Series is a one-dimensional, labelled data structure present in the Pandas library. The axis label is collectively known as index.Series structure can store any type of data such as integer, float, string, python objects, and so on. It can be created using an array, a dictionary or a constant value.Let us see how an empty series can be created in Python −Example Live Demoimport pandas as pd my_series = pd.Series() print("This is an empty series data structure") print(my_series)OutputThis is an empty series data structure Series([], dtype: float64)ExplanationIn the above code, ‘pandas’ library is imported and given an alias name as ‘pd’.Next, ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high level interface. In real-time situations, dataset contains many variables. Sometimes, it may be required to analyse the relationship of every variable with every other variable in the dataset. In such situations, bivariate distribution may take up too much time and may get complicated as well.This is where multiple pairwise bivariate distribution comes into picture. The ‘pairplot’ function can be used to get the relationship between combinations of variables in a dataframe. The output would be a univariate plot.Syntax of pairplot functionseaborn.pairplot(data, …)Now let ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high level interface.Kernel Density Estimation, also known as KDE is a method in which the probability density function of a continuous random variable can be estimated. This method is used for the analysis of the non-parametric values. While using ‘jointplot’, if the argument ‘kind’ is set to ‘kde’, it plots the kernel density estimation plot.Let us understand how the ‘jointplot’ function works to plot a kernel density estimation in python.Exampleimport pandas as pd import seaborn as sb from matplotlib import pyplot as plt my_df ... Read More

Scikit-learn, commonly known as sklearn is a library in Python that is used for the purpose of implementing machine learning algorithms.Conversion of an image from one color space to another is usually used so that the newly achieved color space can prove as a better input to perform other operations on it. This includes separating hues, luminosity, saturation levels, and so on. When an image is represented using RGB representation, the hue and luminosity attributes are shown as a linear combination of channels R, G and B.When an image with RGB color space is tried to be converted to grayscale, ... Read More

Conversion of an image from one color space to another is usually used so that the newly achieved color space can prove as a better input to perform other operations on it. This includes separating hues, luminosity, saturation levels, and so on.When an image is represented using RGB representation, the hue and luminosity attributes are shown as a linear combination of channels R, G and B.When an image is representing using HSV representation (here, H represents Hue and V represents Value), RGB is considered as a single channel.Here’s the example to convert RGB color space to HSV −Exampleimport matplotlib.pyplot as ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high level interface. This interface helps in customizing and controlling the kind of data and how it behaves when certain filters are applied to it.Hexagonal binning can be used in the analysis of bivariate data. This occurs when the data is sparse, i.e. when the data is scattered unevenly. When the data is scattered unevenly, it gets difficult to capture all the data points in a scatterplot.This is where hexagonal binning comes into play. Let us understand how seaborn library can be used to ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high level interface.The barplot function establishes the relationship between a categorical variable and a continuous variable. Data is represented in the form of rectangular bars where the length of the bar indicates the proportion of data in that specific category.Point plots are similar to bar plots but instead of representing the fill bar, the estimated value of the data point is represented by a point at a specific height on the other axis.Categorical data can be visualized using categorical scatter plots or two separate ... Read More

Seaborn is a library that helps in visualizing data. This interface helps in customizing and controlling the kind of data and how it behaves when certain filters are applied to it.With the help of bar plots, we can understand the central tendency of the distribution of data. The barplot function establishes the relationship between a categorical variable and a continuous variable.Data is represented in the form of rectangular bars where the length of the bar indicates the proportion of data in that specific category.Point plots are similar to bar plots but instead of representing the fill bar, the estimated value ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high-level interface.In previous plots, we plotted the entire dataset on the graph. With the help of bar plots, we can understand the central tendency of the distribution of data.The barplot function establishes the relationship between a categorical variable and a continuous variable. Data is represented in the form of rectangular bars where the length of the bar indicates the proportion of data in that specific category.A special case of barplot is the countplot that shows the number of observations in every category with respect ... Read More

Seaborn is a library that helps in visualizing data. It comes with customized themes and a high level interface.In previous plots, we plotted the entire dataset on the graph. With the help of bar plots, we can understand the central tendency of the distribution of data.The barplot function establishes the relationship between a categorical variable and a continuous variable. Data is represented in the form of rectangular bars where the length of the bar indicates the proportion of data in that specific category.Let us understand bar plots with the help of ‘titanic’ dataset −Exampleimport pandas as pd import seaborn as ... Read More