Seaborn | Matplotlib: Scatter plot: 3rd variable is encoded by both size and colour

Question

I want to create a plot that shows the geographical distribution of nightly prices using longitude and lattitude as coordinates, and the price encoded both by color and size of the circles. I curently have no idea on how to encode the plots by the price in both colour and size. I come to you in search of help~ I dont understand the documentation for seaborn in this scenario.

3 columns of interest:

longtitude     lattitude     Price

50.1235156     4.1236436     160
52.3697862     4.8935462     300
52.3640489     4.8895343     8000
52.3729765     4.8931707     1300
52.3657530     4.8796741     5000
52.2957663     4.3058365     60
52.6709324     4.6028347     100

In my scenario: each column is of equal length, but I only want to include prices that are >150

Im stuck with this filter in play, as the column with the applied filter is half the size as longitude and latitude .

My clueless attempt:

plt.scatter(df.longitude, df.latitude, s=(df.price)>150, c= (df.price)>150)

The way I understand it is that the latitude and longitude create the space/plane, and then apply the price data. But implementing it seems to work differently?

Answer 1

First of all, you need to filter the dataframe before plotting. If you do what you're doing (which won't work anyway), your Series of x and y coordinates will be the entire length of the dataframe but series responsible for color-coding and size will be shorter because you're trying to filter out values under 150 with this: s=(df.price)>150 .

Secondly, you can't plot like this using matplotlib. With matplotlib to color-code points you need to create a dictionary, so I'd suggest using seaborn for simplicity.

import seaborn as sns
import pandas as pd

import matplotlib.pyplot as plt

df_plot = df.loc[df.price > 150]

fig = sns.scatterplot(data=df_plot, x='longitude', y='latitude', size='price', hue='price')
plt.show()