In this tutorial, you’ll learn how to use the Pandas read_parquet function to read parquet files in Pandas. While CSV files may be the ubiquitous file format for data analysts, they have limitations as your data size grows. This is where Apache Parquet files can help! By the end of this tutorial, you’ll have learned: […]
pd.read_parquet: Read Parquet Files in Pandas Read More »
In this tutorial, you’ll learn how to use the Pandas dropna() method to drop missing values in a Pandas DataFrame. Working with missing data is one of the essential skills in cleaning your data before analyzing it. Because data cleaning can take up to 80% of a data analyst’s / data scientist’s time, being able
Pandas dropna(): Drop Missing Records and Columns in DataFrames Read More »
In this tutorial, you’ll learn how to flatten an array with NumPy flatten function, meaning that an array is collapsed to a single dimension. The NumPy flatten function allows you to turn a multi-dimensional array into a single-dimensional array. The function allows you to easily flatten arrays in different ways, including column-wise and row-wise. By
Flatten an Array with NumPy flatten Read More »
In this tutorial, you’ll learn how to add a new column to a Pandas DataFrame. The Pandas library provides a helpful way of working with tabular data. One of the most common tasks you’ll encounter is the need to add more data to a Pandas DataFrame. By the end of this tutorial, you’ll have learned:
How to Add a New Column to a Pandas DataFrame Read More »
The Python requests library in Python allows you to send HTTP requests easily. The library abstracts much of the complexity of making requests, by using a simple and consistent API. This guide provides an in-depth view of the essential aspects of the requests library and points to further guides that go even deeper. By the
Python Requests Library: A Guide Read More »
In this tutorial, you’ll learn how to use the Python requests library to make HTTP requests behind a proxy server. This has numerous benefits, including staying anonymous and secure and preventing having an IP address blocked. You’ll learn how to set HTTP, HTTPS, and FTP proxies. By the end of this tutorial, you’ll have learned:
Using a Proxy Server with Python requests Read More »
In this tutorial, you’ll learn how to use the Python requests Session object to persist certain parameters across requests. Doing this allows you to persist cookies across all of the requests made from the Session and will use the same connection pooling. Sessions allow you to work across HTTP GET and HTTP POST requests, as
Python requests and Persistent Sessions Read More »
In this tutorial, you’ll learn how to use timeouts in the Python requests library, when working with any type of HTTP request being made. By default, the requests library will not time out any request you make, which can result in your programming running indefinitely if a server doesn’t respond. By the end of this
Timeouts in Python requests Read More »
In this tutorial, you’ll learn how to provide authentication for the requests you make with the Python requests library. Many web services, such as APIs, require authentication. This can often be a daunting topic for beginner or novice programmers, alike. This is especially true, given that there are many different types of authentication. Thankfully, the
Authentication with Python Requests: A Complete Guide Read More »
In this tutorial, you’ll learn how to use custom headers with the Python requests library. HTTP headers allow you to send additional information to a server and allow the server to provide additional information back to you. Being able to work with headers allows you to, for example, authenticate yourself when working with APIs or
Using Headers with Python requests Read More »
In this tutorial, you’ll learn how to parse a Python requests response as JSON and convert it to a Python dictionary. Whenever the requests library is used to make a request, a Response object is returned. The Python requests library provides a helpful method, json(), to convert a Response object to a Python dictionary. By
response.json() – Working with JSON in Python requests Read More »
In this tutorial, you’ll learn how to install the popular requests package in Python, including on Windows, macOS, and Linux. The requests library is a popular HTTP library that can handle generating different types of requests, including GET, POST, and PUT requests. The library is available for Python 3 from the Python Package Index (PyPI).
How to Install requests Package in Python – Windows, macOS, and Linux Read More »
