We need to perform data exploration and preprocessing for the dataset in the notebooks/EDA.ipynb notebook. The main objectives include understanding the data structure, identifying relationships between features and the target variable, and handling missing values and outliers.
Tasks:
Load the dataset:
Ensure the dataset is correctly loaded into the notebook.
Explore the data structure:
Examine the types and structure of the data.
Generate summary statistics for numerical and categorical features.
Visualize relationships:
Create visualizations to understand the relationships between different features and the target variable.
Use plots such as histograms, box plots, scatter plots, and correlation heatmaps.
Identify missing values and outliers:
Detect and quantify missing values in the dataset.
Identify outliers and consider their impact on the analysis.
Document findings:
Provide a summary of findings from the exploration phase.
Suggest potential next steps for data preprocessing based on the identified issues.
Assignment:
Assign this issue to @sharad3595 . The assignee is responsible for completing the tasks outlined above and documenting their process and findings in the notebooks/EDA.ipynb notebook.
Description:
We need to perform data exploration and preprocessing for the dataset in the
notebooks/EDA.ipynb
notebook. The main objectives include understanding the data structure, identifying relationships between features and the target variable, and handling missing values and outliers.Tasks:
Load the dataset:
Explore the data structure:
Visualize relationships:
Identify missing values and outliers:
Document findings:
Assignment:
Assign this issue to @sharad3595 . The assignee is responsible for completing the tasks outlined above and documenting their process and findings in the
notebooks/EDA.ipynb
notebook.Deadline:
[Specify Deadline]