Tag: tool
Improve the Security of Your GraphQL API with Escape and Postman
Are you tired of dealing with pesky API vulnerabilities? Want to take your GraphQL game to the next level? Introducing the perfect combo for GraphQL success – Escape and Postman.
Escape is a tool that helps developers automatically and
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Time series data are frequently encountered when working with data in Pandas, and we are aware that Pandas is an excellent tool for working with time-series data in Python. Using the to_datetime() and astype() functions in Pandas, you can convert a column (of a text, object, or integer type) to a datetime. Furthermore, if you’re reading data from an external source like CSV or Excel, you can specify the data type (for instance,...
📖 tl;dr: Whether you’re building, testing and/or linting JavaScript, module resolution is always at the heart of everything. Despite its central place in our tools, not much time has been spent on making that aspect fast. With the changes discussed in this blog post tools can be sped up by as much as 30%. In part 1 of this series…
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A 2-dimensional labeled data structure like a table with rows and columns is what the Pandas DataFrame is. The dataframe’s size and values are mutable or changeable. It is the panda thing that is used the most. There are various ways to generate a Pandas DataFrame. Let’s go over each method for creating a DataFrame one at a time.
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There are various approaches to counting the number of rows and columns in Pandas. These include: “len(),” “df.shape[0],” “df[df.columns[0]].count(),” “df.count(),” and “df.size().” Note that len()is the fastest of these methods. As a result, we will be centering on len() to explore its functionality, its use, and why one should opt to use it.
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We’ve started making a tradition of rounding up the latest front-end research at the end of each year. We did it in 2020 and again in 2021. Reports are released throughout the year by a bunch of different companies …
2022 Roundup of Web Research originally published on CSS-Tricks, which is part of the DigitalOcean family. You should get the newsletter.
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Introduction
When programming a tool for a dynamic security scan of an API, you need a way to know what requests you can send, with what parameters and in what order so you can have maximum API coverage to improve the scan quality. The whole point is to generate legitimate
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This tutorial will explore the Python pandas DataFrame.ffill() method. This method adds the missing value to the DataFrame by filling it from the last value before the null value. Fill stands for “forward fill.” By using this method on the DataFrame and learning the syntax and parameters, we will be in a position to solve examples and comprehend the DataFrame.ffill() function.
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📖 tl;dr: Most popular libraries can be sped up by avoiding unnecessary type conversions or by avoiding creating functions inside functions. Whilst the trend is seemingly to rewrite every JavaScript build tool in other languages such as Rust or Go, the current JavaScript-based tools could be a lot faster. The build pipeline in a typical frontend project is usually composed…
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Welcome back! This article is the second and last part of the Achieving end-to-end type safety in a modern JS GraphQL stack series. Read the first part if you haven't yet!
Svelte
I won't go into the details of why Svelte, but I like Svelte a
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