You must have obtained the fundamental concept of SQL and databases along with some elementary queries from SQL for data scientists: Part 1. This is 2nd part of the series where we are discussing the importance of SQL for Data Scientists and how we can utilize it for our project’s data requirement.
ORDER BY is used to sort the results of a SQL query in ascending or descending order based on one or more columns.
We will consider below table for illustration purpose:
Table1: Illustration table(world)
In the table, each row is representing an area, population and GDP of a country along with the continent it belongs to, and the table name’s is the world.
If the column which we want to sort is having numerical data, then ORDER BY sorts it on the basis of its value whereas if the data is not numerical then it sorts on alphabetical order.
By default, ORDER BY sorts in ascending order and if the requirement is to sort in descending we would have to include DESC in the query. For example, if we want to sort the world table from lowest gdp to highest, we can achieve this with the below query:
Order by query
The query is simple and we need to include ORDER BY at the end with the column on which we want the data to be sorted by. By default, ORDER BY sorts in ascending order so the lowest gdp country will be at the top. Below is the snippet of the output of the above query:
Table 2: Output table by applying order by query
From table 2, Tuvalu is the country with the least gdp.
Now, what will be the query if we want to sort world table with highest gdp country at the top that is in descending order? We simply need to add DESC clause along with order by in the above query so that the world table gets sorted in descending order of gdp. Below is the query and output:
Applying order by query in descending order
Table 3: Output table after an order by query in descending order
From table 3, the United States is the country with the highest GDP.
A subquery is a method in which we include a query inside a query to obtain the final requirement.
From above, we saw that the United States is the country with the highest GDP, what if the requirement is to get the country name from the world table with the highest GDP? One of the ways to achieve the above requirement is to use SUBQUERY, remember that, SUBQUERY is not a syntax like ORDER BY and LIMIT, it’s a method or way to write a final query to obtain the final data requirement. Below is the query:
The above query will return the United States as we have selected name where gdp is equal to maximum gdp present in the world table. Now, the question is where did we use SUBQUERY? It is nowhere to be seen in the above query.
(select max(gdp) from world) is the SUBQUERY because this is a query in itself as it will return the maximum gdp value from world table but in the overall query it is being used as a filter medium in the WHERE clause to get the name (country), that is why it is called SUBQUERY of the final QUERY.
IF is used to create a new column based on some conditions on one or more columns (features).
Let’s say, you want to categorize population of a country like High and Low Population where you call a country high population country if its population is greater than 20M and low, otherwise. So, basically, you have a created a condition on population column. This categorization can be achieved by the below query and output:
Table 4: Output table after applying "if query"
The flow of if query execution works like if population>20000000 then High else Low, at first place after IF clause, we write if the condition is True and at the second place we write if the condition is False same as if population>20M then High else Low.
CASE WHEN is similar to IF but it is handy when we have to create multiple categories based on conditions on one or more columns.
Let’s say we have to create population categories High, Medium and Low, then if you look at IF syntax, we don’t have space to include Medium in the same query because it can accommodate only two parameters in a single IF statement.
Although, we can include one more IF clause inside this IF to accommodate Medium category which is also called Nested IF (IF clause inside an IF clause), but it will increase the complexity of the query and it will be a very inefficient way to write code when the number of categories will be more. When the number of categories is more than two then CASE WHEN should be preferred over IF.
Let’s say the new requirement is we will call a country Low population when it’s population<20M, Medium when itis between 20M and 40M (both inclusive) and High when>40M. Below is the query and required result:
Deploying Case when query
Table 5: output table when “Case when” is applied
We are able to include multiple categories and query is also easy to read and understand. CASE WHEN works like when some condition is True THEN it will return a particular value, if some other condition is True THEN it will return some other value and finally, it should be closed by END to inform the query that we don’t need more categories.
It can be easily scaled to include more categories, let’s say you have to include Very High category, then easily one more WHEN statement can be included in the same query without increasing the complexity of the existing query (Reference). Below is the example code:
Case when and when query
SQL, A query language, or a sort of programming language designed to expedites the information retrieval from the databases in particulars with requirements. You have learned how and when “order by query” and “subquery” are being implemented. It is also discussed when to apply “if and case when” statement through the example of a table illustrated.
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
6 Major Branches of Artificial Intelligence (AI)READ MORE
Top 10 Big Data TechnologiesREAD MORE
Introduction to Time Series Analysis: Time-Series Forecasting Machine learning Methods & ModelsREAD MORE
What is the OpenAI GPT-3?READ MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE
7 Types of Activation Functions in Neural NetworkREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE