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Python tuples store data in the form of individual elements. The order of these elements is fixed i.e (1, 2, 3) will remain in the same order of 1, 2, 3 always. In this article, we are going to see how to invert python tuple elements or in simple terms how to reverse the order of the elements. Let us 1st see a sample input and output − Input (5, 6, 7, 8) Output (8, 7, 6, 5) Let us now explore the various ways to invert tuple elements. Method 1: Using Tuple Slicing Slicing is ... Read More
The Hermite series is one of the mathematical techniques, which is used to represent the infinite series of Hermite polynomials. The Hermite polynomials referred as the sequence of orthogonal polynomials which are the solutions of the Hermite differential equation. Dividing one hermite series by another The Hermite series is given by the following equation. f(x) = Σn=0^∞ cn Hn(x) Where Hn(x) is the nth Hermite polynomial cn is the nth coefficient in the expansion. The coefficient cn can be determined by using the below formula: cn = (1/$\mathrm{\surd}$(2^n n!))$\mathrm{\lmoustache}$ f(x) Hn(x) e^(−x^2/2) dx Example ... Read More
Given 2 separate lists, we are going to transform them into a single data structure by mapping them into a key-value data structure namely dictionary. The values of the 1st list will serve as keys and values from the 2nd list will serve as values of the corresponding keys in the dictionary. The relationship can be considered as 1 to 1 or 1 to many i.e. 1 key can have multiple values. Let us now see a sample input and output to better understand how we will be able convert Lists into Similar key value lists in Python in this ... Read More
Hermite_e series is also known as probabilist's Hermite polynomial or the physicist's Hermite polynomial the available in mathematics which is used to sum of the weighted hermites polynomials. In some particular cases of the quantum mechanics, the Hermite_e series the weight function is given as e^(−x^2). The following is the formula for Hermite_e series. H_n(x) = (-1)^n e^(x^2/2) d^n/dx^n(e^(-x^2/2)) Where, H_n(x) is the nth Hermite polynomial of degree n x is the independent variable d^n/dx^n denotes the nth derivative with respect to x. Defining the coefficients To perform differentiation of the Hermite_e series first we have ... Read More
A Band Reject filter is the filter which rejects or blocks all the frequencies within the range and passes the frequencies outside the range. The Butterworth is the type of a filter designed to filter the frequencies as flat as possible in the pass band. The following are the main features of the digital band reject butter worth filter. The sampling rate of the filter is about 12 kHz. The pass band edge frequencies are in the range of 2100 Hz to 4500 Hz. The stop band edge frequencies are within the range of 2700 Hz to 3900 ... Read More
The high pass filter is the electronic filter which passes the frequency of signals greater than the defined cutoff frequency and the frequency of the signals lower than the cutoff will be attenuated. The attenuation of each frequency is based on the filter design. The High pass Butterworth filter has some specialized features defined as follows. The sampling rate of the given input signal is given as 3.5 kHz The edge frequency of the pass band is 1050 Hz The edge frequency of the stop band is 600 Hz The ripple of the pass band is 1 dB The ... Read More
The low pass filter is the electronic filter which passes the frequency of signals lesser than the defined cutoff frequency and the frequency of the signals higher than the cutoff will be attenuated. The High pass Butterworth filter has some specialized features defined as follows. The sampling rate of the given input signal is given as 40 kHz The edge frequency of the pass band is 4 kHz The edge frequency of the stop band is 8 kHz The ripple of the pass band is 0.5 dB The minimum attenuation of the stop band is 40 dB and the ... Read More
We use the appearance property to style an element according to the platform-native style of the user’s operating system. Syntax The syntax of CSS appearance property is as follows − Selector { appearance: /*value*/; -webkit-appearance: /*value*/; /*for Safari and Chrome */ -moz-appearance: /*value*/; /*for Firefox */ } The following examples illustrate CSS appearance property − Hide Dropdown Arrow for Input Type Number In this example, we have shown how to hide the dropdown arrow for the . For that, we gave set the appearance property to none − ... Read More
Pandas library is used to manipulate the data and analyze the data. The data will be created using the pandas library in two ways Dataframe and Series. A DataFrame is the two dimensional data structure containing the rows and columns. There different ways to divide the DataFrame data based on the ratio. Let’s see them one by one. Using np.random.rand() Using pandas.DataFrame.sample() Using numpy.split() Using numpy.random.rand() In the following example, we will divide the dataframe data into parts by defining the ratio using the randm.rand() function. If we want to divide the data in the percentage of ... Read More
We can use the CSS overflow property to manage/handle the overflowing content of an element. This property allows user to clip content, provide scrollbars to view clipped content, render content outside the container thus the name overflow. Syntax The following is the syntax for CSS Overflow property − Selector { overflow: /*value*/ } The property values can be auto, hidden, clip, scroll, and auto. Let us see some examples to handle overflow content using the CSS overflow property − The Overflow Scroll Value In this example, we have set the overflow property to scroll. The ... Read More