An NLP analysis on 2015 New Year’s Eve Resolution tweets downloaded from Maven Analytics Digital Playground

Image gotten from google photos search

Social media has become such an important platform and tool nowadays. Individuals and businesses leverage social media platforms such as Twitter and Instagram for various purposes. Businesses leverage social media in advertising their services and products, getting feedbacks or reviews regarding their services as well as a range of other things such as getting insights about peak periods of sales, customer segmentation and so on.

It has become sort of a norm for individuals to set goals, plans, resolutions regarding things they want to…


It’s the weekend people!! All I can think of right now is how I can’t wait to unwind with a really good bottle of wine and a good series, preferably Korean. Talking of wines, this post focuses on using machine learning to predict the quality of a sample wine data. Sounds interesting right? Let’s get right into it!

Here’s a link to my github page analyzing this data https://github.com/Sofuwa/She-Code-Africa/blob/main/White_Wine_Quality.ipynb

Below are the steps I used in analyzing and predicting my dataset. I’ll be giving a brief explanation of what I did under each step.

  1. Import Libraries
  2. Data Preprocessing
  3. Exploring and…

I came across a class placement dataset recently on Kaggle. I wanted to carry out EDA analysis on the data and also practice my skills in machine learning. The dataset looks at the placement rate if students based on multiple criteria such as gender, degree taken in the university, if such students have an MBA with a specialization etc. For the context of my visualization in tableau, I examined several questions, some of which you can find below as well as the insights I was able to derive from the data.

a) What is the proportion of the placement rate?


I recently started my three months mentorship program with She Code Africa (Cohort 3) and it has been great so far. I took up an interest in data science and analytics some months ago and while I have been trying my hands on working with datasets from Kaggle, it’s important for me go back the basics once in a while. Another reason I’m glad to participate in this program is because I have an opportunity to be mentored.

In this post, I’ll give you a brief insight to tasks I did, new things I learnt and the likes.

WEEK 1


Leveraging data with data science and analytics is becoming more important across industries. We live in a world of technology and with growing developments in the technology, data generated by individuals and corporations keep increasing.

How then does probability affect data science and analytics?

Probability just has to do with the likelihood of an event occurring or not occurring. In the world we live in, we apply probability in our daily lives without even realizing it. Nothing is 100% certain. There is always some form of uncertainty. …


I started my journey into data science and analytics probably at the beginning of 2019. I took a 6 months online course in data analytics where I learnt the basics of SQL, Tableau and Python to analyze and visualize data. After the course was done, I was really looking forward to getting a job and applying the skills I had learnt in real world situations. However, it’s not so easy to do that in the real world. I did get some opportunities but I never made it past the second to the final recruitment stage or even the final recruitment…


An analysis of the FIFA World Cup

What is football to you?

Pelé, regarded by many as the greatest player of all time describes football as “a beautiful game”.

I do not watch football regularly but I do follow the FIFA World Cup. I would describe football as a game of emotions, friends and family. There are always various emotions that people experience when watching football which include but are not limited to happiness, anger, sadness, tension.

The FIFA World Cup was founded in 1930 and has been held every four years ever since with the exception of the 1942 and 1946 World Cup which were cancelled…


SQL: The Hackerrank Challenge

Hello everyone!!!

New Month, New Challenges!! The project for this month from the GitGirl School of Data that I attend is putting our knowledge about SQL to practice through the HackerRank SQL challenge. Before I go on to discussing the challenge, we had to study some advanced syntax and functions in SQL. These include but are not limited to case when, advanced queries such as correlated and nested sub-queries, window functions and so on. Now, in order to get a better understanding to these advanced syntax and functions in SQL, it is paramount that you have…


Data wrangling: Seychelles travel data

Data wrangling which is often known as data cleaning is an important step in the data analysis process. Data cleaning has often been done with Excel among other tools in the past which was time consuming. The preparation of data with Excel constituted 80% of the work to be done while data analysis constituted 20%. However, with the introduction of Tableau prep, data cleaning can be easily done in a lesser amount of time than before. Our project at Git Girl for the month of April was wrangling the travel data for Seychelles from 2000–2017…


A Beginner’s Guide: Python Packages

Hello everyone!!! Today I’ll be taking you on a step by step process on another project from the Git Girl program which I am currently enrolled in. To get more information about Git Girl, visit their website: https://www.gitgirl.co/ .

In this post, I’ll give you a brief introduction to python packages which will be used for the project which will be discussed. The concept to be covered includes NumPy, Pandas and Matplotlib. Datacamp and Dataquest provides some free resources that cover these concepts, so make sure to check it out.

NUMPY

According to Wikipedia, This is…

Oluwafunmilayo C. Sofuwa

Data Analyst

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