SARAH AKINKUNMI

Still ongoing

Restaurants and Hotels Sentiment Analyzer

A joint project with my team members from Team Kapwepwe, Cohort 8 AI Saturdays, to analyse customer reviews of restaurants and hotels for their sentiments. This would empower Nigerians in making better informed choices and help restaurants and hotels improve their services by leveraging guest feedback.

Tools used: Python, vaderSentimentAnalysis package, Streamlit, Microsoft Excel

March 03, 2023

Airline On-Time Performance Data

a Northwest Airline plane taking off

The data, found here reports flights in the United States, including carriers, arrival and departure delays, and reasons for delays, from 1987 to 2008. However, due to the large volume of data in each year, I chose just the 2008 data.

After some preliminary wrangling, I used the Univariate, Bivariate, Multivariate exploration steps to explore my features of interest. Then I summarized my findings to present visualizations containing the answers to the following questions:

  • How are delay times distributed? Are many flights were delayed or not?
  • What is the major cause of delay?
  • Were the flights over more longer distances than short distances?
  • What are the top destinations and origins for the flights?
  • Does distance affect delay times?
  • Do some airlines experience more delays than others?
  • What is the relationship between delay times and the causes of delay?
  • How do the delay times and NAS delay vary with the most common destinations in each month?

Tools used: Python (pandas, numpy, matplotlib, seaborn)

January 14, 2023

WeRateDogs Twitter Analysis

A juxtaposition of several images taken from the WeRateDogs Twitter account

A data wrangling project carried out on the WeRateDogs Twitter account. The data was gotten from 3 different sources, downloaded in 3 ways - manually, programmatically and through Twitter API request.
Tools used: Python (pandas, numpy, matplotlib, seaborn, requests, tweepy)

December 19, 2022

TMDB Movie Analysis

Here, I cleaned and analyzed over 10,000 rows of movie data from 1960-2015 sourced from TMDB and pre-cleaned by Udacity to gain insights about the average movie runtime trend, the most popular genres over the years, the most popular production companies over the years and the factors that most likely influence the revenue generated.
Tools used: Python(pandas, numpy, matplotlib)

November 19, 2022

How Can a Wellness Company Play it Smart?

Women in a yoga class. There’s a black woman standing, three women in the Vajrasana pose in the background on pink mats and two women stretching at the back. Picture by Bruce Mars on Unsplash.

My Capstone Project for the Google Data Analytics Professional Certificate. I analyzed smart device usage data to discover trends in consumer usage and unlock growth opportunities for Bellabeat - a wellness company catering to women.
Tools used: Microsoft Excel, Microsoft Power BI

September 24, 2022

LinkedIn Connections Analysis

LinkedIn's logo

Exploratory analysis on my LinkedIn connections data. I was able to determine the total number of connections I have, connections I have made over time, unique professions and the number of connections in them and the unique companies and the number of connections in them.
Tools used: Google Sheets, Microsoft Power BI