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Introduction to Numpy and Matplotlib in Python

Using Numpy and Matplotlib for data visualization in Python

Numpy and matplotlib.

Of late, Python has risen to become one of the most preferred programming languages by most aspirants of data scientist positions. In terms, of speed, Python is much slower than C or C++. But the real reason why most people prefer to use Python is for it’s a high-level language that is more simplified. In fact, it's much easier to learn Python.

Python, as a data analysis tool, has lots of packages that could serve you well. But there are two basic packages that you will often use. These are NumPy and matplotlib. After learning these two, you can proceed to learn other packages. This article only gently nudges you into using the two packages. From there, it will take your effort, passion, and determination to learn how to use these packages fully. At all times, our online NumPy and matplotlib tutors provide you with instant help whenever you experience any challenges.


Numpy, as we can infer from its name, is made of two words numerical for num and py for Python. Therefore, it's a numerical package. A special feature of NumPy is that it works with arrays. All mathematical expressions and logical expressions can only be performed on an array. The NumPy array is a one-dimensional object containing rows and columns. The beauty is that you can convert lists and pandas data frames to NumPy array where you can do manipulation such as accessing certain elements of the array, removing some elements, or even copying the array. You can also perform some complicated tasks such as regression

NumPy installation.

Numpy does not come preinstalled with your Python. To use it you have to install it. One way could be through the command prompt or through an anaconda. To install NumPy through the command prompt, open the command prompt. On your terminal, type pip installs NumPy and hit enter. The installation process will commence almost instantly after hitting enter. Using an anaconda, you can follow the same process, only that you have to type conda install NumPy at the anaconda terminal. To verify that NumPy is installed type python in the anaconda or command prompt and hit enter. Python will open from the terminal, type import NumPy and hit enter again. If it does not show any error such as import enter, it means that NumPy is installed. From there, you can proceed to explore the world of data analysis using NumPy.


Matplotlib is the visualization package in Python. In most cases, you will use it in plotting graphs. Visualization in data cannot be understated. Practically, there is no data analysis task that can be accomplished without visualization. Why? Because of the common saying a picture is worth more than words. Pictures can pass information that is hard to identify in a dataset. Let's take, for instance, you have the average monthly rainfall data recorded for the previous year. In the data, it's not easy to identify the month with the highest rainfall record. A sneak view of a plotted histogram can give you the month with the highest average rainfall.

Matplotlib was introduced by John D. Hunter. However, Michael Droettboom has been the principal developer since 2012. Learning matplotlib can be challenging. It requires a high level of organization and dedication if you want to go learn it. Documentation is there, but learning from the documents can be challenging. The library itself is huge, with over 60,000 lines of code. Additionally, you have to be cautious with the content that you are using. Some of them could be out of date because the package is always continually updated.

The most important function in Python is pyplot which is used for 2d plotting. It provides functionalities for plotting the basic plots such as scatter plots, line graphs, and histograms. Additionally, you can add annotations and colors using the function. It's normally imported by the line from matplotlib import pyplot.

Matplotlib installation.

If you have come to this end, you won't have any challenge of installing matplotlib. Simply follow the above procedure. The difference comes in the wordings. You will substitute pip install NumPy with pip install matplotlib and the text on anaconda with conda install -c conda-forge matplotlib.

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