{"id":249952,"date":"2023-03-03T08:32:46","date_gmt":"2023-03-03T08:32:46","guid":{"rendered":"https:\/\/imarticus.org\/?p=249952"},"modified":"2024-04-06T20:10:48","modified_gmt":"2024-04-06T20:10:48","slug":"the-role-of-python-sql-and-r-in-data-analysis","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/the-role-of-python-sql-and-r-in-data-analysis\/","title":{"rendered":"The Role of Python, SQL and R in Data Analysis"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">A <\/span><strong><a href=\"https:\/\/imarticus.org\/postgraduate-program-in-data-science-analytics\/\">career in data science<\/a><\/strong><span style=\"font-weight: 400;\"> requires in-depth knowledge of various software tools and programming languages. Languages like R, Python and SQL offer massive advantages that one can use for efficiently conducting data analysis.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This article will discuss in detail the role each language carries while we delve into the advantages of a data science programme. For instance, the programmer can utilise R and SQL for complex queries and tables while conducting fundamental statistics. On the other hand, one can easily use <\/span><span style=\"font-weight: 400;\">Python objects<\/span><span style=\"font-weight: 400;\"> to create and automate tasks while working on various data sets.\u00a0<\/span><\/p>\n<h2><strong>Python in Data Analysis\u00a0<\/strong><\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-243048 size-medium\" src=\"https:\/\/imarticus.org\/blog\/wp-content\/uploads\/2020\/09\/shutterstock_718643389-300x200.jpg\" alt=\"become a Data Analyst\" width=\"300\" height=\"200\" srcset=\"https:\/\/imarticus.org\/blog\/wp-content\/uploads\/2020\/09\/shutterstock_718643389-300x200.jpg 300w, https:\/\/imarticus.org\/blog\/wp-content\/uploads\/2020\/09\/shutterstock_718643389-768x512.jpg 768w, https:\/\/imarticus.org\/blog\/wp-content\/uploads\/2020\/09\/shutterstock_718643389-900x600.jpg 900w, https:\/\/imarticus.org\/blog\/wp-content\/uploads\/2020\/09\/shutterstock_718643389.jpg 1000w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Python is a powerful tool in data analysis as it provides a colossal library count that can be used for <strong><a href=\"https:\/\/imarticus.org\/blog\/how-to-become-an-expert-in-data-visualisation\/\">data visualisation<\/a><\/strong> and manipulation.<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\n<h3><strong>A. Advantages of Python in Data Analysis\u00a0<\/strong><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Easy Programming Language:<\/b><span style=\"font-weight: 400;\"> Data analysis is a large venture requiring a lot of work with every task. With <\/span><span style=\"font-weight: 400;\">Python objects<\/span><span style=\"font-weight: 400;\">, syntax and code can be written straightforwardly.<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Extensive Library Count:<\/b><span style=\"font-weight: 400;\"><span style=\"font-weight: 400;\"> Python&#8217;s standard library allows for complex data analysis tasks like data manipulation, statistics, and data visualisation to be done with ease.<\/span><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Open-source Feature:<\/b><span style=\"font-weight: 400;\"><span style=\"font-weight: 400;\"> Since Python can be modified, it is free for users to access and write, making it the ideal choice for different data analysis projects.<\/span><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Community Support:<\/b><span style=\"font-weight: 400;\"> Python boasts a large group of developers available anytime to answer and help each other with queries.<\/span><\/li>\n<\/ul>\n<h3><strong>B. Popular Libraries and Frameworks Used in Data Analysis<\/strong><\/h3>\n<p><span style=\"font-weight: 400;\">Python utilises many <strong><a href=\"https:\/\/imarticus.org\/blog\/python-libraries-that-are-hidden-gems-in-data-science\/\">libraries<\/a> <\/strong>like TensorFlow and Scikit-learn to exercise <\/span><span style=\"font-weight: 400;\">machine learning <\/span><span style=\"font-weight: 400;\">algorithms. Other libraries and frameworks include Keras, Pandas, PyTorch and Matplotlib.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Pandas uses the &#8216;<\/span><b>sort_values<\/b><span style=\"font-weight: 400;\">&#8216; function to make way for the action. In this example, we can see the popular instance of listing items and their prices arranged in descending order in store 1. The prerequisite \u2018Pandas\u2019 from the Python library has been used for this particular action.<\/span><\/p>\n<p><b>items[items.store_id == 1][[&#8216;description&#8217;,&#8217;price&#8217;]]\\<\/b><\/p>\n<p><b>.sort_values(by=&#8217;price&#8217;, ascending=False)<\/b><\/p>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\"><strong>Store ID<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\"><strong>Description<\/strong><\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\"><strong>Price<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">zucchini<\/td>\n<td style=\"text-align: center;\" width=\"151\">7.45<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">1<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">orange<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.45<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">3<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">pear<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.45<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">1<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">butter<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.40<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">onion<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.35<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"123\">1<\/td>\n<td style=\"text-align: center;\" width=\"151\">celery<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">0.75<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h2><strong>SQL in Data Analysis\u00a0<\/strong><\/h2>\n<h3><strong>A. Advantages of SQL in Data Analysis\u00a0<\/strong><\/h3>\n<p><span style=\"font-weight: 400;\">SQL&#8217;s performance is commendable as it can be used to query and manipulate the data present in the database. SQL can also create numerous reports and dashboards for visualising data.\u00a0<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>High Performance:<\/b><span style=\"font-weight: 400;\"> SQL is widely known for its efficient form that aids in offering faster results than other programming languages.