Using adjustText to avoid label overlap with Python prince correspondence analysis

Question

I have read about how efficient the package adjustText is with respect to avoiding label overlap and I would like to use to the following diagram created by prince:

Here is the code that created the image:

import pandas as pd
import prince
from adjustText import adjust_text

pd.set_option('display.float_format', lambda x: '{:.6f}'.format(x))
X=pd.DataFrame(data=[ ... my data ... ],
columns=pd.Series([ ... my data ... ]),
index=pd.Series([ ... my data ...]),
)

ca = prince.CA(n_components=2,n_iter=3,copy=True,check_input=True,engine='auto',random_state=42)
ca = ca.fit(X)
ca.row_coordinates(X)
ca.column_coordinates(X)
ax = ca.plot_coordinates(X=X,ax=None,figsize=(6, 6),x_component=0,y_component=1,show_row_labels=True,show_col_labels=True)

ax.get_figure().savefig('figure.png')

In all examples of adjustText I could find, there was always a direct access to the coordinates of labels. How do I access the coordinates of labels in this case? How can I apply adjust_text to this figure?

Answer 1

You can also put a small angle in texts iteration. I saw on my side that it helps the adjust_text routine.

texts=[plt.text(XGLOBAL[x],YGLOBAL[x],x,fontsize=7, 
rotation = -XGLOBAL.keys()+2*x) for x in XGLOBAL.keys()]

Answer 2

First, deactivate label display by plot_coordinates():

ax = ca.plot_coordinates(X=X,ax=None,figsize=(6, 6),x_component=0,y_component=1,show_row_labels=False,show_col_labels=False)

Then, extract coordinates of columns and rows:

COLS=ca.column_coordinates(X).to_dict()
XCOLS=COLS[0]
YCOLS=COLS[1]
ROWS=ca.row_coordinates(X).to_dict()
XROWS=ROWS[0]
YROWS=ROWS[1]

Structures XCOLS, YCOLS, XROWS, YROWS are dictionaries with values that are floats (the coordinates). Let us merge the two x-axis dictionaries in a single x-axis dictionary I will call XGLOBAL, same thing for the y-axis dictionaries, into YGLOBAL:

XGLOBAL={ k : XCOLS.get(k,0)+XROWS.get(k,0) for k in set(XCOLS) | set(XROWS) }
YGLOBAL={ k : YCOLS.get(k,0)+YROWS.get(k,0) for k in set(YCOLS) | set(YROWS) }

Now I just apply adjust_text() as described in the documentation:

fig = ax.get_figure()
texts=[plt.text(XGLOBAL[x],YGLOBAL[x],x,fontsize=7) for x in XGLOBAL.keys()]
adjust_text(texts,arrowprops=dict(arrowstyle='-', color='red'))
fig.savefig('newfigure.png')

And the result is:

Notice that while the image generation was instantaneous without adjust_text, it took around 40 seconds with adjust_text.