visualize based on two pandas data frame columns (continuous values and marker style)

I would like to visualize a dataset (with legend and color bar). The dataset is a pandas dataframe as follows: X and Y are the values, the year column defines the year of data collection, and the shape column defines the method that is used in data collection. I am wondering how I can plot Y against X while color-coded based on years and markers (and therefore legend) defined by shape in one command such as plot.

df = pd.DataFrame({
    'X':     [1,    1,    2,    2,    2,    3,    3,    4],
    'Y':     [3,    4,    1,    6,    7,    8,    8,    5],
    'year':  [1998, 1999, 1994, 1991, 1999, 1995, 1994, 1992],
    'shape': ['o',  '^',  'o',  '^',  'o',  '^',  'o',  '^']
})

Of course, I can loop over the shapes and plot per shape (method) and add a color bar separately as well ensuring the min and max of the years in the color bar and legend based on shape. I would like to avoid loop and manual setting of legend or color bar if possible. I am wondering if there is a better way forward. Thank you!

>Solution :

This sounds like a job for seaborn:

import seaborn as sns
sns.scatterplot(data=df, x='X', y='Y',
                hue='year',
                style='shape',
                markers=df['shape'].unique().tolist()
)

Output:

Is this what you are looking for?