Difficult problem with multi index in DataFrame in Python Pandas?

Question

I have DataFrame like below:

df = pd.DataFrame({"ID" : ["1", "1", "1", "2", "3"], "value" : [10, 11, 12, 13, 14]})
df.set_index(["ID", "value"], inplace=True)

By doing so I have multiindex "ID" and "value" like below:

What can I do so as to have this multiindex like on the result like below:

I tried also other way on the data frame like below:

df = pd.DataFrame({"ID" : ["1", "1", "1", "2", "3"], "value" : [10, 11, 12, 13, 14], "a} : [1,2,3,4,5)
df.set_index(["ID", "value"], inplace=True)

And code:

#temporaly display all levels of MultiIndex
with pd.option_context('display.multi_sparse',False):
    print (df)

But result is not a "elegant" DataFrame

Please choose a more specific question title.

a_guest
– a_guest

2021-01-15 08:40:26 +00:00
Commented Jan 15, 2021 at 8:40 — a_guest
– a_guest, Commented Jan 15, 2021 at 8:40

jezrael · Accepted Answer · 2021-01-15 08:39:35Z

2

It is about diplaying, by default are hidden repeated values, link :

display.multi_sparse, True, “Sparsify” MultiIndex display (don’t display repeated elements in outer levels within groups)

df = pd.DataFrame({"ID" : ["1", "1", "1", "2", "3"], "value" : [10, 11, 12, 13, 14]})
df.set_index(["ID", "value"], inplace=True)
df['tmp'] = 1

#temporaly display all levels of MultiIndex
with pd.option_context('display.multi_sparse',False):
    print (df)
          tmp
ID value     
1  10       1
1  11       1
1  12       1
2  13       1
3  14       1

For set always display all levels (not default option):

pd.set_option('display.multi_sparse', False)
print (df)

edited Jan 15, 2021 at 8:39

answered Jan 15, 2021 at 8:29

jezrael

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10 Comments

dingaro Over a year ago

DO you know other way ? id does not work for me :/

jezrael Over a year ago

@bruno845 - Can you explian more not working?

jezrael Over a year ago

@bruno845 - Is possible see your not working code?

dingaro Over a year ago

because you add another column, I do not want to add another column

dingaro Over a year ago

jezrael nevertheless I do not have result as DataFrame using your code

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