Reading and writing CSV data in Python - Step-by-Step Execution

Concept Flow - Reading and writing CSV data

Open CSV file for reading

↓

Create CSV reader object

↓

Loop: Read each row

↓

More rows?

No→Close file

Open a CSV file, create a reader, loop through rows, process each, then close the file.

Execution Sample

Python

import csv
with open('data.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

Reads each row from 'data.csv' and prints it as a list.

Execution Table

Step	Action	Evaluation	Result
1	Open 'data.csv' for reading	File opened	File object created
2	Create csv.reader object	csv.reader(file)	Reader object ready
3	Read first row	reader.__next__()	Row 1 data as list
4	Print row	print(row)	Row 1 printed
5	Read second row	reader.__next__()	Row 2 data as list
6	Print row	print(row)	Row 2 printed
7	Read next row	reader.__next__()	No more rows, StopIteration raised
8	Exit loop	StopIteration caught	Loop ends
9	Close file	file.close()	File closed

💡 No more rows to read, StopIteration ends the loop

Variable Tracker

Variable	Start	After 1	After 2	Final
file	None	File object	File object	Closed
reader	None	Reader object	Reader object	Reader object
row	None	Row 1 list	Row 2 list	None (loop ended)

Key Moments - 3 Insights

Why does the loop stop reading rows?

The loop stops because the csv.reader raises StopIteration when no more rows exist, as shown in execution_table step 7.

What type of data is each 'row' variable during the loop?

Each 'row' is a list of strings representing the CSV columns, as seen in execution_table steps 3 and 5.

Why do we use 'with open' instead of just open()?

'with open' automatically closes the file after the block ends, ensuring no file remains open, as shown in execution_table step 9.

Visual Quiz - 3 Questions

Look at the execution_table, what is the value of 'row' after step 3?

A None

B Row 1 data as list

C Row 2 data as list

D File object

💡 Hint

Check the 'Result' column in execution_table row with Step 3

At which step does the loop stop reading rows?

A Step 9

B Step 5

C Step 7

D Step 3

💡 Hint

Look for StopIteration in the 'Evaluation' column in execution_table

If the CSV file had 3 rows instead of 2, how would the execution_table change?

A There would be an extra pair of 'Read row' and 'Print row' steps before step 7

B The file would close earlier

C The reader object would be created twice

D The loop would never end

💡 Hint

Check the pattern of reading and printing rows in execution_table steps 3-6

Concept Snapshot

Reading CSV:
- Use 'with open(filename, "r") as file'
- Create reader: csv.reader(file)
- Loop: for row in reader
- Each row is a list of strings
- File auto-closed after block

Writing CSV:
- Use 'with open(filename, "w", newline="") as file'
- Create writer: csv.writer(file)
- Use writer.writerow(list) to write rows

Full Transcript

This visual trace shows how Python reads CSV data step-by-step. First, the file is opened for reading. Then, a csv.reader object is created to parse the file. The program loops over each row, reading and printing it as a list of strings. When no more rows exist, the reader raises StopIteration, ending the loop. Finally, the file is closed automatically by the 'with' statement. Variables like 'file', 'reader', and 'row' change values as the program runs. Key points include understanding the StopIteration that ends the loop, the list structure of each row, and the automatic file closing with 'with open'. The quiz questions help check understanding of these steps.

Practice

1. What does the Python csv.reader function do when reading a CSV file?

easy

A. It deletes rows from the CSV file.

B. It reads the file and returns each row as a list of strings.

C. It converts CSV data into a dictionary automatically.

D. It writes data to a CSV file.

Solution

1. Step 1: Understand csv.reader purpose

   The csv.reader reads CSV files and returns each row as a list of strings representing columns.

2. Step 2: Differentiate from other functions

   Functions like csv.DictReader return dictionaries, and writing functions save data, not read it.

