Hello, I'm ANJANA C, a Post Graduate in Mathematics, and I hold an IBM Professional Data Analyst Certification. I specialize in data analysis with skills in Python, SQL, Tableau, Excel, and Power BI. I am passionate about uncovering insights from data and eager to apply my skills in a professional setting. Thank you for visiting my portfolio; I look forward to connecting and exploring data-driven opportunities.
Predictive analysis is a powerful tool for deriving insights and making informed decisions from data. In this project, I demonstrate how I utilized a linear regression model in Python to predict the water temperature based on salinity?.
Libraries used are : Pandas,NumPy,Matplotlib,Seaborn,Scikit-learn. I collected dataset from Kaggle and performed EDA in python by importing dataset using Pandas.
For this prediction task, I chose a linear regression model due to its simplicity and interpretability. Using Python and the scikit-learn library, I implemented the model to establish a relationship between temperature (dependent variable) and salinity (independent variable).I trained the linear regression model on the training dataset, where salinity serves as the predictor variable and temperature as the target variable. After training, I evaluated the model's performance using metrics such as R-squared on the testing dataset. This allowed me to assess how well the model generalizes to new data.
Budget sales analysis in Power BI enables businesses to assess their actual sales performance against predefined budget targets. By leveraging Power BI's analytical capabilities, we can delve into sales data, identify variances.
In this project, I utilized Power BI to analyze and visualize sales and budget data for a retail company. Compared the actual sales with budgeted sales. Identify trends and patterns in sales performance, profit and quantity ordered. Analyze variance to understand discrepancies
Developed interactive dashboards showcasing key metrics such as actual vs budgeted sales, sales and profit trends,performance by region and product category and customer analysis.
In this project,I conducted an EDA on a heart disease dataset using Python and visualized the findings in Tableau. The goal was to uncover patterns,trends and correlations within the data to gain insights into factors that may contribute to heart disease
Cleaned the data and performed an EDA in python using libraries Pandas, NumPy, Matplotlib and Seaborn.Analyze distribution of key variables like age,sex,blood pressure,cholesterol levels and many more
Created interactive dashboard to visualize key findings from the EDA.
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This project demonstrates my proficiency in SQL for data manipulation and analysis as well as Tableau.Conducted EDA to understand distribution and characteristics of the data.Identified potential factore contributing to attrition,such as job role,department,salary,etc.Created interactive dashboard to showcase key findings.
This financial anlysis project showcases my proficiency in using Python for data analysis and visualization in context of financial markets.By leveraging market capitalization and quarterly sales data, I was able to provide valuabe insights into trends in market capitalization and quarterly sales over time and identified companies with strong financial performance.
This project showcases my proiciency in SQL for data exploration. Used SQL to extract data from 11 different tables using JOIN and did data exploration using CLAUSES and WINDOW functions .
Selected appropriate regression method and applied regression analysis techniques in Excel to build models to forecasts future values.
This Super Bowl player data analysis project showcases my proficiency in using Tableau for visualizing and analyzing sports data .
Scraping data from a real website using Pandas and BeautifulSoup in Python.Libraries like requests makes it easier to scrape websites.
This project deals with analysis of a sales data showcases my proficiency in Python to do EDA.
