San Francisco Housing Analysis

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San Francisco Housing Analysis

This project covers the use of PyVis and the hvplots library to plot and analyze rent statistics based on location.

"If you're going to San Francisco be sure to wear some flowers in your hair."

Technologies

This project uses Python, Pandas, and the Hvplot library to plot graphical interpretations of data.

pandas HVplot

Installation Guide

In order to use this program please import and utilize the following libraries and dependencies:

import pandas as pd
import hvplot.pandas
from pathlib import Path

Usage

the following blocks of code from the Pandas library are fundamental in executing the program.

pd.read_csv(Path("../"))

This imports a local csv file for integration.

pd.groupby("")

This command groups the output of a pandas DataFrame by a specfic string.

df.hvplot.bar("")

This is a plot code using the HVplot "Bar" graph type. It will output your data in a standard bar graph.

df.hvplot.line(xlabel="",ylabel="")

This is a plot that uses a line(s) for graphing data. You can specify labels for the X and Y axes.

df.hvplot.points("")

This code will plot a graph using points across a geographical overlay. You may be required to specify a "geo" parameter in boolean "True" or "False" logic. Additionally you will likely need to specify "Longitude" and "Lattitude" as parameters for the graph to plot.

Contributors

Jeffrey J. Wiley Jr

License

MIT