MultiIndex (hierarchical indexing) in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a MultiIndex from two lists.

Data Analysis Python

import pandas as pd
levels = [['A', 'B'], [1, 2]]
index = pd.MultiIndex.from_product([1])
print(index)

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A[1, 2]

B['A', 'B']

Clevels

Dpd.Index(levels)

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single list instead of a list of lists.

Passing only one level instead of both.

We use pd.MultiIndex.from_product with a list of levels. Here, levels is the list of lists representing each level.

2fill in blank

medium

Complete the code to create a MultiIndex from tuples.

Data Analysis Python

import pandas as pd
arrays = [('A', 1), ('A', 2), ('B', 1), ('B', 2)]
index = pd.MultiIndex.from_tuples([1])
print(index)

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Aarrays

Barrays[0]

Ctuple(arrays)

Dlist(arrays)

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single tuple instead of a list of tuples.

Converting the list unnecessarily.

The from_tuples method expects a list of tuples. Here, arrays is already a list of tuples.

3fill in blank

hard

Fix the error in the code to access the second level of the MultiIndex.

Data Analysis Python

import pandas as pd
index = pd.MultiIndex.from_tuples([('A', 1), ('B', 2)])
second_level = index.[1][1]
print(second_level)

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Alevels

Bcodes

Clabels

Dvalues

Attempts:

3 left

💡 Hint

Common Mistakes

Using labels which is deprecated.

Trying to access levels which gives unique values, not codes.

In pandas 1.0+, codes holds the integer codes for each level. Accessing index.codes[1] gives the second level codes.

4fill in blank

hard

Fill both blanks to create a DataFrame with a MultiIndex and select data for 'B'.

Data Analysis Python

import pandas as pd
index = pd.MultiIndex.from_tuples([('A', 1), ('B', 2), ('B', 3)])
data = pd.DataFrame({'value': [10, 20, 30]}, index=[1])
selected = data.loc[[2]]
print(selected)

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Aindex

B'B'

C'A'

Ddata

Attempts:

3 left

💡 Hint

Common Mistakes

Using the DataFrame itself as index.

Selecting with the wrong label.

The DataFrame uses index as its index. To select rows where the first level is 'B', use data.loc['B'].

5fill in blank

hard

Fill all three blanks to create a MultiIndex DataFrame and filter rows where second level is greater than 1.

Data Analysis Python

import pandas as pd
index = pd.MultiIndex.from_tuples([('X', 1), ('X', 2), ('Y', 3)])
data = pd.DataFrame({'score': [5, 10, 15]}, index=[1])
filtered = data[[[2] for [3] in data.index if [2] > 1]]
print(filtered)

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Aindex

Bx[1]

Cx

Ddata.index

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable names in the list comprehension.

Accessing the wrong level of the MultiIndex.

The DataFrame uses index as its index. The list comprehension iterates over data.index with variable x. To filter rows where the second level (index position 1) is greater than 1, use x[1] > 1.