Handling duplicate column names in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a DataFrame with duplicate column names.

Data Analysis Python

import pandas as pd

data = {'A': [1, 2], [1]: [3, 4]}
df = pd.DataFrame(data)
print(df)

Drag options to blanks, or click blank then click option'

A'A'

B'B'

C'C'

D'D'

Attempts:

3 left

💡 Hint

Common Mistakes

Using different keys will not create duplicate columns.

Forgetting to use quotes around column names.

The dictionary keys are column names. Using 'A' twice creates duplicate columns.

2fill in blank

medium

Complete the code to rename duplicate columns by adding suffixes.

Data Analysis Python

df.columns = [col + '_1' if df.columns.duplicated()[i] else col for i, col in enumerate([1])]
print(df.columns)

Drag options to blanks, or click blank then click option'

Adf.columns

Bdf.head()

Cdf.values

Ddf.index

Attempts:

3 left

💡 Hint

Common Mistakes

Using df.index instead of df.columns.

Trying to rename without checking duplicates.

We check duplicates in column names using df.columns.duplicated() and rename accordingly.

3fill in blank

hard

Fix the error in the code to select the first 'A' column from a DataFrame with duplicate columns.

Data Analysis Python

first_A = df[[1]]
print(first_A)

Drag options to blanks, or click blank then click option'

A'A'

B['A']

Cdf['A']

Ddf.columns[0]

Attempts:

3 left

💡 Hint

Common Mistakes

Using df.loc[:, 'A'] which may cause ambiguity with duplicates.

Using a list instead of a string for column selection.

Using df['A'] selects the first column named 'A' even if duplicates exist.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that keeps only columns with unique names.

Data Analysis Python

unique_cols = {col: df[col] for col in df.columns if df.columns.[1](keep=False)[df.columns.[2](col)] == False}

Drag options to blanks, or click blank then click option'

Aduplicated

Bunique

Ctolist

Dget_loc

Attempts:

3 left

💡 Hint

Common Mistakes

Using unique() which returns unique values, not a boolean mask.

Using tolist() which converts to list, not for checking duplicates.

df.columns.duplicated(keep=False)[df.columns.get_loc(col)] returns True if the column name appears more than once. We keep columns where this is False.

5fill in blank

hard

Fill all three blanks to create a DataFrame with unique column names by appending suffixes to duplicates.

Data Analysis Python

cols = []
counter = {}
for col in df.columns:
    if col in counter:
        counter[col] += 1
        cols.append(col + [1] + str(counter[col]))
    else:
        counter[col] = 0
        cols.append(col + [2])
df.columns = cols
print(df.columns)

Drag options to blanks, or click blank then click option'

A'_'

B''

C'-'

D'#'

Attempts:

3 left

💡 Hint

Common Mistakes

Adding suffix to the first occurrence.

Using no separator between name and number.

We add an underscore and a number suffix to duplicate columns. The first occurrence has no suffix.