How Can I Read and Write CSV Files in Python?
CSV File I/O in Python
Reading CSV Files
To read the provided CSV file, you can use the csv module in Python. Here's an example:
import csv with open('sample.csv', 'r') as f: reader = csv.reader(f, delimiter=',', quotechar='"') data_read = [row for row in reader]
This code reads the CSV file line by line, converts each line to a list of strings, and stores the resulting list in data_read.
Writing CSV Files
To write data to a CSV file, you can again use the csv module. Here's an example:
import csv with open('sample.csv', 'w', newline='') as f: writer = csv.writer(f, delimiter=',', quotechar='"') writer.writerow(['1', 'A towel', '1.0']) writer.writerow(['42', ' it says, ', '2.0']) # ... continue writing data ...
This code creates a new CSV file with the specified delimiter and quote character and writes rows to it.
Python 2 to Python 3 Note
Please note that the Python 2 version of the above code is no longer supported. The provided code is compatible with Python 3 and above.
Alternatives to CSV
CSV is a common file format for data exchange, but there are other alternatives to consider:
- JSON: Another popular format that is often used for storing data in a human-readable way.
- YAML: A configuration language that is commonly used for writing Python configuration files.
- Pickle: A Python-specific serialization format that is often used for storing Python objects.
- MessagePack: A binary serialization format that is compact and efficient.
- HDF5: A hierarchical data format that is often used for storing large datasets.
The choice of which format to use will depend on the specific requirements of your application, such as readability, performance, or compatibility with other systems.
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