Insérer un lien URL au-dessus et la première rangée de données de pandas

Question

Comment est-ce que j'insérerais un lien d'URL à la cellule supérieure de mon dataframe pandas?

myurl = 'www.xyz.com'

Disons que voici mon code:

import pandas as pd 
import numpy as np 

dates = pd.date_range('20130101', periods=4) 
df = pd.DataFrame(np.random.randn(6,4), columns=dates) 

sortie du code:

2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0 -1.359604 2.236055 -1.247478 -0.466911 
1 0.632732 1.177155 0.572847 0.024058 
2 0.301902 -0.118306 -1.162931 0.180230 
3 -0.851283 -0.427693 0.070223 -1.469248 
4 -0.309400 0.935575 1.938843 1.898458 
5 -0.598406 0.519100 -0.700112 0.539412 

souhaitee output1:

www.xyz.com 
    2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0 -1.359604 2.236055 -1.247478 -0.466911 
1 0.632732 1.177155 0.572847 0.024058 
2 0.301902 -0.118306 -1.162931 0.180230 
3 -0.851283 -0.427693 0.070223 -1.469248 
4 -0.309400 0.935575 1.938843 1.898458 
5 -0.598406 0.519100 -0.700112 0.539412 

Résultat souhaité2:

2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0 www.xyz.com 
1 -1.359604 2.236055 -1.247478 -0.466911 
2 0.632732 1.177155 0.572847 0.024058 
3 0.301902 -0.118306 -1.162931 0.180230 
4 -0.851283 -0.427693 0.070223 -1.469248 
5 -0.309400 0.935575 1.938843 1.898458 
6 -0.598406 0.519100 -0.700112 0.539412 

Answer 1

Est-ce ce que vous cherchez? (Renommer la colonne et le nom index)

df.rename_axis('www.xyz.com',axis=1) 

www.xyz.com 2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0    -0.168198 -1.129815 0.427983 -0.788428 
1    0.382714 0.539336 -0.568658 0.783393 
2    -0.738407 0.276275 0.347246 0.956509 
3    1.620627 0.373145 -0.308667 -1.366621 
4    0.778496 -0.432625 -0.863804 1.362475 
5    0.629325 0.435807 -0.681608 -0.077567 

df.rename_axis('www.xyz.com',axis=0) 
Out[138]: 
      2013-01-01 2013-01-02 2013-01-03 2013-01-04 
www.xyz.com             
0    -0.168198 -1.129815 0.427983 -0.788428 
1    0.382714 0.539336 -0.568658 0.783393 
2    -0.738407 0.276275 0.347246 0.956509 
3    1.620627 0.373145 -0.308667 -1.366621 
4    0.778496 -0.432625 -0.863804 1.362475 
5    0.629325 0.435807 -0.681608 -0.077567 

base sur vos besoins ..

sortie2 désiré:

pd.concat([pd.DataFrame({df.columns[0]:['www.xyz.com']}),df],axis=0).fillna('').reset_index(drop=True) 
Out[146]: 
    2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0 www.xyz.com         
1 -0.168198 -1.12982 0.427983 -0.788428 
2  0.382714 0.539336 -0.568658 0.783393 
3 -0.738407 0.276275 0.347246 0.956509 
4  1.62063 0.373145 -0.308667 -1.36662 
5  0.778496 -0.432625 -0.863804 1.36248 
6  0.629325 0.435807 -0.681608 -0.0775674 

et

souhaitee output1:

print('www.xyz.com','\n',df) 
www.xyz.com 
    2013-01-01 2013-01-02 2013-01-03 2013-01-04 
0 -0.168198 -1.129815 0.427983 -0.788428 
1 0.382714 0.539336 -0.568658 0.783393 
2 -0.738407 0.276275 0.347246 0.956509 
3 1.620627 0.373145 -0.308667 -1.366621 
4 0.778496 -0.432625 -0.863804 1.362475 
5 0.629325 0.435807 -0.681608 -0.077567