Author: saqibkhan
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StatSnap Tutorial
1. Installation First, you need to install StatSnap. You can do this via pip: 2. Importing Libraries Start by importing the necessary libraries: 3. Loading Data You can load your dataset using Pandas. For this example, let’s create a sample DataFrame. 4. Descriptive Statistics StatSnap can help you generate descriptive statistics easily: 5. Visualizing Data…
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Setting Up
Example: Drawing a Simple Pattern Here’s a step-by-step example to create a simple pattern. Step 1: Create a New File Create a new file named pattern.ren. Step 2: Basic Code Structure Step 3: Drawing Shapes Now, let’s draw some circles in a grid. Step 4: Adding Effects You can add some effects to make the…
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DataDive
Data Collection Using pandas to read data from a CSV file. 2. Data Cleaning Handling missing values and duplicates. 3. Data Exploration Basic statistics and visualizations. 4. Data Transformation Creating new features and encoding categorical variables. 5. Data Analysis Performing group operations and aggregations. 6. Data Visualization Creating plots to visualize relationships. 7. Machine Learning…
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What is the difference between the with() and within() functions?
The with() function evaluates an R expression on one or more variables of a data frame and outputs the result without modifying the data frame. The within() function evaluates an R expression on one or more variables of a data frame, modifies the data frame, and outputs the result. Below we can see how these functions work using a sample data…
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What is Shiny in R?
Shiny is an open-source R package that allows the easy and fast building of fully interactive web applications and webpages for data science using only R, without any knowledge of HTML, CSS, or JavaScript. Shiny in R offers numerous basic and advanced features, widgets, layouts, web app examples, and their underlying code to build upon…
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List and define the various approaches to estimating model accuracy in R.
Below are several approaches and how to implement them in the caret package of R. To implement these cross-validation methods in R, we need to set the method parameter of the trainControl() function to “cv”, “repeatedcv”, or “LOOCV” respectively, when defining the training control of the model.
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What are correlation and covariance, and how do you calculate them in R?
Correlation is a measure of the strength and direction of the linear relationships between two variables. It takes values from -1 (a perfect negative correlation) to 1 (a perfect positive correlation). Covariance is a measure of the degree of how two variables change relative to each other and the direction of the linear relationships between…
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How to select features for machine learning in R?
Let’s consider three different approaches and how to implement them in the caret package. We need to create a correlation matrix of all the features and then identify the highly correlated ones, usually those with a correlation coefficient greater than 0.75: We need to create a training scheme to control the parameters for train, use…
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What are regular expressions, and how do you work with them in R?
A regular expression, or regex, in R or other programming languages, is a character or a sequence of characters that describes a certain text pattern and is used for mining text data. In R, there are two main ways of working with regular expressions: