What are the most common pandas ways to select/filter rows of a dataframe whose index is a MultiIndex?

• Slicing based on a single value/label
• Slicing based on multiple labels from one or more levels
• Filtering on boolean conditions and expressions
• Which methods are applicable in what circumstances

Assumptions for simplicity:

1. input dataframe does not have duplicate index keys
2. input dataframe below only has two levels. (Most solutions shown here generalize to N levels)

---

Example input:

mux = pd.MultiIndex.from_arrays([
    list('aaaabbbbbccddddd'),
    list('tuvwtuvwtuvwtuvw')
], names=['one', 'two'])

df = pd.DataFrame({'col': np.arange(len(mux))}, mux)

         col
one two     
a   t      0
    u      1
    v      2
    w      3
b   t      4
    u      5
    v      6
    w      7
    t      8
c   u      9
    v     10
d   w     11
    t     12
    u     13
    v     14
    w     15

Question 1: Selecting a Single Item

How do I select rows having "a" in level "one"?

         col
one two     
a   t      0
    u      1
    v      2
    w      3

Additionally, how would I be able to drop level "one" in the output?

     col
two     
t      0
u      1
v      2
w      3

Question 1b
How do I slice all rows with value "t" on level "two"?

         col
one two     
a   t      0
b   t      4
    t      8
d   t     12

Question 2: Selecting Multiple Values in a Level

How can I select rows corresponding to items "b" and "d" in level "one"?

         col
one two     
b   t      4
    u      5
    v      6
    w      7
    t      8
d   w     11
    t     12
    u     13
    v     14
    w     15

Question 2b
How would I get all values corresponding to "t" and "w" in level "two"?

         col
one two     
a   t      0
    w      3
b   t      4
    w      7
    t      8
d   w     11
    t     12
    w     15

Question 3: Slicing a Single Cross Section (x, y)

How do I retrieve a cross section, i.e., a single row having a specific values for the index from df? Specifically, how do I retrieve the cross section of ('c', 'u'), given by

         col
one two     
c   u      9

Question 4: Slicing Multiple Cross Sections [(a, b), (c, d), ...]

How do I select the two rows corresponding to ('c', 'u'), and ('a', 'w')?

         col
one two     
c   u      9
a   w      3

Question 5: One Item Sliced per Level

How can I retrieve all rows corresponding to "a" in level "one" or "t" in level "two"?

         col
one two     
a   t      0
    u      1
    v      2
    w      3
b   t      4
    t      8
d   t     12

Question 6: Arbitrary Slicing

How can I slice specific cross sections? For "a" and "b", I would like to select all rows with sub-levels "u" and "v", and for "d", I would like to select rows with sub-level "w".

         col
one two     
a   u      1
    v      2
b   u      5
    v      6
d   w     11
    w     15

Question 7 will use a unique setup consisting of a numeric level:

np.random.seed(0)
mux2 = pd.MultiIndex.from_arrays([
    list('aaaabbbbbccddddd'),
    np.random.choice(10, size=16)
], names=['one', 'two'])

df2 = pd.DataFrame({'col': np.arange(len(mux2))}, mux2)

         col
one two     
a   5      0
    0      1
    3      2
    3      3
b   7      4
    9      5
    3      6
    5      7
    2      8
c   4      9
    7     10
d   6     11
    8     12
    8     13
    1     14
    6     15

Question 7: Filtering by numeric inequality on individual levels of the multiindex

How do I get all rows where values in level "two" are greater than 5?

         col
one two     
b   7      4
    9      5
c   7     10
d   6     11
    8     12
    8     13
    6     15

---

Note: This post will not go through how to create MultiIndexes, how to perform assignment operations on them, or any performance related discussions (these are separate topics for another time).