


Writing Python Dictionaries to CSV Files
If you need to write a Python dictionary to a csv file, where the dictionary keys appear in the first row and the key values in the second, employ the following approach:
Step 1: Use DictWriter.writerow()
The code you cited uses DictWriter.writerows() which expects a list of dictionaries, not a single dictionary. To write a single row, utilize DictWriter.writerow():
import csv my_dict = {"test": 1, "testing": 2} with open("mycsvfile.csv", "w", newline="") as f: w = csv.DictWriter(f, my_dict.keys()) w.writeheader() w.writerow(my_dict)
Step 2: Include DictWriter.writeheader()
If you desire a header row for your CSV file, call DictWriter.writeheader() before writing the dictionary:
w.writeheader() w.writerow(my_dict)
Step 3: Utilize the "with" Statement
The "with" statement handles file opening and closing elegantly, even during exceptions:
with open("mycsvfile.csv", "w", newline="") as f: # ...
Step 4: Disable Newline Management
The CSV writer manages line breaks internally, so disable the default behavior in open() using newline="":
with open("mycsvfile.csv", "w", newline="") as f: # ...
This revised code generates a CSV file with the dictionary keys and values correctly separated:
test,testing 1,2
The above is the detailed content of How to Write a Python Dictionary to a CSV File with Keys and Values in Separate Rows?. For more information, please follow other related articles on the PHP Chinese website!

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

SublimeText3 English version
Recommended: Win version, supports code prompts!

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

Zend Studio 13.0.1
Powerful PHP integrated development environment

Atom editor mac version download
The most popular open source editor

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.
