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Category: Data Science Tutorials

Python Tuples: A Step-by-Step Tutorial (with 14 Code Examples)

When working with data collections, we occasionally encounter situations where we want to ensure it’s impossible to change the sequence of objects after creation. For instance, when reading data from a database in Python, we can represent each table record as an ordered and unchangeable sequence of objects since we don’t need to alter the […]

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DateTime in Pandas: A Simple Guide for Beginners (2022)

We are surrounded by data that comes in different types and forms. No doubt, one of the most interesting and essential data categories is time-series data. Time-series data is everywhere, and it has many applications across various industries. Patient health metrics, stock price changes, weather records, economic indicators, servers, networks, sensors, and applications performance monitoring […]

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Tutorial: Lambda Functions in Python

In this tutorial, we will define lambda functions in Python and explore the advantages and limitations of employing them. What is a Lambda Function in Python? A lambda function is an anonymous function (i.e., defined without a name) that can take any number of arguments but, unlike normal functions, evaluates and returns only one expression. […]

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Tutorial: Using If Statements in Python

Our life is full of conditions even if we don’t notice them most of the time. Let’s look at a few examples: If tomorrow it doesn’t rain, I’ll go out with my friends in the park. Otherwise, I’ll stay home with a cup of hot tea and watch TV. If tomorrow it isn’t too hot, […]

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Using Machine Learning and Natural Language Processing Tools for Text Analysis

This is a third article on the topic of guided projects feedback analysis. The main idea of the topic is to analyse the responses learners are receiving on the forum page. Dataquest encourages its learners to publish their guided projects on their forum, after publishing other learners or staff members can share their opinion of […]

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Tutorial: Reset Index in Pandas

In this tutorial, we’ll discuss the reset_index() pandas method, why we may need to reset the index of a DataFrame in pandas, and how we can apply and tune this method. We’ll also consider a small use case of resetting the DataFrame index after dropping missing values. To practice DataFrame index resetting, we’ll use a […]

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Tutorial: Filtering Pandas DataFrames

The Pandas library is a fast, powerful, and easy-to-use tool for working with data. It helps us cleanse, explore, analyze, and visualize data by providing game-changing capabilities. Having data as a Pandas DataFrame allows us to slice and dice data in various ways and filter the DataFrame’s rows effortlessly. This tutorial will go over the […]

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Tutorial: Connect, Install, and Query PostgreSQL in Python

Databases are everywhere — in your phone, on your computer, and behind your beloved applications. But what’s a database worth if you can’t query data from it? In this article, we’ll show you examples of querying any PostgreSQL-based database from your Python code. First, you’ll gain a high-level understanding of PostgreSQL and database connectors. Later […]

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Tutorial: How to Use the Apply Method in Pandas

The apply() method is one of the most common methods of data preprocessing. It simplifies applying a function on each element in a pandas Series and each row or column in a pandas DataFrame. In this tutorial, we’ll learn how to use the apply() method in pandas — you’ll need to know the fundamentals of […]

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Tutorial: Indexing DataFrames in Pandas

In this tutorial, we are going to discuss what indexing pandas dataframes means, why we need it, what kinds of dataframe indexing exist, and what syntax should be used for selecting different subsets. What is Indexing Dataframes in Pandas? Indexing a pandas dataframe means selecting particular subsets of data (such as rows, columns, individual cells) […]

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