In this tutorial, we are covering the Pandas functions loc() and iloc() which are used for data selection operations on dataframes. By using the loc() function, we access a group of rows and/or columns based on their respective labels, whereas the iloc() function is an integer-location-based way to access these groups. Getting values with the … Read more
A box plot is a method used in statistics to graphically show a group, or groups, of numerical data with their quartiles identified. A box plot is often also called a box-and-whisker plot, as the plot may have lines extending from the box to show data outside the upper and lower quartiles. In this article, … Read more
The Pandas DataFrame filter() Method In this tutorial, we will have a look at the Pandas filter() method. We will see what this function does and how we can apply it to our dataframes. As the name suggests, the filter() method filters our dataframe. To be more specific, the method subsets the rows or columns … Read more
In this tutorial, we will see what the Pandas groupby() method is and how we can use it on our datasets. Described in one sentence, the groupby() method is used to group our data and execute a function on the determined groups. It is especially useful to group a large amount of data and to … Read more
Problem Formulation The extreme location of a function is the value x at which the value of the function is the largest or smallest over a given interval or the entire interpretation range. There is a local maximum of f(x) in x0 if there is an environment such that for any x in this environment … Read more
A bootstrap plot is a graphical representation of uncertainty in a characteristic chosen from within a population. While we can usually calculate data confidence levels mathematically, gaining access to the desired characteristics from some populations is impossible or impracticable. In this case, bootstrap sampling and the bootstrap plot come to our aid. This article will … Read more
In this final installment of my series on Newspaper3k, we will see the real possibilities of what we can do after scraping massive amounts of news articles. To demonstrate data will be collected from 3 popular American news websites for a full year, from September of 2020 to August of 2021. We will analyze articles … Read more
You can check out the code in this article in the interactive Jupyter notebook here (Google Colab). Introduction A popular query in Google is about load-duration curves. Some of the questions are: What is a load-duration curve? What is the importance of a load-duration curve? How do you calculate a load-duration curve? What is the … Read more
A Bollinger Band consists of three lines: a simple moving average, an upper band, and a lower band. The assumption is that if the real price crosses over one of the bands, this can be seen as a signal to trade in or our of a given asset. For cryptocurrencies, breakout trades are more frequently … Read more
We hear more and more about natural language processing. In today’s world, the amount of text content produced is growing exponentially. In order to process a text with a machine learning model, it is important to find certain information and numerical features about the text. What Are N-Grams? N-Grams are one of the tools to … Read more
Syntax numpy.all(a, axis=None, out=None, keepdims=<no value>, *, where=<no value>) Argument Type Description a array_like Input array axis None, int, or tuple of int Optional. One axis or multiple axes along which logical AND should be performed. Per default, it computes logical AND on the flat array. If this is a tuple of integers, calculates logical … Read more
Can you spot the outliers in the following sequence: 000000001000000001? Detecting outliers fast can be mission critical for many applications in military, air transport, and energy production. This article shows you the most basic outlier detection algorithm: if an observed value deviates from the mean by more than the standard deviation, it is considered an … Read more