Python Write CSV File

Sure, here’s an example of how to write a CSV file in Python:

import csv

# Define the data to be written in CSV file
data = [
    ['Name', 'Age', 'Gender'],
    ['John Doe', 25, 'Male'],
    ['Jane Doe', 30, 'Female'],
    ['Bob Smith', 35, 'Male']
]

# Define the name of CSV file to be created
filename = "example.csv"

# Open the CSV file in write mode
with open(filename, 'w', newline='') as file:

    # Create a CSV writer object
    writer = csv.writer(file)

    # Write the data to the CSV file
    writer.writerows(data)

print("CSV file created successfully.")

In this example, we first import the csv module, which provides functionality for reading and writing CSV files.

Next, we define the data that we want to write to the CSV file. This is simply a list of lists, where each inner list represents a row in the CSV file.

We then specify the name of the CSV file that we want to create.

We open the file in write mode using the open() function, and use the csv.writer() function to create a CSV writer object. We then use the writerows() method to write the data to the CSV file.

Finally, we print a message indicating that the CSV file has been created successfully.

Note that we use the newline='' parameter when opening the file to ensure that no extra blank lines are added between rows in the CSV file. This is important because some applications may not handle these blank lines correctly.

Python CSV Module Functions:

The csv module in Python provides several functions that allow you to work with CSV files. Here are some of the most commonly used functions:

1. csv.reader(file, dialect='excel', **fmtparams) – This function returns a reader object that can be used to read data from a CSV file. It takes a file object as its first argument and optional dialect and fmtparams arguments.
2. csv.writer(file, dialect='excel', **fmtparams) – This function returns a writer object that can be used to write data to a CSV file. It takes a file object as its first argument and optional dialect and fmtparams arguments.
3. csv.DictReader(file, fieldnames=None, restkey=None, restval=None, dialect='excel', **fmtparams) – This function returns a reader object that can be used to read data from a CSV file as a dictionary. It takes a file object as its first argument and optional fieldnames, restkey, restval, dialect and fmtparams arguments.
4. csv.DictWriter(file, fieldnames, restval='', extrasaction='raise', dialect='excel', **fmtparams) – This function returns a writer object that can be used to write data to a CSV file as a dictionary. It takes a file object as its first argument and mandatory fieldnames argument, restval, extrasaction, dialect and fmtparams arguments are optional.
5. csv.field_size_limit([new_limit]) – This function returns the current size limit for fields allowed in the CSV file. If new_limit argument is provided, it sets a new size limit.
6. csv.get_dialect(name) – This function returns the dialect associated with the given name.
7. csv.list_dialects() – This function returns a list of all available dialect names.

These functions provide a powerful way to read and write data to CSV files using Python. The csv module also provides a number of options for specifying the format of the CSV file, such as the delimiter character, quote character, and line terminator. By default, the module uses the comma as the delimiter, double quotes as the quote character, and CRLF as the line terminator.

Writing CSV Files:

To write data to a CSV file in Python, you can use the csv.writer() function provided by the csv module. Here’s an example:

import csv

# Data to be written to the CSV file
data = [
    ['Name', 'Age', 'Gender'],
    ['John', 25, 'Male'],
    ['Jane', 30, 'Female'],
    ['Bob', 35, 'Male']
]

# Open the CSV file in write mode
with open('example.csv', 'w', newline='') as file:

    # Create a CSV writer object
    writer = csv.writer(file)

    # Write the data to the CSV file
    writer.writerows(data)

print('Data written to the CSV file.')

In this example, we first import the csv module. Then we define the data that we want to write to the CSV file as a list of lists. Each inner list represents a row in the CSV file.

Next, we open the CSV file in write mode using the open() function, passing the name of the file, the mode (‘w’ for write), and the optional newline='' argument to prevent blank lines between rows.

We then create a CSV writer object using the csv.writer() function and pass in the file object as an argument.

Finally, we use the writerows() method of the CSV writer object to write the data to the CSV file. This method takes a list of lists as an argument and writes each inner list as a row in the CSV file.

After the data has been written to the file, we print a message indicating that the data has been written to the CSV file.

Note that when using the csv.writer() function, the module will automatically handle special characters, such as commas and quotes, by quoting them appropriately. This ensures that the data is written to the CSV file correctly and can be read back in without any issues.

Write a CSV into a Dictionary:

To read a CSV file into a dictionary in Python, you can use the csv.DictReader() function provided by the csv module. Here’s an example:

Suppose we have a CSV file example.csv with the following content:

Name, Age, Gender
John, 25, Male
Jane, 30, Female
Bob, 35, Male

import csv

# Open the CSV file in read mode
with open('example.csv', 'r') as file:

    # Create a CSV reader object
    reader = csv.DictReader(file)

    # Create an empty dictionary to store the data
    data = {}

    # Loop through each row in the CSV file
    for row in reader:
        name = row['Name']
        age = row['Age']
        gender = row['Gender']

        # Add the row data to the dictionary
        data[name] = {'Age': age, 'Gender': gender}

print(data)

data = {'Name': ['John', 'Jane', 'Bob'],
        'Age': [25, 30, 35],
        'Gender': ['Male', 'Female', 'Male']}

import pandas as pd

df = pd.DataFrame(data)

df.to_csv('example.csv', index=False)

Name,Age,Gender
John,25,Male
Jane,30,Female
Bob,35,Male