Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Python Articles
Page 785 of 855
Explain how a violin plot can be visualized using factorplot function in Python?
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 plots with the help of pointplot or a higher level function known as factorplot.The factorplot function draws a ...
Read MoreHow can RGB color space be converted to a different color space in Python?
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 MoreHow can Seaborn library be used to display a hexbin plot in Python?
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 MoreHow can bar plot be used in Seaborn library in Python?
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 MoreHow can box and whisker plot be used to compare the data in different categories in Python Seaborn?
Seaborn library helps in visualizing data. It comes with customized themes and a high level interface.Scatter plots provide limited information, since they only tell us about the distribution of values within a given category of data. We need to use a different technique if we wish to compare the data present within categories. This is where box plots come into play. It is a way in which the data distribution in the dataset can be understood with the help of quartiles.It consists of vertical lines that extend from the boxes. These extensions are known as whiskers. These whiskers talks about ...
Read MoreAvoid the points getting overlapped without using jitter parameter in categorical scatter plot in Python Seaborn?
We will be using Seaborn. 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.The ‘stripplot’ function is used when atleast one of the variables is categorical. The data is represented in a sorted manner along one of the axes. But the disadvantage is that certain points get overlapped. This where the ‘jitter’ parameter has to be used to avoid the overlapping between variables.It adds some random noise to the ...
Read MoreHow can seaborn library be used to display data without the background axis spines in Python?
Machine learning deals with creating models from data, and generalizing on never before seen data. The data provided to a machine learning model as input should be such that it should be understood by the system properly, so that it can interpret the data and produce results.Visualizing data is an important step since it helps understand what is going on in the data without actually looking at the numbers and performing complicated computations.This interface helps in customizing and controlling the kind of data and how it behaves when certain filters are applied to it. The ‘despine’ function can be used ...
Read MoreExplain how L2 Normalization can be implemented using scikit-learn library in Python?
The process of converting a range of values into standardized range of values is known as normalization. These values could be between -1 to +1 or 0 to 1. Data can be normalized with the help of subtraction and division as well.Let us understand how L2 normalization works. It is also known as ‘Least Squares’. This normalization modifies the data in such a way that the sum of the squares of the data remains as 1 in every row.Let us see how L2 normalization can be implemented using Scikit learn in Python −Exampleimport numpy as np from sklearn import preprocessing ...
Read MoreHow can non-linear data be fit to a model in Python?
We will be using the Seaborn library, that helps in visualizing data.When regression models are being built, multicollinearity is checked for. This is because we need to understand the correlation present between all different combinations of continuous variables. If multicollinearity exists between the variables, we have to make sure that it is removed from the data. The data in real world is usually non-linear.We need to find mechanisms to fit such non-linear data to the model. We will be using Anscombe’s dataset to visualize this data. The ‘implot’ function is used with this non-linear data.Here’s the example −Exampleimport pandas as ...
Read MoreExplain how L1 Normalization can be implemented using scikit-learn library in Python?
The process of converting a range of values into standardized range of values is known as normalization. These values could be between -1 to +1 or 0 to 1. Data can be normalized with the help of subtraction and division as well.Data fed to the learning algorithm as input should remain consistent and structured. All features of the input data should be on a single scale to effectively predict the values. But in real-world, data is unstructured, and most of the times, not on the same scale.This is when normalization comes into picture. It is one of the most important ...
Read More