str.lower() and str.upper() in Pandas - Mini Project: Build & Apply

Using str.lower() and str.upper() with pandas

📖 Scenario: You work in a company that collects customer feedback. The feedback data has inconsistent capitalization, making it hard to analyze.You want to standardize the text to either all lowercase or all uppercase to make searching and grouping easier.

🎯 Goal: Standardize the customer feedback text by converting all entries to lowercase and uppercase using pandas string methods.

📋 What You'll Learn

Create a pandas DataFrame with a column named feedback containing exact text entries.

Create a variable to store the column name feedback.

Use str.lower() to convert the feedback text to lowercase.

Use str.upper() to convert the feedback text to uppercase.

Print the resulting lowercase and uppercase DataFrames.

💡 Why This Matters

🌍 Real World

Standardizing text data is important in customer feedback analysis, sentiment analysis, and search functionality to ensure consistent results.

💼 Career

Data analysts and data scientists often clean and preprocess text data using string methods like <code>str.lower()</code> and <code>str.upper()</code> before analysis.

1

Create the feedback DataFrame

Create a pandas DataFrame called df with a column named feedback containing these exact entries: 'Great Service', 'quick response', 'Friendly Staff', 'Will come again'.

Pandas

import pandas as pd

# Create DataFrame df with feedback column and exact entries
# Your code here

Hint

Use pd.DataFrame with a dictionary where the key is 'feedback' and the value is the list of strings.

2

Create a variable for the column name

Create a variable called col_name and set it to the string 'feedback'.

Pandas

import pandas as pd

df = pd.DataFrame({
    'feedback': ['Great Service', 'quick response', 'Friendly Staff', 'Will come again']
})

# Create variable col_name with value 'feedback'
# Your code here

Hint

Just assign the string 'feedback' to the variable col_name.

3

Convert feedback text to lowercase and uppercase

Create two new variables: lowercase_feedback and uppercase_feedback. Use df[col_name].str.lower() to set lowercase_feedback and df[col_name].str.upper() to set uppercase_feedback.

Pandas

import pandas as pd

df = pd.DataFrame({
    'feedback': ['Great Service', 'quick response', 'Friendly Staff', 'Will come again']
})

col_name = 'feedback'

# Create lowercase_feedback using df[col_name].str.lower()
# Create uppercase_feedback using df[col_name].str.upper()
# Your code here

Hint

Use the pandas string methods str.lower() and str.upper() on the column accessed by df[col_name].

4

Print the lowercase and uppercase feedback

Print lowercase_feedback and then print uppercase_feedback.

Pandas

import pandas as pd

df = pd.DataFrame({
    'feedback': ['Great Service', 'quick response', 'Friendly Staff', 'Will come again']
})

col_name = 'feedback'

lowercase_feedback = df[col_name].str.lower()
uppercase_feedback = df[col_name].str.upper()

# Print lowercase_feedback
# Print uppercase_feedback
# Your code here

Hint

Use two print() statements, one for each variable.

Practice

1. What does the pandas method str.lower() do when applied to a Series of text data?

easy

A. Converts all characters in the text to lowercase.

B. Converts all characters in the text to uppercase.

C. Removes all spaces from the text.

D. Reverses the order of characters in the text.

Solution

1. Step 1: Understand the method purpose

   The str.lower() method changes all letters in text to lowercase.

2. Step 2: Compare with other options

   Other options describe different actions like uppercase, removing spaces, or reversing text, which are not what str.lower() does.

3. Final Answer:

   Converts all characters in the text to lowercase. -> Option A

4. Quick Check:

   str.lower() = lowercase conversion [OK]

Hint: Lowercase means all letters small [OK]

Common Mistakes:

• Confusing str.lower() with str.upper()
• Thinking it removes spaces
• Assuming it reverses text

2. Which of the following is the correct way to convert a pandas Series named names to uppercase?

easy

A. names.str.upper()

B. str.upper(names)

C. names.upper()

D. names.str.upper

Solution

1. Step 1: Recall pandas string method syntax

   To apply string methods on a pandas Series, use Series.str.method() syntax.

