Model Spain's most optimal starting XI based on the video game FIFA 22 data
FIFA 22 Player's Dataset
Python Code - Spain's XI
We will download the FIFA 22 video game dataset for this study. The dataset provides numerous data points and interesting facts and statistics about the players on an individual level, fortunately for this analysis we will be using only a few of the columns on the pertinent dataset... All the transformations and mining of the dataset has been already inputted into the code (So that yo
OBJECTIVEUnderstand how different statistical factors can make a college basketball team successful.
*We obtained our dataset from kaggle.com - College Basketball Dataset
Click on the button below to access R Code ---> Open R Studio project & Run the code to display results & visuals
R Studio Code
We will clean the data in order to work with an accurate model. In our current database, we observe a total of 2455 variables along with 24 columns. We have data from the years 2013 to 2019. For presentation purposes, I'll subset
OBJECTIVEAnalyze the spending of the social media company Snapchat as well as its ads targeting data to target people when getting closer to political elections.
After obtaining the datasets from a third party on a csv format, we will user Excel's Power Query in order to perform data pre processing so that we can structure the dataset to be analyisis friendly. After inserting the 3 different datasets into Tableau, we will preview the data and study the different connections between the data.
OBJECTIVEPredict accurately the winner of the LVI Super Bowl (Bengals vs Rams).
This will be done through a statistical analysis of the regular season to come up with a forecast of "ratings" in order to give value to all the teams. After the analysis is done we will use Solver in order to accurately depict team ratings and the values that the Bengals and Rams possess, allowing us to determine who should win based on the performance of the regular season. The study will be done through Microsoft Excel.
We will being by
OBJECTIVEAfter recent blockbusters like Spider-Man No Way Home, No Time to Die or Uncharted I wondered what would be the correlation between a movie's budget and its success. To do this we will apply correlation models through Python in Jupyter Notebooks.
Link to code in Github
We will start by importing the necessary libraries, pandas, numpy and seaborn. Along with that we will import the database for the movie industry (Which is on a csv format). We will assign the variable "df" to it to make it easier to reference later.
OBJECTIVEStudy the impact of COVID-19 on an international level and at the national level (US). For this analysis I obtained the dataset through the government's CDC official page, then I proceeded to query it and mine it to obtain the necessary data points, this was done through Microsoft Data Studio using SQL. After the mining of data was done I aimed to create a visualization of the study through Tableau data viz software.
The methodology I used to create a visualization of my findings was the following:
After acquiring the datas
Description/ObjectivesMethods - Python/R StudioCode + Visuals
DESCRIPTION - OBJECTIVE OF THE PROJECTAs a soccer fan, I was intrigued by the 2020-2021 season as it was a very thrilling one. Hence, I decided to analyze the player's performance as well as some interesting data points which I considered could bring value to the reader. Though this is a very generic statistical analysis, I'm working on developing further this model through Jupyter Notebooks.
For the study of the dataset I used Jupyter Notebook to code by combining Python and R scripts.
This project was the capstone for my "Market research through data analytics" class.
For 6 months I led a team of 4 people in which we had to present our findings and recommendations to senior executives from the company Grubhub. The team was deemed winner out of the capstone competition over 30 different teams and we got to present our results to the company's executives through a Power Point Presentation, a final report in Word Doc and an Excel file containing essential information regarding the information we analyzed.
OBJECTIVE OF THE PROJECTThe purpose of this
After COVID-19, businesses have been disrupted and after three months of interrupted activity, they won’t go back to normal, or at least for a while. The silver lining of this situation is that businesses are starting to adapt to this new situation… But how?
Over the last decade, almost all companies have advanced exponentially on their digital capabilities over the past few years, but with the amid of the COVID-19 outbreak, companies are suffering moderate impacts; one of them has been shifting all operations to remote work (Even classes) through online methods via vi
Problem to solveData CollectedMethods - R Studio Software / Microsoft ExcelFindings Conclusion
Problem to solveThis Tech Sales Report details the performance of the sales representatives of a Tech Company for2021. It contains the methods used to evaluate the salaries of 12,130 sales representativesfrom the software product group of a high-tech company. For each employee, the data includesocio-demographic and education information, salary, and a personality indicator. Also included inthe data is the net promoter score, which is an indicator of customer satisfaction with
OBJECTIVEAs a fitness enthusiast, I decided to track my steps along with running activity from my Huawei watch. The study started on May 10th and ended on the 8th of June. I decided to present a Power BI dashboard in order to have a quick overview of my exercise data
Data Collection & Table Structures
The necessary data was collected and structured in Excel Files. The exercise data was organized as a fact table and date & activity were organized as dimension tables for filtering the data.
Exercise data was