Making $65 per Hour on Upwork with Pandas

Pandas, an open-source data analysis and manipulation library for Python, is a tool of choice for many professionals in data science. Its advanced features and capabilities enable users to manipulate, analyze, and visualize data efficiently. πŸ‘©β€πŸ’» Recommended: 10 Minutes to Pandas (in 5 Minutes) In the above video “Making $65 per Hour on Upwork with … Read more

Python Web Scraping: From URL to CSV in No Time

Setting up the Environment Before diving into web scraping with Python, set up your environment by installing the necessary libraries. First, install the following libraries: requests, BeautifulSoup, and pandas. These packages play a crucial role in web scraping, each serving different purposes.✨ To install these libraries, click on the previously provided links for a full … Read more

Python List of Tuples to DataFrame 🐼

To convert a list of tuples to a Pandas DataFrame, import the pandas library, call the DataFrame constructor, and pass the list of tuples as the data argument such as in pd.DataFrame(tuples_list, columns=[‘Number’, ‘Letter’]). Here’s a minimal example: The output of the given code will be a Pandas DataFrame with two columns, ‘Number’ and ‘Letter’, … Read more

Dictionary of Lists to DataFrame – Python Conversion

Problem Formulation Working with Python often involves processing complex data structures such as dictionaries and lists. In many instances, it becomes necessary to convert a dictionary of lists into a more convenient and structured format like a Pandas DataFrame 🐼. DataFrames offer numerous benefits, including easier data handling and analysis πŸ”, as well as an … Read more

Pandas Boolean Indexing

Boolean indexing in Pandas filters DataFrame rows using conditions. Example: df[df[‘column’] > 5] returns rows where ‘column’ values exceed 5. Efficiently manage and manipulate data with this method. Here’s an easy example: This code creates a DataFrame with data for four people, then uses boolean indexing to filter out the rows with an age greater … Read more

Python List of Dicts to Pandas DataFrame

In this article, I will discuss a popular and efficient way to work with structured data in Python using DataFrames. πŸ’‘ A DataFrame is a two-dimensional, size-mutable, and heterogeneous tabular data structure with labeled axes (rows and columns). It can be thought of as a table or a spreadsheet with rows and columns that can … Read more

How I Scattered My Fat with Python – Scraping and Analyzing My Nutrition Data From

From April 1st through August 14th, I tracked everything I ate on as part of a weight loss challenge. Overall I lost almost 25 pounds at a rate of 1.2 pounds per week. I always wondered what I could learn if I could scrape that data and get it into a Jupyter Notebook. In … Read more

Data Science Tells This Story About the Global Wine Markets 🍷

πŸ“– Background Many people like to relax or party with a glass of wine. That makes wine an important industry in many countries. Understanding this market is important to the livelihood of many people. For fun, consider the following fictional scenario: 🍷 Story: You work at a multinational consumer goods organization that is considering entering … Read more

Basketball Statistics – Page Scraping Using Python and BeautifulSoup

In this blog series, powerful Python libraries are leveraged to help uncover some hidden statistical truths in basketball. The first step in any data-driven approach is to identify and collect the data needed. Luckily for us, hosts pages of basketball data that can be easily scraped. The processes of this walkthrough can be easily … Read more

Bitcoin – Trading Moving Averages or HODL? A Python Script Uncovers the Answer!

I’ve always wondered if a slow and high-level trading strategy focusing on long-term trends could outperform a buy-and-hold strategy. To answer this question, I created a Python script that would utilize a momentum-based strategy to tell me when to buy and when to sell Bitcoin. Despite my busy life and doubts that day trading would … Read more