Need Expert Help with Python Programming Assignment

Aggiornato 2 giorni fa in Presentiamoci
0 2 giorni fa

Hello Python Community,

I hope everyone is doing well. I’m currently tackling a Python programming assignment and I’ve hit a few roadblocks.

Assignment Overview:

The task involves performing data analysis using Python, focusing on the following key areas:

  1. Data Cleaning:
    • Managing missing values
    • Removing duplicates
    • Standardizing data formats
  2. Exploratory Data Analysis (EDA):
    • Generating summary statistics
    • Creating visualizations (histograms, scatter plots, box plots)
    • Identifying and interpreting key patterns or trends
  3. Data Transformation:
    • Normalizing/standardizing data
    • Creating new features based on existing data
  4. Machine Learning Model:
    • Selecting and applying an appropriate model (eg, linear regression, decision tree)
    • Splitting data into training and testing sets
    • Evaluating the model’s performance

Challenges I’m Facing:

  1. Data Cleaning:
    • I’m unsure about the best methods for handling missing values ​​in various contexts.
    • What are the most efficient techniques to identify and remove duplicates?
  2. AND FROM:
    • I need help selecting the appropriate plots to visualize the data effectively.
    • How should I interpret complex patterns in the visualizations?
  3. Data Transformation:
    • The concept of feature engineering is a bit challenging for me. Any practical examples or tips would be helpful.
  4. Machine Learning:
    • Advice on choosing the right machine learning model for my dataset.
    • Best practices for data splitting and accurate model evaluation.

Tools and Libraries I’m Using:

  • Python 3.8
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn

Progress So Far:

  • I’ve loaded the dataset and done some initial cleaning.
  • Generated some basic visualizations with Matplotlib and Seaborn.
  • Attempted data normalization, but I’m not confident in the results.
  • Started with a simple linear regression model, but the performance is not as expected.

What I Need:

  • Advanced data cleaning techniques: examples or tutorials
  • Effective EDA: resources or tips
  • Feature engineering: guidance and practical examples
  • Machine learning model selection and evaluation: recommendations

Any assistance or pointers from this knowledgeable community would be greatly appreciated. I’m also happy to offer help in return through python programming assignment help for anyone who needs it.

Thank you so much for your time and support!

Best regards, Stella Elliott,

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