In this article, we will be highlighting the top 10 discussions of the year that have garnered a lot of attention from learners at Data Science Dojo.
Every year Data Science Dojo serves a lot of students from different geographics and academic backgrounds with its detailed courses and informative sessions. All these students have one single goal; to be equipped with enough baseline understanding of data science that they can learn and become experts eventually on their own.
In order to expedite the process and make it more collaborative, we make use of different resources, and our discussion platform is one of the most effective ones.
1. Operators in query matching
Operators are an important aspect of query matching, as they allow users to specify the type of relationship, they are seeking between different search terms. The ‘LIKE’ operator is one of the most used ones and helps the user in separating out data with specific characteristics. This Q/A will help you understand the LIKE operator and will also provide you with a code runner to practice as well.
Check out the discussion here: Operators in query matching
2. Alias command
The alias command is an important tool for improving the efficiency and organization of command line workflows. It is widely used by system administrators, developers, and other users who work with the command line on a regular basis. This short snippet on Alias Command will give you a basic understanding of what Alias command can do and how it can help you improve the organization of your code.
Check out the discussion here: Alias command
3. Data wrangling in Python
Data wrangling, also known as data munging or data preparation, is the process of cleaning, organizing, and transforming raw data into a format that is more suitable for analysis and visualization.
This is a crucial step in the data science process, as it helps to ensure that the data is in a usable and accurate form before it is analyzed. If you are looking for the shortest crash course on data wrangling, this discussion is for you, and it comes with some very easy hands-on practice exercises as well.
Check out the discussion here: Data wrangling in Python
4. Clauses of SELECT query
The SELECT clause is a crucial part of the SQL language, as it is used to specify the columns or expressions that should be included in the results of a query. The SELECT clause is the first command that is taught to SQL students. If you want to take the first step towards learning SQL, this short article is the best way to take that first step.
Check out the discussion here: Clauses of SELECT query
5. JOIN and its different types
Now that you have learned SELECT, the JOIN is the next step. The JOIN clause is a key component of the SQL language, as it allows users to combine data from multiple tables in a single query.
The JOIN clause is a powerful tool for working with data in SQL, and a good understanding of its various clauses is essential for anyone working with data in a SQL database. But before you take on a SQL database, read our small but concise intro to the JOIN clause in this Q/A.
Check out the discussion here: JOIN and its different types
6. Lambda functions
Use our code runner in this discussion and create your first lambda function today.
Check out the discussion here: Lambda functions
Matplotlib is a powerful and widely used library for creating data visualizations in Python. The ability to effectively plot and visualize data is an important skill for any data scientist or analyst and knowing the fundamentals of plotting with matplotlib is essential for anyone working with data in Python.
If you are a Python beginner and want to use it to create effective visualizations, this Q/A can get you started right away.
Check out the discussion here: Matplotlib
A subquery is a query that is nested within another query, and it is used to retrieve data that is used in the outer query. If you are struggling with the idea of nesting and how you can use it more effectively, visit this discussion and get answers instantly.
Check out the discussion here: Sub-query
9. Break, continue, and pass
The break, continue, and pass statements are control flow statements. These are commonly used in programming languages such as Python, C, and Java.
The ability to use break, continue, and pass statements is an important skill for any programmer, as it allows them to control the flow of their code and implement the desired logic and behavior more effectively. If you want to start using the break, continue and pass statements in your code today but need to practice before you give it a go, this Q/A is for you.
Check out the discussion here: Break, continue, and pass
Window functions, also known as OVER functions, are a powerful tool in SQL that allow users to perform calculations or aggregations on a set of rows, rather than on the entire table.
The ability to use window functions is an important skill for anyone working with data in a SQL database and understanding their different types and uses can help users to more effectively and efficiently retrieve and manipulate data.
If these sound like the skills that you need, visit this discussion and start practicing right away.
Check out the discussion: Window functions
Learn from our discussion platform
These discussions cover a wide range of topics, but we make sure that these topics cover fundamentals so that they become the first step towards our students’ data science learning journey.
Whether you’re a beginner or a seasoned data scientist, these discussions will provide you with a better understanding of the fundamental concepts along with a bit of hands-on practice, thanks to our embedded code runner.