2

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:

enter image description here

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

enter image description here

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

enter image description here

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  • Please choose a more specific question title. Commented Jan 15, 2021 at 8:40

1 Answer 1

Reset to default
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)
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10 Comments

DO you know other way ? id does not work for me :/
@bruno845 - Can you explian more not working?
@bruno845 - Is possible see your not working code?
because you add another column, I do not want to add another column
jezrael nevertheless I do not have result as DataFrame using your code
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