I have a DataFrame that looks something like this:
>>> df = pd.DataFrame(index=pd.MultiIndex.from_tuples([(num,letter,color)
for num in range(1,3)
for letter in ['a','b','c'] for color in ['Red','Green']],
names=['Number','Letter','Color']))
>>> df['Value'] = np.random.randint(1,100,len(df))
>>> df
Value
Number Letter Color
1 a Red 97
Green 61
b Red 97
Green 98
c Red 91
Green 47
2 a Red 17
Green 63
b Red 26
Green 73
c Red 34
Green 68
But I actually want my index to be ordered 'Letter, Color, Number'.
I currently do this as follows:
>>> df.reset_index().set_index(['Letter','Color','Number'])
Value
Letter Color Number
a Red 1 97
Green 1 61
b Red 1 97
Green 1 98
c Red 1 91
Green 1 47
a Red 2 17
Green 2 63
b Red 2 26
Green 2 73
c Red 2 34
Green 2 68
Is this the best approach?
It's better to use reorder_levels
to manipulate the order of MultiIndex levels. Just pass in a list of the level names/numbers in the order you want:
>>> df.reorder_levels(['Letter','Color','Number'])
Value
Letter Color Number
a Red 1 41
Green 1 56
b Red 1 43
Green 1 42
c Red 1 89
Green 1 18
a Red 2 55
Green 2 93
b Red 2 64
Green 2 9
c Red 2 21
Green 2 93
There's also swaplevel
if you simply want to swap the positions of two levels.
Call MultiIndex.reorder_levels
, then assign the new index to your DataFrame.
df.index = df.index.reorder_levels(['Letter', 'Color', 'Number'])
df
Value
Letter Color Number
a Red 1 41
Green 1 56
b Red 1 43
Green 1 42
c Red 1 89
Green 1 18
a Red 2 55
Green 2 93
b Red 2 64
Green 2 9
c Red 2 21
Green 2 93
Since Index objects are immutable, you cannot get over creating a new Index, but you can avoid duplicating your data by otherwise calling df.reorder_levels
.
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