Python / Seaborn - How to plot the names of each value in a scatterplot

Question

first of all, in case I comment on any mistakes while writing this, sorry, English is not my first language.

I'm a begginer with Data vizualiation with python, I have a dataframe with 115 rows, and I want to do a scatterplot with 4 quadrants and show the values in R1 (image below for reference)

enter image description here

At moment this is my scatterplot. It's a football player dataset so I want to plot the name of the players name in the 'R1'. Is that possible?

enter image description here

Answer 1

You can annotate each point by making a sub-dataframe of just the players in a quadrant that you care about based on their x/y values using plt.annotate. So something like this:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

##### Making a mock dataset #################################################
names = ['one', 'two', 'three', 'four', 'five', 'six']
value_1 = [1, 2, 3, 4, 5, 6]
value_2 = [1, 2, 3, 4, 5, 6]

df = pd.DataFrame(zip(names, value_1, value_2), columns = ['name', 'v_1', 'v_2'])
#############################################################################

plt.rcParams['figure.figsize'] = (10, 5) # sizing parameter to make the graph bigger
ax1 = sns.scatterplot(x = value_1, y = value_2, s = 100) # graph code

# Code to make a subset of data that fits the specific conditions that I want to annotate
quadrant = df[(df.v_1 > 3) & (df.v_2 > 3)].reset_index(drop = True)

# Code to annotate the above "quadrant" on the graph
for x in range(len(quadrant)):
    plt.annotate('Player: {}\nValue 1: {}\nValue 2: {}'.format(quadrant.name[x], quadrant.v_1[x], quadrant.v_2[x]),
                 (quadrant.v_1[x], quadrant.v_2[x])

Output graph:

If you're just working in the notebook and don't need to save the image with all the player's names, then using a "hover" feature might be a better idea. Annotating every player's name might become too busy for the graph, so just hovering over the point might work out better for you.

%matplotlib widget # place this or "%matplotlib notebook" at the top of your notebook
                   # This allows you to work with matplotlib graphs in line

import mplcursors # this is the module that allows hovering features on your graph

# using the same dataframe from above
ax1 = sns.scatterplot(x = value_1, y = value_2, s = 100)
@mplcursors.cursor(ax1, hover=2).connect("add") # add the plot to the hover feature of mplcursors
def _(sel):
    sel.annotation.set_text('Player: {}\nValue 1: {}\nValue 2: {}'.format(df.name[sel.index], sel.target[0], sel.target[0])) # set the text


    # you don't need any of the below but I like to customize
    sel.annotation.get_bbox_patch().set(fc="lightcoral", alpha=1) # set the box color
    sel.annotation.arrow_patch.set(arrowstyle='-|>', connectionstyle='angle3', fc='black', alpha=.5) # set the arrow style

Example outputs from hovering: