In marketing and business analytics, if you want to jump-start your career then knowing how to manipulate and analyze large datasets using python is a necessary skill set . Python tops the chart for the best career option for software engineers. And why not? Career opportunities in python are growing manifold across the globe.
Some of the reasons why Python is popular today:
1. Python is a High-level language.
2. Python is easy to learn.
3. Python is used to build server-side applications.
4. Python is an open source platform.
5. Python is Object Oriented Programming language.
Needless to say, learning Python has numerous benefits. Even it has been used by numerous big companies like Instagram, IBM, Google, Yahoo, and a few others to name. Since a lot of multinational companies are using python, there is no dearth of big opportunities for Python experts.
Have a look at various profile options you can proceed with after learning this amazing language:
There are plenty of platforms out there offering online guides and tutorial on Python, Strata Scratch is one name that is getting popularity for offering the best online Python Tutorials.
Top 5 Guides of Strata Scratch:
1. How to Clean Data with Pandas
In order to have glitch free data, the need arises to clean the ambiguous or fix missing data. So the need arises to clean the data using Pandas (pandas is an open source licensed library with easy to use data analysis tools for Python programming language.)
This tutorial introduces you to functions that will help you fill in missing values, remove null values. By the end of this tutorial, you should be able to learn how to drop unnecessary values and clean your dataset.
2. Functions, Lambda Functions, Loops, and List Comprehensions
In data analytics, there is a strong need to perform advanced operations on data such as reading lists, deleting vowels from the list and many others. Lambda functions are used to create a list.
In this tutorial, you learn about python comprehension using lambda or python loop functions.
3. Exploring Your Data
The essential part of data analytics is to explore data. It allows us to extract insights from data. Exploratory Data Analysis (EDA) using Python is very important for data modeling and getting insights from a large set of data
This tutorial teaches you an exploratory data analysis using techniques like histograms, boxplots and scatter plots.
4. Combining Data for Analysis (Joining/ Merging Dataframes)
Concatenation is very helpful in computer programming. In business analytics, most of the times need arises to make a single file from multiple files and spreadsheets. Python offers us very powerful tools to get this job easily done.
In this strata scratch tutorial, you learn how to concatenate or merge data frames with the help of various exercises.
Hope you enjoyed working on these practice exercises and learned different basics and advanced Python Queries. Wish you best of luck for your future. Stay connected with us for more challenging Practice sheets. Don’t forget to give your valuable feedback and comments for further improvements.