https://github.com/huseyincenik/data_science

Data Science materials
https://github.com/huseyincenik/data_science

data data-science data-structures data-visualization dataanalysis dataengineering datapreparation dataprocessing datascience dataset time-series time-series-analysis timeline timeseries timeseries-analysis timeseriesforecasting

Last synced: 2 months ago
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Data Science materials

• Host: GitHub
• URL: https://github.com/huseyincenik/data_science
• Owner: huseyincenik
• Created: 2023-05-09T02:24:37.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-09-15T13:37:55.000Z (5 months ago)
• Last Synced: 2024-09-16T14:00:19.887Z (5 months ago)
• Topics: data, data-science, data-structures, data-visualization, dataanalysis, dataengineering, datapreparation, dataprocessing, datascience, dataset, time-series, time-series-analysis, timeline, timeseries, timeseries-analysis, timeseriesforecasting
• Language: Jupyter Notebook
• Homepage:
• Size: 53.1 MB
• Stars: 3
• Watchers: 0
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Data Analysis with Python

## Projects

| Project Name | Description | GitHub | Kaggle |

| --- | --- | --- | --- |

| **Bike Demand Visualization Capstone Project** | Explore bike demand trends through interactive visualizations. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/Bike%20Demand%20Visualization%20Capstone%20Project) | [Kaggle](https://www.kaggle.com/code/huseyincenik/bike-demand-visualization-capstone-project) |

| **Capstone Project (AutoScout Exploratory Data Analysis (EDA) Project)** | Ongoing project with continuous updates. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/Capstone%20Project) | [Kaggle](https://www.kaggle.com/code/huseyincenik/autoscout-exploratory-data-analysis-part-1) [Kaggle](https://www.kaggle.com/code/huseyincenik/autoscout-exploratory-data-analysis-part-2) [Kaggle](https://www.kaggle.com/code/huseyincenik/autoscout-exploratory-data-analysis-part-3) |

| **Exploratory Data Analysis (EDA) Project For Top Games on Google Play** | Analyze and visualize trends in the top games on Google Play. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/Exploratory%20Data%20Analysis%20(EDA)%20Project%20For%20Top%20Games%20on%20Google%20Play) | [Kaggle](https://www.kaggle.com/code/huseyincenik/eda-project-for-top-games-on-google-play) |

| **Health Expense Explorer** | Investigate health expense data for valuable insights. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/Health%20Expense%20Explorer) | [Kaggle](https://www.kaggle.com/code/huseyincenik/health-expense-explorer) |

| **RFM Analysis Project** | Apply RFM analysis for customer segmentation and insights. | [GitHub](https://github.com/huseyincenik/SQL---Structured-Query-Language/tree/main/Projects/RFM%20Analysis%20Project) | [Kaggle]() |

| **Segmentation - Cohort - RFM - Analysis** | Explore segmentation, cohort, and RFM analysis for business insights. | [GitHub](https://github.com/huseyincenik/SQL---Structured-Query-Language/tree/main/Projects/Segmentation%20-%20Cohort%20-%20RFM%20-%20Analysis) | [Kaggle](https://www.kaggle.com/code/ahmetyazgan/rfm-segmentation-cohort-analysis) |

| **Titanic - EDA, A Statistical Analysis and Prediction** | Analyze and predict outcomes based on Titanic passenger data. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/Titanic%20-%20EDA%2C%20A_Statistical_Analysis%20and%20Prediction) | [Kaggle](https://www.kaggle.com/code/huseyincenik/titanic-eda-statistical-analysis-and-prediction) |

| **World Happiness Analysis** | Investigate factors influencing world happiness levels. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/Projects/World%20Happiness%20Analysis%2C) | [Kaggle]() |

| **Time Series Analysis** | Comprehensive exploration of time series data using various decomposition methods. | [GitHub](https://github.com/huseyincenik/data_science/tree/main/time_series_analysis) | [Kaggle]() |