Creating DataFrame from list of lists in Pandas - Practice Exercises

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this DataFrame creation code?

Given the code below, what will be the content of the DataFrame df?

Pandas

import pandas as pd

data = [[1, 2], [3, 4], [5, 6]]
df = pd.DataFrame(data, columns=['A', 'B'])
print(df)

A

   A  B
0  1  2
1  3  4
2  5  6

B

   A  B
0  1  3
1  2  4
2  5  6

C

   0  1
0  1  2
1  3  4
2  5  6

D Error: Missing columns argument

💡 Hint

Check how columns are assigned when creating a DataFrame from a list of lists.

The DataFrame is created with two columns named 'A' and 'B'. Each inner list becomes a row. So the first row is [1, 2], second is [3, 4], and third is [5, 6].

❓ data_output

intermediate

How many rows and columns does this DataFrame have?

Consider this code creating a DataFrame from a list of lists. How many rows and columns does df have?

Pandas

import pandas as pd

data = [[10, 20, 30], [40, 50, 60]]
df = pd.DataFrame(data)
print(df.shape)

A (3, 3)

B (3, 2)

C (2, 3)

D (2, 2)

💡 Hint

Each inner list is a row; count rows and columns accordingly.

There are 2 inner lists, so 2 rows. Each inner list has 3 elements, so 3 columns. The shape is (2, 3).

🔧 Debug

advanced

Why does this DataFrame creation code raise an error?

Look at this code. Why does it raise an error?

Pandas

import pandas as pd

data = [[1, 2], [3, 4]]
df = pd.DataFrame(data, columns=['A'])

A SyntaxError due to missing brackets

B TypeError because columns must be integers

C No error, DataFrame created with one column

D ValueError because number of columns does not match data width

💡 Hint

Check if the number of columns matches the number of elements in each inner list.

The data has 2 elements per row but only 1 column name is given. This mismatch causes a ValueError.

🚀 Application

advanced

Create a DataFrame with custom row labels from list of lists

You have this list of lists: data = [[7, 8], [9, 10]]. You want to create a DataFrame with columns named X and Y and row labels row1 and row2. Which code does this correctly?

A pd.DataFrame(data, columns=['X', 'Y'], index=['row1', 'row2'])

B pd.DataFrame(data, index=['X', 'Y'], columns=['row1', 'row2'])

C pd.DataFrame(data, columns=['row1', 'row2'], index=['X', 'Y'])

D pd.DataFrame(data, labels=['X', 'Y'], rows=['row1', 'row2'])

💡 Hint

Remember the parameters for columns and index in DataFrame constructor.

The columns parameter sets column names, index sets row labels. Option A uses them correctly.

🧠 Conceptual

expert

What happens if inner lists have different lengths when creating a DataFrame?

Consider this code:

import pandas as pd
data = [[1, 2], [3, 4, 5]]
df = pd.DataFrame(data)

What will be the content of df?

A DataFrame with columns named 0 and 1 only

B DataFrame with NaN in missing places, shape (2, 3)

C DataFrame with only first two columns, extra data ignored

D ValueError due to inconsistent row lengths

💡 Hint

Pandas fills missing values with NaN when rows have different lengths.

Pandas creates columns for the longest row length and fills missing values with NaN for shorter rows.