Author name: cndro

                                                                       Photo by Windows on Unsplash What is Office 365 Calendar? The Microsoft Office 365 suite of business applications is packed with helpful features, and the Calendar is no exception. This digital scheduler lets you keep track of important events and appointments with ease. And because it’s a cloud-based service, you can access your calendar from virtually any computer or mobile device. If you use the Office 365 Calendar, you probably already know it’s an essential tool for managing your busy schedule. But did you know that the Calendar in Office 365 has many useful features that can help you manage your time more effectively? If not, don’t worry — this article will explain everything you need to know about using the Microsoft Office 365 Calendar app to stay organized and on track every day of the week! How to Access the Microsoft Office 365 Calendar Before you start using the Calendar in Office 365, you need to know how to access it first. There are a couple of pretty easy ways you can access Office 365 calendar. The first way is to go to this address: outlook.live.com. It will open an outlook page where you have the email, calendar, and the to-do tabs at the bottom left of the page. Click on the calendar tab, and boom…there you are! Another way to access the Calendar is by going through Bing. Go to www.bing.com on your browser and click on the three dots tab at the top. You’d see a drop down, scroll down to Office and select the Calendar option. The last and the easiest way to access the Calendar is to simply type Calendar in your browser and allow your browser to complete it. However, this works best with google calendar. Office 365 Calendar Overview The Calendar interface is shown in the image below. It’s a free version so it has limited features. However, you can perform basic functions like creating events, sharing your calendar, add calendars, edit calendars, view holidays, and others. Viewing your Calendar You can choose different views for your calendar. You can choose week, month, week, work week, and day view. How to Create an Event in Office 365 Calendar To create an event in Calendar, simply click on the menu “New Event” at the top left corner of the page. A new page pops up that allows you to create an event. Here, you have the scheduling assistant, response options, show as, and categorize. Editing Events on the Calendar To edit an event on the calendar, open the event by clicking on it. Change the details you wish to modify and save. Deleting Events on the Calendar If you wish to remove an event, you can delete it by clicking on the event(specifically, click on the event time) in the calendar. You will see the delete option, select and your event will be deleted. Another method is to click on the edit button, a new page would be opened, at the top left corner, you’ll see the delete option. Sharing your Calendar with Others You can share your Calendar with people inside or outside your organization. It’s easy to do that. Go to the share menu at the top right corner of the page, click on it to share. You can share through an email and set permissions for the user. Wrapping Up Calendar is one such program that can be used to keep track of events and appointments. It also allows users to create their own custom calendars and manage various events and reminders. Hope you enjoyed reading this article. If you do, comment and share with your friends. See you in our next post.

                                                                       Photo by AltumCode on Unsplash In our previous tutorial, we did an introduction on what TabPy(Tableau Python Server) is and why everyone should start using it. Just as discussed, TabPy is an API which enlarges Tableau’s capabilities by allowing users to execute Python scripts and saved functions via Tableau’s table calculations. With TabPy, we can handle our data exploration and visualization better, and the ability to use Python programming language here is the main deal. Now, let’s discuss each of the python functions we can use to write our TabPy code. SCRIPT_BOOL: This function is mainly used whenever you want to return a Boolean output from a given calculation. e.g. TRUE/FALSE SCRIPT_INT : This function can be used whenever you want to return an output of type integer from the given calculation. e.g. -2,-1, 0, 2 SCRIPT_REAL: This function is also used whenever you intend to return an output of type real from the given calculation. e.g. -.25, 0, 2/3 SCRIPT_STR: This is used for returning an output of type string from the given calculation. e.g. “Jack”, “red”. Let’s move further and see how we can use each of the functions; SCRIPT_BOOL: Verify if Profit is Greater than Zero In our demonstration, we want to loop through our profit values and see if some of the values are greater than Zero or not. The output we get here should be a True or False response. From the image  above, we used our SCRIPT_BOOL function here. We opened an empty list named verify, which is to store our result. On the next line we looped through _arg1, this _arg1 stands for the Profit measure which we passed in at the last line. Looping through this _arg1, we checked if our data values is greater than zero and pass in the result by appending via the empty list and return the list. We used the calculation in our view, which is what we have below; SCRIPT_INT: Looping through Profit Value With the SCRIPT_INT function, we’ll loop through our profit value and now divide the profit by 100 and round the expected value. Let’s check below and see how it’s done. From the image above, we demonstrated by looping through the _arg1, the _arg1 here represents the profit and now we could see an empty list was declared which we named “total”. This empty list is where we passed the result of our calculation after dividing by 100 and rounding it up. The reason this empty list was used is for Tableau to handle our result efficiently and if possible to avoid errors. We used this calculation in our view, which is what we have here below; SCRIPT_REAL: Finding Relationship Between Sales and Profit With the SCRIPT_REAL function, we’ll calculate the correlation we have between the sales and Profit, which is more like knowing the relationship we have between both. Our result should be either negative or positive correlation, between the range of -1 and 1. In our calculation here, we will import a library, which is the Numpy library and we need to use 2 measures now(i.e. Sales & Profit). Just as we’ve done earlier whereby we’ve been passing our argument as _arg1. Here, the _arg1 will stand for Sales and _arg2 will stand for Profit. Let’s see the calculation below; We tested with the view we have here below; SCRIPT_STR: Extracting Customer’s Last Name In this demonstration, we’ll use our SCRIPT_STR function to extract each customer’s last name. Here, we will loop through the customer’s name and use the split function in python to split on whitespaces and with list indices, we extract the Last name. We used the code below; Let’s use this calculation in our view, we have each of the customer’s Last name extracted as seen below; Hope you enjoyed this post. Thanks for reading.

