7 simple hacks to speed up your data analysis in Python

data analytics certification course

Python is a high-level programming language with a built-in data structure with dynamic typing and data binding. It is general-purpose and straightforward to use the language used to create various computer programs. At Imarticus, we help you learn Python online through the PGA program.

Python creates various programs like developing websites, task automation, software, data analysis, and data visualization. Python is an easy-to-learn language; it is shared between accountants and scientists. It is also used to organize finance and numerous other day-to-day chores.

Python and data science go hand in hand with each other. The data analysts use this language to conduct complex statistical calculations, create data visualization, manipulate and analyze data. Python in web development is pervasive; it includes sending and receiving data processing data while communicating with the database. It also helps in the routing of URLs and ensuring security. 

Python is a dynamic language supporting structured and object-oriented programming. It is the language that focuses on readability, and it is the most accessible language that is why it attracts developers and thereby has a large developer community. 

Python helps in data analysis through the following steps:

  • Python helps to efficiently perform high computational tasks with libraries like Pandas and Numpy.
  • Libraries like beautiful soup and scraps help extract data from the net.
  • Python libraries like Matplotlib and Seaborn help in the analysis of pictographic representation and visualization of data.
  • The Scikit-learn library in Python makes complex mathematical calculations efficient and straightforward.
  • Python library such as OpenCV handles the operations on the image. 

Data Analysis With Tableau

With the PGA course at Imarticus, we help you learn Tableau, data visualization, and data analytics. This course will help you build interactive dashboards and publish them on online Tableau. 

Data analytics is the presentation of data with a blend of colors, dimensions, and labels to create a visualization for providing insight into business and making informed decisions. It is an unavoidable aspect of business analytics as it helps enterprises analyze trends and make decisions quickly and visually. For this visualization and data discovery, you need the Tableau tool.

For business intelligence and data visualization, you need Tableau as it is easy to learn, fast to use, and intuitive for consumer use. 

Data Analysis Using SQL

SQL is the database querying language that helps simultaneously interact with multiple people's databases. One of the most flexible languages combines a learning curve with a complex depth to help users create tools and dashboards for data analytics.

SQL is famous for quick creation and interaction with the database, and it is also a simple language performing complex data analysis. This language uses many valuable tools such as excel popular python libraries like pandas combined with its internal logic to interact with the data sets. 

So, what are the ways to use SQL for data analytics? SQL uses its base infrastructure and easy-to-use dashboards and reporting tools for communication with complex instructions and fast manipulation of data. One of the other interesting properties of SQL is simple accessibility, strategic organization, and simple, manageable, and understandable interaction. 

Through the PGA program at Imarticus, we help you unfold many uses of SQL in data analytics, such as direct integration into other frameworks, additional functionality, and the ability to communicate effectively. SQL is the tool that acts as an intermediary between the usage and storage of complex data and the end-users, and for using this tool, you need to know Python.

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