3. Final Answer:

   It reads the file and returns each row as a list of strings. -> Option B

4. Quick Check:

   csv.reader returns lists [OK]

Hint: csv.reader reads rows as lists, not dictionaries [OK]

Common Mistakes:

• Confusing csv.reader with csv.DictReader
• Thinking csv.reader writes data
• Assuming it deletes or modifies files

2. Which of the following is the correct way to open a CSV file for writing in Python?

easy

A. open('file.csv', 'w', newline='')

B. open('file.csv', 'r')

C. open('file.csv', 'a', encoding='utf-8')

D. open('file.csv', 'rb')

Solution

1. Step 1: Identify mode for writing CSV

   To write CSV files, open the file in write mode 'w' and use newline='' to prevent extra blank lines on Windows.

2. Step 2: Check other options

   'r' is read mode, 'a' is append (valid but not asked), 'rb' is binary read mode (not for writing text CSV).

3. Final Answer:

   open('file.csv', 'w', newline='') -> Option A

4. Quick Check:

   Write mode with newline='' [OK]

Hint: Use 'w' mode with newline='' to write CSV files correctly [OK]

Common Mistakes:

• Forgetting newline='' causes blank lines
• Using 'r' mode when writing
• Using binary mode for text CSV

3. What will be the output of this code snippet?

import csv
with open('data.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(['Name', 'Age'])
    writer.writerow(['Alice', 30])

with open('data.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)

medium

A. ['Name', 'Age']\n['Alice', 30]

B. Name,Age\nAlice,30

C. ['Name', 'Age']\n['Alice', '30']

D. Error because of missing encoding

Solution

1. Step 1: Writing rows with csv.writer

   The code writes two rows: header ['Name', 'Age'] and data ['Alice', 30]. Numbers are converted to strings when written.

2. Step 2: Reading rows with csv.reader and printing

   Reading returns each row as a list of strings. print(row) shows repr with quotes: ['Name', 'Age'] and ['Alice', '30'].

3. Final Answer:

   ['Name', 'Age']\n['Alice', '30'] -> Option C

4. Quick Check:

   csv.writer writes lists, csv.reader reads lists [OK]

Hint: csv.reader returns lists of strings, print shows quotes around all elements [OK]

Common Mistakes:

• Expecting printed rows as comma strings
• Confusing string and integer types in output
• Assuming encoding error without cause

4. Identify the error in this code that reads a CSV file:

import csv
with open('file.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
    print(row)

medium

A. Indentation error in the for loop

B. Missing import statement for csv module

C. File opened in wrong mode

D. csv.reader requires newline argument

Solution

1. Step 1: Check code indentation

   The print statement inside the for loop must be indented to be part of the loop body.

2. Step 2: Verify other parts

   Import is present, file mode 'r' is correct for reading, and newline argument is not needed for reading.

3. Final Answer:

   Indentation error in the for loop -> Option A

4. Quick Check:

   Python requires correct indentation [OK]

Hint: Indent inside loops to avoid syntax errors [OK]

Common Mistakes:

• Forgetting to indent inside loops
• Thinking newline is needed for reading
• Confusing file modes

5. You want to read a CSV file where the first row contains column names, and then write a new CSV file with only rows where the 'Age' column is greater than 25. Which approach is correct?

hard

A. Use csv.reader to read, skip first row manually, filter rows, then write with csv.writer.

B. Use csv.writer to read and write files directly without filtering.

C. Use csv.reader to read all rows, convert 'Age' to int, then write with csv.DictWriter without header.

D. Use csv.DictReader to read rows as dictionaries, filter by 'Age' key, then write with csv.DictWriter including header.

Solution

1. Step 1: Choose reading method with headers

   csv.DictReader reads CSV rows as dictionaries using the first row as keys, making it easy to filter by column names like 'Age'.

2. Step 2: Filter and write with headers

   Filter rows where 'Age' > 25, then write using csv.DictWriter with fieldnames to include headers properly.

3. Final Answer:

   Use csv.DictReader to read rows as dictionaries, filter by 'Age' key, then write with csv.DictWriter including header. -> Option D

4. Quick Check:

   DictReader + DictWriter for header and filtering [OK]

Hint: Use DictReader/DictWriter for header-based filtering [OK]

Common Mistakes:

• Skipping header manually instead of using DictReader
• Writing without headers causing missing columns
• Using csv.writer without filtering logic