I'm Farah Ibrar, originally from the United Kingdom. I hold a BSc in Biomedical Sciences (Hons) and recently completed my MSc in Biomedical Sciences (Immunology) from the University of Westminster, London.
My academic path sparked a deep interest in data analytics, visualization, and technology, particularly through Bioinformatics and R. My Master's final project in Data Science focused on innovating database storage solutions for OMICS data solidified my passion. Since then, I have been actively enhancing my skills in data&tech. Currently, I'm advancing my skills in programming and data analysis through a Python course with CFG powered by Activision.
Python |
RStudio |
MySQL |
PostgreSQL |
SPSS |
HTML5 |
CSS |
JavaScript |
Tableau |
Anaconda |
VSCode |
Jupyter |
Github |
![]() Git |
Nodejs |
NumPy |
Pandas |
Sklearn |
Pytorch |
Matplotlib |
Seaborn |
TensorFlow |
Docker |
SpaCy |
PyCharm |
Canva |
Figma |
This Python script automates outlier detection using the Interquartile Range (IQR) method, a robust statistical technique. By calculating the IQR and defining upper and lower bounds, it identifies significant anomalies in datasets. This streamlines data cleaning, ensuring more accurate and reliable analysis.
import numpy as np
def detect_outliers(data):
q1, q3 = np.percentile(data, [25, 75])
iqr = q3 - q1
lower_bound = q1 - 1.5 * iqr
upper_bound = q3 1.5 * iqr
outliers = [x for x in data if x < lower_bound or x > upper_bound]
return outliers
if __name__ == "__main__":
# Example usage:
data = [12, 18, 25, 7, 10, 15, 8, 19, 3, 100, 16] # Example dataset with an outlier (100)
print("Detecting Outliers...")
outliers = detect_outliers(data)
if outliers:
print("Outliers detected:", outliers)
else:
print("No outliers detected.")
I advocate for a healthy but busy lifestyle and thrive on continuous learning and new challenges. Motivational quotes keep me focused and driven, fueling my passion for growth and inspiration.
![]() Cricket |
![]() Badminton |
![]() Cooking |
![]() Reading |
![]() Travelling |
![]() Productive |
![]() Training |
![]() Music |
![]() Dancing |
![]() AI |
Click to find out more!
- Multilingual: Fluent in 4 languages—English, Urdu, Punjabi, and Hindi.
- Achievements: Best Progress Award (2019 & 2020), Rochdale School's Badminton Championship Winner (2019), Sports (Cricket and Badminton) Achievements - Secondary School, Best Handwriting Award, State Level Urdu Competition.
- Creative Skills: I have a passion for calligraphy, excel in henna artistry, and can choreograph impressive dance routines.