Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
In any profession that involves handling large amounts of data, from finance to marketing and beyond, time is always crucial. Stumbling upon an efficient Data Analysis technique that allows us to quickly organize and analyze the data which saves valuable time for data analysts. In this article, we will learn how to install Data Analysis Toolpak within an Excel worksheet, enhancing your productivity. This powerful toolpak improves users' analytics concepts, especially when handling large voluminous of data. It also facilitates future trends, pattern and summarizes the data, and aids managers in better decision−making and reaching a conclusion. To download Data ... Read More
You will discover how to perform an F test using Data Analysis Toolpak in this article. The F−test function would be used to verify whether two distinct samples have the same variances or not. Manually doing the F test has a significant probability of error, is time−consuming, and yields erroneous findings. After conducting the F test, users may decide whether to accept the null hypothesis or reject the alternative hypothesis. It is one of the best statistical methods and generates accurate results when dealing with numerous samples in a dataset. To conduct F−Test of two samples for Variances without mathematical ... Read More
The popular Exponential Smoothing data analysis technique will be applied to forecast the time series' upcoming outcome. Sales managers and business analysts may make better decisions and predict future sales forecasts through this method. Before delving deeply into this article, users must have prior knowledge of Excel and must download the Data Analysis Toolpak. There are two ways to achieve Exponential smoothing in Excel. We have a built−in formula in Excel called FORECAST.ETS to flatten the time series, and another way is to utilize the Data Analysis tab efficiently. To perform Exponential Smoothening using the Data Analysis tab Step ... Read More
In MS Excel, users face difficulty while performing Statistical Analysis due to a lack of their knowledge. Numerous built-in statistical methods are obtainable in Excel but deploying all the essential statistical functions separately is very time−consuming. Descriptive Statistics is one of the predominant options presented inside the Data Analysis tab to summarize the specified data that is entered by the user. The Descriptive Statistics option assists us in unraveling the statistical characteristics of the dataset like Mean, Mode, Maximum or Minimum value, etc. To Conduct the Descriptive Statistics in MS Excel Step 1 − Open a new worksheet in ... Read More
A diversity of statistical methods is available in MS Excel to generate the descriptive summary of data. Two-factor ANOVA is a paramount technique utilized by research scholars and data analysts to verify whether the relevant output is to be generated or not after performing a few tests. It would be possible to evaluate the means of more than one set of values using an analysis of variance. The major variations of ANOVA are unidirectional ANOVA and two-way ANOVA. The F-test is the statistical significance test for ANOVA. To perform ANOVA two-factor with Replication in Excel Step 1 − Assume ... Read More
Sometimes users enter data in the wrong column, due to this user need to swap the available contents between the two cells. This can be done in many possible ways. In this article, we will swap the contents of the two cells in Excel by using the normal drag and drop facility, and by using the VBA code. Both the provided examples are accurate, precise, and thorough. By following all the guided steps, the user can easily swap the contents of the two cells. After swapping the values will move back to their original supposed location or cell in the ... Read More
Pandas is one of the libraries in python which is used to perform data analysis and data manipulation. The data can have created in pandas in two ways one is as DataFrame and the other way is Series. The DataFrame is the two dimensional labeled data structure in python. It is used for data manipulation and data analysis. It accepts different data types such as integer, float, strings etc. The label of the column is unique whereas the row is labeled with the unique index value which helps in accessing the defined row. DataFrame is used in machine ... Read More
NumPy is one of the popular libraries in python which is used to perform numerical calculations, scientific computations. It also allows us to work with large multi-dimensional arrays and matrices. There are many functions and modules in-built in the numpy library which are used to work with the different dimensional arrays. Converting a dictionary into a NumPy array We can convert a dictionary into a NumPy array by using the different modules and functions available in Numpy library. Let's see each way one by one. Using the numpy.array() function In NumPy, we have the function namely array(), which is used ... Read More
The Instance variables are generally used to represent the state or attributes of an object. Each instance of a class can have its own set of instance variables, which can store unique values. An instance variable is defined within the methods of a class and is accessible throughout the instance's lifespan. Accessing the instance variable in python The flexibility that comes with usage of instance variables allows each instance to maintain its own set of variables, enabling customized behaviour and data storage for different objects. Thus, accessing instance variables in python is a useful step.There are different ways to ... Read More
Sorting refers as the technique to arrange the elements in the defined order. There are different ways to sort the dictionary by keys in python. In this article we are going to learn those. Using sorted() function The sorted() function is used to sort the elements in the iterable data structures like tuple, dictionary, list etc. This function takes the iterable as the argument and returns the new sorted list containing the sorted elements as the output. Following is the syntax for using the sorted() function on dictionary. sorted(dictionary.keys()) Where, sorted is the function used to sort ... Read More