2. Step 2: Check each option

   names.str.upper() uses names.str.upper(), which is correct. names.upper() misses .str, str.upper(names) is incorrect function call, names.str.upper misses parentheses.

3. Final Answer:

   names.str.upper() -> Option A

4. Quick Check:

   Use .str.upper() on Series [OK]

Hint: Use .str before string methods on Series [OK]

Common Mistakes:

• Calling upper() directly on Series without .str
• Forgetting parentheses after method
• Using str.upper() as a standalone function

3. Given the pandas Series data = pd.Series(['Apple', 'Banana', 'Cherry']), what is the output of data.str.lower()?

medium

A. ['Apple', 'Banana', 'Cherry']

B. ['APPLE', 'BANANA', 'CHERRY']

C. ['apple', 'banana', 'cherry']

D. ['aPPLE', 'bANANA', 'cHERRY']

Solution

1. Step 1: Understand the input Series

   The Series contains capitalized fruit names: 'Apple', 'Banana', 'Cherry'.

2. Step 2: Apply str.lower() method

   This method converts all letters to lowercase, so each word becomes fully lowercase.

3. Final Answer:

   ['apple', 'banana', 'cherry'] -> Option C

4. Quick Check:

   str.lower() makes all letters lowercase [OK]

Hint: str.lower() makes all letters small [OK]

Common Mistakes:

• Expecting original case to remain
• Confusing with str.upper() output
• Thinking only first letter changes

4. What is wrong with this code snippet to convert a pandas Series cities to uppercase?

cities = pd.Series(['Paris', 'London', 'Berlin'])
cities_upper = cities.upper()

medium

A. Missing import statement for pandas.

B. The code should use cities.upper without parentheses.

C. Series cannot be converted to uppercase.

D. Method upper() should be called as cities.str.upper().

Solution

1. Step 1: Identify method usage on Series

   String methods like upper() must be called with .str accessor on pandas Series.

2. Step 2: Check the code

   The code uses cities.upper() which is invalid; correct is cities.str.upper().

3. Final Answer:

   Method upper() should be called as cities.str.upper(). -> Option D

4. Quick Check:

   Use .str.upper() on Series [OK]

Hint: Use .str before string methods on Series [OK]

Common Mistakes:

• Calling upper() directly on Series
• Forgetting .str accessor
• Removing parentheses from method call

5. You have a pandas DataFrame df with a column 'Product' containing mixed case product names. You want to create a new column 'Product_Upper' with all names in uppercase. Which code correctly does this?

hard

A. df['Product_Upper'] = df['Product'].upper()

B. df['Product_Upper'] = df['Product'].str.upper()

C. df['Product_Upper'] = str.upper(df['Product'])

D. df['Product_Upper'] = df['Product'].str.lower()

Solution

1. Step 1: Understand the DataFrame and goal

   The goal is to create a new column with uppercase product names from an existing column.

2. Step 2: Apply correct method for uppercase conversion

   Use .str.upper() on the Series to convert text to uppercase correctly.

3. Step 3: Check options

   df['Product_Upper'] = df['Product'].str.upper() uses correct syntax. df['Product_Upper'] = df['Product'].upper() misses .str, df['Product_Upper'] = str.upper(df['Product']) uses wrong function call, df['Product_Upper'] = df['Product'].str.lower() converts to lowercase, not uppercase.

4. Final Answer:

   df['Product_Upper'] = df['Product'].str.upper() -> Option B

5. Quick Check:

   Use .str.upper() to uppercase Series text [OK]

Hint: Use .str.upper() to convert Series text uppercase [OK]

Common Mistakes:

• Calling upper() without .str
• Using str.upper() as a function on Series
• Confusing upper() with lower()