_source = 'gsearch' AND website_sessions.utm_campaign = 'nonbrand'; OUTPUT-  OUERY 3 - TRAFFIC SOURCE TRENDING SELECT MIN( DATE(created_at)) AS week_start_date, COUNT(website_session_id) AS sessions FROM website_sessions WHERE created_at < '2012-05-10' AND utm_source = 'gsear...

temp-162419151367394675 In [133]: import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt % matplotlib inline In [134]: matches = pd . read_csv ( "matches.csv" ) matches . drop ( axis = 1 , columns = [ "dl_applied" , "umpire1" , "umpire2" , "umpire3" ], inplace = True ) matches . head () Out[134]: id season city date team1 team2 toss_winner toss_decision result winner win_by_runs win_by_wickets player_of_match venue 0 1 2017 Hyderabad 2017-04-05 Sunrisers Hyderabad Royal Challengers Bangalore Royal Challengers Bangalore field normal Sunrisers Hyder...