The following are some of the top reasons why learning about NumPy will help you going forward:
● Operation speed
You might not know about this, but NumPy is written in one of the oldest programming languages, C. One of the properties you benefit from is that it can execute faster than other packages. This makes a lot of sense when you think about Python as a whole being a dynamic language that...
Friday, November 29, 2019
Thursday, November 28, 2019
NumPy - Slicing and Indexing
By now I expect that you are familiar with slicing standard Python lists. The same knowledge applies when slicing one-dimensional NumPy arrays. You will also learn how to flatten arrays. Flattening arrays simply means converting a multidimensional array into a one-dimensional array.
The ravel() function can manipulate the shape of an array as follows:
Input
b
Output
array([[[ 0, 1, 2, 3],
[ 4,...
Wednesday, November 27, 2019
NumPy - Generating Arrays
There are different ways of creating arrays. The examples in the previous illustrate the simplest, by creating a sequence or a list in the form of an argument with the array() function. Below is an example:
>>> x = np.array([[5, 7, 9],[6, 8, 10]])
>>> x
array([[5, 7, 9],[6, 8, 10]])
Other than the lists created, you can also create one or more tuples in the same manner as shown...
Tuesday, November 26, 2019
NumPy - Statistics in Python
For data analysis, your understanding of NumPy will help in scientific computation. Knowledge of this library is a fundamental step in data analysis mastery. Once you understand NumPy, you can then build on to other libraries like Pandas.
Once you learn the basics of NumPy, you can then advance into data analytics, using linear algebra and other statistical approaches to analyze data. These are...
Monday, November 25, 2019
Python Libraries for Data Analysis
The standout reason why Python is quite popular is the large endowment of libraries. Each library is unique, yet extensive enough to enable programmers to solve many data problems every day. The following are some of the top libraries used in data science:
● NumPy
For numerical computations, you need Numerical Python (NumPy). NumPy is considered the foundation of numerical computations in Python....
Saturday, November 23, 2019
Shortcomings of Analyzing Data in Python
Given all the buzz about data and data analysis, it might come as a surprise to a lot of people, but data analysis does have unique challenges that are impeding the expected deliverables. One of the biggest challenges that data analysts have to work through is the fact that most of the data they rely on are user-level based.
Because of this reason, there is room for a lot of errors which eventually...
Friday, November 22, 2019
Data Analysis in Python over Excel
For most analysts, you start with Excel then advance into Python and other languages. In the business world, Microsoft Excel is one of the most important programs, especially when it comes to collecting data. You can use it for data analysis, but there are challenges you might experience, which necessitates the move to Python programming for data analysis.
While Excel is a great tool, it has some...
Wednesday, November 20, 2019
Tools Used in Data Analysis
There are several tools you need to learn about to help you in your career as a data analyst. At the basic level, you should at least have a working knowledge of web development, SQL, math, and Microsoft Excel. It also follows that you should be good at PHP, HTML, JavaScript, and know how to work with basic programming commands, libraries, and syntaxes. As an advanced user, you should also be adept...
Tuesday, November 19, 2019
Types of Data Analysis
Different terminologies are used in data analytics depending on the type of analytics. There is so much data that can be extracted from different sources today. Understanding raw data is quite a challenge given the unpredictable nature of some forms of data. This is where data analysis comes in. Analysis deals with refining raw data into an understandable and actionable form. Here are some of the...
Monday, November 18, 2019
Methods Used in Data Analysis
Data analysts are exposed to lots of data from time to time. The challenge is sifting through voluminous data to interpret the ramifications. There are several tools and methods that are used, especially in statistical data analysis.
In a world where big data is coming full circle, there are several tools that can help you reduce your workload, while at the same time improving...
Data Analysis Procedure
The data analysis methods discussed in the previous post might be different in their approaches, but the end result is almost always the same. Their core objective is to support decision-making in the organization at different levels. The following are some of the steps that you will follow during data analysis:
● Define the objectives
The objectives behind your study must be clearly outlined....
Saturday, November 16, 2019
Techniques Used in Data Analysis
Here is an overview of some of the techniques you will come across in data analysis:
● Data visualization
Data visualization is about presentation. You are already aware of most of the tools that are used in data visualizations, such as pivot tables, pie charts, and other statistical tools. Other than resentability, data visualization makes large sets of data easy to understand. Instead of reading...
Python in Healthcare
Python has attracted users from different platforms for its advantages in rapid application development and its dynamic building options. Little did we know that it is considered to be one of the “safest” programming languages too apart from all the popularity because of its functionality. Also, Python plays an important role in the healthcare sector.
Although it is tough for a normal person...
Thursday, November 14, 2019
Meteoric rise of data science
Marked as one of the highest paying jobby Glassdoor, the field of Data science has witnessed an immense growth in recent years. Employers are in the search of data scientists more than ever. A report by Indeed indicated a 29% increase in the demand of data scientists in a year. However, the increase in people skilled in data science grew at a slower pace which observed a rise by 14% only. The gap...
Wednesday, November 13, 2019
Data science and its future
Data science refers to the activity of analyzing a large amount of data in order to extract knowledge and insight leading to actionable decisions.
Now you might ask what kind of knowledge, insight, and actionable decision are we talking about?
To orient the conversation, let's reduce the scope to three fields of data science:
• Descriptive analytics: Data science is associated with information...
Hacking with Python
By now you have a basic idea of how Python works and how programs were created using this programming language. Now, you are ready to learn how you can use Python scripts to compromise websites, networks, and more.
Learning how to hack entails being able to setup the right environment that you can...