[Feature]: Logarithmic Transformation - Githubissues

OPCODE-Open-Spring-Fest / Accommodating-Insights

This project delves into a rich dataset containing information about short-term rentals in a geographic location. By analyzing this data, we aim to uncover insights and trends within the rental market.

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[Feature]: Logarithmic Transformation #2

Closed Dev7g closed 7 months ago

Dev7g commented 7 months ago

So, what is it about?

What is the distribution of logarithmically transformed prices (price_log) for listings, and how does it compare to a normal distribution?

Logarithmic Transformation:

Take the logarithmic transformation of the 'price' column and add it as a new column named 'price_log' to the dataframe.

Plot a histogram or kernel density estimate (KDE) plot to visualize the distribution of 'price_log'.
Overlay a normal distribution curve on the plot to compare it with the observed distribution.

Observations:

Analyze the plot to assess the similarity between the distribution of 'price_log' and a normal distribution.
Determine if the logarithmically transformed prices exhibit characteristics of normality, such as symmetry and peakedness.
Consider any deviations from normality and their implications for statistical analysis or modeling.

Code of Conduct

[X] I agree to follow this project's Code of Conduct

xTwo56 commented 7 months ago

Can I have this assignment

Dev7g commented 7 months ago

okay , assigning you this issue for 2 days @xTwo56