Write dictionary of lists to a CSV file in python

Write dictionary of lists to a CSV file in python

You can write a dictionary of lists to a CSV file in Python using the csv module. Here's an example of how you can do this:

import csv # Dictionary of lists data = { 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 28], 'Country': ['USA', 'Canada', 'UK'] } # Specify the CSV file name csv_file = 'data.csv' # Write the dictionary of lists to the CSV file with open(csv_file, 'w', newline='') as file: writer = csv.writer(file) # Write the header writer.writerow(data.keys()) # Write the rows writer.writerows(zip(*data.values())) print(f'Data has been written to {csv_file}')

In this example, the csv.writer is used to write the data to the CSV file. The keys() of the dictionary are written as the header row, and the values() are transposed using the zip(*data.values()) to match the structure of the CSV rows.

The newline='' parameter in open() is used to prevent extra newline characters in the CSV file, which can cause formatting issues.

Make sure to replace the sample data and file name with your own dictionary of lists and desired CSV file name.

Examples

  1. "How to write a dictionary of lists to a CSV file in Python?"

    • Description: Learn how to write a dictionary of lists to a CSV file, where each list represents a row or column in the CSV.

    • Code:

      pip install pandas # If using pandas to simplify CSV handling 
      import csv # Dictionary of lists where keys represent column headers data = { "Name": ["Alice", "Bob", "Charlie"], "Age": [25, 30, 35], "City": ["New York", "Los Angeles", "Chicago"] } # Write to CSV with the dictionary keys as headers with open("output.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile) # Write headers writer.writerow(data.keys()) # Write rows by transposing the dictionary values for row in zip(*data.values()): writer.writerow(row)

  2. "Writing a dictionary of lists to a CSV with custom delimiter"

    • Description: Learn how to write a CSV file with a custom delimiter, using a dictionary of lists.
    • Code:
      import csv # Dictionary of lists data = { "Product": ["Widget", "Gadget", "Thingamajig"], "Price": [19.99, 29.99, 39.99], "Stock": [100, 200, 300] } # Write to CSV with a custom delimiter (e.g., semicolon) with open("custom_delimiter.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile, delimiter=";") writer.writerow(data.keys()) # Write headers for row in zip(*data.values()): # Write rows writer.writerow(row)

  3. "Writing dictionary of lists to CSV with specific quoting"

    • Description: Learn how to control quoting in CSV files when writing from a dictionary of lists.
    • Code:
      import csv # Dictionary of lists with text that might need quoting data = { "Quote": ["He said, \"Hello!\"", "Another, \"example\"", "Without quotes"], "Score": [10, 20, 30] } # Write to CSV with quoting all fields with open("quoted_output.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile, quoting=csv.QUOTE_ALL) writer.writerow(data.keys()) # Write headers for row in zip(*data.values()): # Write rows writer.writerow(row)

  4. "Writing dictionary of lists to CSV with custom fieldnames"

    • Description: Learn how to specify custom fieldnames when writing a dictionary of lists to a CSV.
    • Code:
      import csv # Dictionary of lists with custom fieldnames data = { "Column1": ["A", "B", "C"], "Column2": ["X", "Y", "Z"] } # Custom fieldnames fieldnames = ["Custom1", "Custom2"] # Write to CSV with custom fieldnames with open("custom_fieldnames.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile) writer.writerow(fieldnames) # Write custom headers for row in zip(*data.values()): # Write rows writer.writerow(row)

  5. "Writing dictionary of lists to CSV with pandas"

    • Description: Learn how to use pandas to write a dictionary of lists to a CSV file, simplifying the process.
    • Code:
      import pandas as pd # Dictionary of lists data = { "Employee": ["John", "Jane", "Joe"], "Department": ["HR", "Finance", "IT"], "Salary": [50000, 60000, 70000] } # Convert the dictionary to a DataFrame df = pd.DataFrame(data) # Write the DataFrame to a CSV file df.to_csv("pandas_output.csv", index=False) # No index column in CSV

  6. "Writing a dictionary of lists to CSV with custom newline handling"

    • Description: Learn how to handle newlines within CSV data when writing from a dictionary of lists.
    • Code:
      import csv # Dictionary of lists with text containing newlines data = { "Description": ["First\nLine", "Second\nLine", "Third Line"], "Value": [100, 200, 300] } # Write to CSV with appropriate newline handling with open("newline_output.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile, quoting=csv.QUOTE_ALL) # Ensure proper handling writer.writerow(data.keys()) # Write headers for row in zip(*data.values()): # Write rows writer.writerow(row)

  7. "Appending to an existing CSV file with dictionary of lists"

    • Description: Learn how to append new data from a dictionary of lists to an existing CSV file.
    • Code:
      import csv # Additional data to append to an existing CSV new_data = { "Name": ["Dave", "Eve"], "Age": [40, 45], "City": ["Miami", "Boston"] } # Append to the existing CSV file with open("output.csv", "a", newline="") as csvfile: # Open in append mode writer = csv.writer(csvfile) for row in zip(*new_data.values()): # Append new rows writer.writerow(row)

  8. "Writing a dictionary of lists to CSV with custom order"

    • Description: Learn how to control the order of columns when writing a dictionary of lists to CSV.
    • Code:
      import csv # Dictionary of lists data = { "Country": ["USA", "Canada", "Mexico"], "Population": [331000000, 37742154, 126014024] } # Desired order of columns ordered_keys = ["Population", "Country"] # Custom order # Write to CSV with specific column order with open("ordered_output.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile) writer.writerow(ordered_keys) # Write headers in custom order for row in zip(*[data[key] for key in ordered_keys]): # Write rows writer.writerow(row)

  9. "Write a dictionary of lists to CSV with dynamic row count"

    • Description: Learn how to write a CSV with a variable number of rows using a dictionary of lists.
    • Code:
      import csv # Dictionary with different list lengths data = { "ID": [1, 2, 3], "Description": ["Item A", "Item B", "Item C"], "Value": [10, 20, 30, 40, 50] # More elements in one list } # Write to CSV handling different list lengths with open("dynamic_rows.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile) writer.writerow(data.keys()) # Write headers # Determine the maximum row count max_rows = max(len(v) for v in data.values()) for i in range(max_rows): # Write up to the maximum row count row = [data[key][i] if i < len(data[key]) else None for key in data.keys()] writer.writerow(row)

  10. "Writing a dictionary of lists to CSV with nested lists"

    • Description: Learn how to handle nested lists within a dictionary when writing to a CSV file.
    • Code:
      import csv # Dictionary with nested lists data = { "Name": ["Tom", "Jerry"], "Scores": [[100, 90, 80], [95, 85, 75]] # Nested lists } # Write to CSV handling nested lists with open("nested_lists.csv", "w", newline="") as csvfile: writer = csv.writer(csvfile, quoting=csv.QUOTE_ALL) # Ensure proper quoting writer.writerow(data.keys()) # Write headers # Write rows with nested lists converted to strings for row in zip(*data.values()): # Convert nested lists to strings writer.writerow([str(item) if isinstance(item, list) else item for item in row])

More Tags

layout replication avatar database-deadlocks ftp magento can-bus generate talkback cpu-speed

More Python Questions

More Math Calculators

More Bio laboratory Calculators

More General chemistry Calculators

More Dog Calculators