https://github.com/caterinatasinato/excel-projects
Projects I worked on as Trainee in Data Analytics at ProfessionAI
https://github.com/caterinatasinato/excel-projects
excel statistics
Last synced: 4 months ago
JSON representation
Projects I worked on as Trainee in Data Analytics at ProfessionAI
- Host: GitHub
- URL: https://github.com/caterinatasinato/excel-projects
- Owner: caterinatasinato
- Created: 2024-07-04T10:13:38.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-10T17:42:55.000Z (over 1 year ago)
- Last Synced: 2025-03-05T00:18:27.461Z (over 1 year ago)
- Topics: excel, statistics
- Homepage: https://profession.ai/
- Size: 274 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🧩 My Excel Projects
Welcome to my repository of Excel projects! ✨
This repository showcases various projects and analyses I worked on as a trainee in **Data Analytics** at **ProfessionAI**. Each folder represents a separate project and includes detailed documentation, examples, and insights. Feel free to explore the projects below to see the approaches I used and the results I achieved. 🦋
## Projects Overview
### 1. Customer Complaints Analysis 🗂️
In this project, I worked with a dataset of user complaints submitted to financial management companies. The main objectives were to:
- **Transform and Clean Data:** Reformat and organize the dataset to meet specific requirements.
- **Analyze Complaint Data:** Perform calculations to understand complaint trends.
- **Generate Reports:** Showcase the geographical distribution of complaints and provide statistical insights.
**Key Features:**
- **Data Cleaning and Reformatting:** Transform raw data to meet specific formatting and structuring requirements.
- **Analysis of Complaint Trends and Responses:** Perform calculations to uncover trends and evaluate responses.
- **Geographical Insights and Statistical Evaluations:** Generate reports on the geographical distribution of complaints and perform statistical evaluations of the data.
**Folder Contents:**
- 📊 **Excel Spreadsheet:** Detailed analysis of customer complaints.
- 📄 **Documentation:** Methods and methodologies used for the analysis.
---
### 2. Trade of Financial Operations 💹
In this project, I analyzed financial trading data to explore trading operations and perform various financial analyses. The main objectives were to:
- **Format and Analyze Trading Data:** Perform calculations, and analyze trading performance.
- **Summarize Trade Activities:** Evaluate trade metrics and calculate tax obligations for different stock exchanges.
- **Calculate and Visualize Profit Insights:** Provide detailed analyses of trade profits and durations.
- **Distribute Trade Data:** Analyze the distribution of trades across regions and calculate specific probabilities.
**Key Features:**
- **Date Formatting and Profit Calculation:** Reformat dates and calculate profits for each trade.
- **Pivot Table Creation for Trade Activities and Tax Calculations:** Summarize trade activities and determine tax obligations for various stock exchanges.
- **Bar Chart Visualizations and Trade Duration Analysis:** Create charts to visualize trade durations and analyze the results.
- **Distribution Analysis and Probability Calculations:** Analyze the distribution of trades across regions and calculate relevant probabilities.
**Folder Contents:**
- 📊 **Excel Spreadsheet:** Detailed analysis of financial trading operations.
- 📄 **Documentation:** Tasks performed, insights gained, and explanations of calculations and visualizations.
---
### 3. Data Generation and Analysis for the Luggnagg Population 📊
This project involves creating a dataset, performing data manipulations, and conducting statistical analyses using Excel. The goal was to consolidate concepts from inferential statistics by generating and analyzing data for a fictional population.
**Key Features:**
- **Data Generation:** Simulate ages of 250 individuals using normal distribution parameters.
- **Sample Analysis:** Extract and analyze a sample to perform statistical calculations and estimations.
- **Correlation Analysis:** Explore relationships between age, number of cats, and partner's age.
- **Linear Regression:** Perform a regression analysis to study the relationship between age and rank.
**Folder Contents:**
- 📊 **Excel Spreadsheet:** Contains datasets, calculations, and analyses.
- 📄 **Documentation:** Detailed explanations of tasks performed, methodologies used, and analysis results.
- 📈 **Charts and Graphs:** Visualizations for statistical insights, correlation analysis, and linear regression.
**Excel Workbook Structure:**
| Sheet Name | Description | Tasks and Contents |
|--------------------------|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------------|
| **Parameters** | Contains parameters for age data generation. | Set up values for probability, mean, and standard deviation. |
| **Data** | The generated age data and group assignments. | View age data and group numbers for 250 individuals. |
| **Sample** | Includes age data, group assignments, and a filtered sample for analysis. | Analyze a subset of data based on a selected group. |
| **Statistical Insight** | Provides statistical calculations and insights based on the sample data. | Perform statistical calculations and explain results. |
| **Uncorrelated Variables** | Explores correlation between age, number of cats, and partner's age. | Perform and explain correlation analysis for different variables. |
| **Linear Regression** | Contains linear regression analysis between age and rank. | Analyze the relationship between age and rank with scatterplots and regression results. |
**Instructions for Using the Excel Workbook:**
1. **Review the Parameters:** Check the `Parameters` sheet for the values used in data generation.
2. **Explore the Data:** View the `Data` sheet for age data and group assignments.
3. **Analyze the Sample:** Use the `Sample` sheet to review the subset of data and analyze the selected group.
4. **Perform Statistical Analysis:** Review the `Statistical Insight` sheet for statistical calculations and interpretations.
5. **Examine Correlations:** Check the `Uncorrelated Variables` sheet for correlation analysis and explanations.
6. **Review the Linear Regression:** Use the `Linear Regression` sheet for regression analysis and visualizations.
**Results and Analysis:**
- **Statistical Insights:** Provides a summary of sample data statistics, including standard deviation, mean, and confidence intervals.
- **Correlation Analysis:** Demonstrates relationships between variables and compares actual vs. desired correlations.
- **Linear Regression:** Contains a scatterplot and regression analysis for the relationship between age and rank.