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Secure Database:<\/b><span style=\"font-weight: 400;\"> SQL&#8217;s most relevant feature is high security for storing and retrieving data which can be used against unauthorised access and malicious attacks.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Scalability:<\/b><span style=\"font-weight: 400;\"> SQL is known for holding a substantial amount of databases that can store more data over time.<\/span><\/li>\n<\/ul>\n<h3><strong>B. Popular SQL Programming Database Management Systems Used in Data Analysis<\/strong><\/h3>\n<p><span style=\"font-weight: 400;\">SQL utilised a range of DMS systems for analysing data effectively. These include MySQL, PostgreSQL, MSSQL, MariaDB and Oracle.<\/span><\/p>\n<p><strong>This list shows how MySQL has been implemented for acting:<\/strong><\/p>\n<p><b>mysql&gt; SELECT DESCRIPTION, PRICE<\/b><\/p>\n<p><b>\u00a0\u00a0\u00a0\u00a0-&gt; FROM ITEMS<\/b><\/p>\n<p><b>\u00a0\u00a0\u00a0\u00a0-&gt; WHERE STORE_ID = 1<\/b><\/p>\n<p><b>\u00a0\u00a0\u00a0\u00a0-&gt; ORDER BY PRICE DESC;<\/b><\/p>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"151\">\n<p style=\"text-align: center;\"><strong>Description<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\"><strong>Price<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"151\">\n<p style=\"text-align: center;\">zucchini<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">7.45<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"151\">orange<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.45<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"151\">\n<p style=\"text-align: center;\">pear<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">1.45<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"151\">butter<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.40<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"151\">onion<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.35<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"151\">\n<p style=\"text-align: center;\">celery<\/p>\n<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">0.75<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h2><strong>R in Data Analysis\u00a0<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">R is an essential language for data analysts as it helps create robust data structures and visualisations.<\/span><\/p>\n<h3><strong>A. Advantages of R in Data Analysis\u00a0<\/strong><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Cost-effective Features:<\/b><span style=\"font-weight: 400;\"> R&#8217;s libraries and frameworks are open-source and free to use, making them an excellent option for greater accessibility in data analysis.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>User-friendly Visualisation Tools:<\/b><span style=\"font-weight: 400;\"> R comprises various user-friendly visualisation tools that rapidly form graphs and charts.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Flexibility:<\/b><span style=\"font-weight: 400;\"> R&#8217;s vivid tools can analyse many data types \u2014 text, audio and images.<\/span><\/li>\n<\/ul>\n<h3><strong>B. Popular R Libraries and Packages Used in Data Analysis<\/strong><\/h3>\n<p><span style=\"font-weight: 400;\">The most common and widely used R frameworks for analysing data include dplyr, tidyr, Shiny, plotly, XGBoost and data.table.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this example, you can see the data.table format:<\/span><\/p>\n<p><b>&gt; items[store_id == 1, .(description, price)][order(-price)]<\/b><\/p>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\"><strong>Store ID<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\"><strong>Description<\/strong><\/td>\n<td style=\"text-align: center;\" width=\"151\"><strong>Price<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">1<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">zucchini<\/td>\n<td style=\"text-align: center;\" width=\"151\">7.45<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"123\">2<\/td>\n<td style=\"text-align: center;\" width=\"151\">orange<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.45<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">3<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"151\">pear<\/td>\n<td style=\"text-align: center;\" width=\"151\">1.45<\/td>\n<\/tr>\n<tr>\n<td width=\"123\">\n<p style=\"text-align: center;\">4<\/p>\n<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">butter<\/p>\n<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.40<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"123\">5<\/td>\n<td style=\"text-align: center;\" width=\"151\">onion<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">1.35<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"123\">6<\/td>\n<td style=\"text-align: center;\" width=\"151\">celery<\/td>\n<td width=\"151\">\n<p style=\"text-align: center;\">0.75<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p><strong>Conclusion\u00a0<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">All three languages mentioned above have a substantial role in data analysis as they offer numerous functions for managing and manipulating data effectively. While R is a powerful statistical language, <\/span><span style=\"font-weight: 400;\">SQL programming<\/span><span style=\"font-weight: 400;\"> is a database query for storing databases. Furthermore, Python&#8217;s general-purpose language can be accessed for <\/span><span style=\"font-weight: 400;\">machine learning<\/span><span style=\"font-weight: 400;\"> purposes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A <\/span><a href=\"https:\/\/imarticus.org\/postgraduate-program-in-data-science-analytics\/\"><strong>career in data science<\/strong><\/a><span style=\"font-weight: 400;\"> can be gratifying, especially when using your technical skill sets. It can be especially beneficial while forming simple descriptive statistics or creating complex <\/span><span style=\"font-weight: 400;\">machine learning<\/span><span style=\"font-weight: 400;\"> models. Opt for Imarticus\u2019s <\/span><span style=\"font-weight: 400;\">Post graduate program in Data Science and Analytics<\/span><span style=\"font-weight: 400;\"> while you work on amplifying your resume.\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A career in data science requires in-depth knowledge of various software tools and programming languages. Languages like R, Python and SQL offer massive advantages that one can use for efficiently conducting data analysis.\u00a0 This article will discuss in detail the role each language carries while we delve into the advantages of a data science programme. 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