                                                       Photo by Fotis Fotopoulos on Unsplash TabPy is an Analytics Extension from Tableau that allows users to execute Python Scripts and saved functions using Tableau. With TabPy, we can run Python Script on the fly and display results as a visualization. It is also possible to control data sent to TabPy by interacting with the Tableau worksheet and dashboard via the parameters. We all know Python programming is the most popular language used to work on various statistical problems. Using this language with Tableau is a significant improvement in improving the effectiveness of a Developer. Now, let’s discuss why you need to start using TabPy. Key Reasons For Data Cleaning Purpose: With TabPy, we can perform data cleaning on messy data by removing non-useful columns, missing values, and as well any other actions we might want to perform. TabPy gives Developers the feel of working smarter. For Building predictive algorithms: Predictive Modeling is a way we use our data and statistics to predict the outcome of a data model. This process is also known as predictive analysis. Therefore, using TabPy, we can build our Predictive Algorithms inside Tableau. Churn prediction: Churn Prediction is another vital aspect business owners mostly dwell on. With TabPy, we can learn when and why users leave. We can also detect patterns we need in our data, predict and prevent them from happening. Writing Calculated Field in Python: We can also write our calculated field with Python without using Tableau with the help of TabPy. Using Python whenever we want to do advanced analytics is also always advisable. Lead scoring: Leads generation is another essential sector lot of business owners works hard to convert leads into payable customers. We can create an efficient conversion funnel with Python for scoring users’ behavior with a predictive model. This can be made possible with TabPy as well. Now that we’ve seen the major reasons TabPy is very good to use in Tableau, let’s see how we can install it. How to Install TabPy We’ll install TabPy using Anaconda Navigator through the Anaconda Prompt. Step 1 Open your Anaconda prompt and create a virtual environment using the below command. This isn’t compulsory, though. 1 conda create — name virtualenv Step 2 Now, let’s upgrade our pip version with the command below. 1 python -m pip install — upgrade pip Step3 Our Pip has been upgraded, and we can move further to install TabPy. From the image below, TabPy was installed earlier on my machine. 1 pip install tabpy   Step 4 By now, you should have TabPy installed on your machine. Let’s run the server now. We can run using the command below inside the same Anaconda prompt. So, you type tabpy, and you should have a similar image we have below. 1 tabpy Now, you open your browser and visit this URL http://localhost:9004/ to verify the web service is running. You should have an image like this. Step 5 What we need to do next is to make Tableau connected with Tabpy, open our Tableau Desktop, and click on help -> Settings and Performance ->Manage Analytics Extension Connection. This brings up a pop-up. You select TabPy as the External Service, indicate the server as localhost and Port as 9004, then click OK. Now we’ve created a connection. Have you started exploring TabPy ? What was your experience like? Share your thoughts in the comments section below.

                                                              Photo by Susannah Burleson on Unsplash This tutorial will discuss why Power Query is essential to Power BI. Microsoft Power BI, as we all know, is a business analytic solution that allows you to visualize your data and share insights in an organization. Several services have been made available for users to use among all the Power BI Desktop, which is free. We use this tool daily for producing interactive visuals and for all sorts of data visualization. Also, non-technical business users can use this tool for whatever they want to do, and this tool requires no upfront training. Let’s move to our topic of interest, the Power Query. The Power Query is listed among other components of Power BI, such as the Power Pivot, Power View, Power Map, and Power Q&A. Each of these components has a cogent role they play in helping users meet their business needs. Power Query The Power Query is a data transformation tool and a preparation engine that came with Microsoft Excel and Microsoft Power BI. This tool helps users process and manage data of different file types such as Excel, CSV, Web Pages, Databases, e.t.c. We can use Power Query to combine data from these various sources, derive new columns, reshape this data, format and write formulas for advanced data manipulations. We have two ways to access Power Query, and you can either use it via Power BI Desktop or Online. Since we’ve defined Power Query, let’s look at why it’s being used a lot. Key reasons for using this tool Power Query provides connectivity to a wide range of data sources, including data of different sizes and structures. This highly interactive tool gives users excellent guidance for building queries over any data source. With Power Query, we can work over a subset of a dataset to carry out data transformations and filter to our desired size. Power Query also provides consistency of experience and parity of query capabilities over all data sources. We can manually refresh Power Query or use its scheduled refresh capabilities. With Power Query, we can reshape data by transposing, grouping, pivoting, un-pivoting, e.t.c. We can also write formulas to perform advanced manipulation of data. Overview of Power Query Interface To gain access to the Power Query Editor, open your Power BI Desktop, bring in sample data, go to the Home tab, and click Transform data. After you’ve clicked on the Transform data, you should have an interface as shown below; The image shows five different tabs: Home, Transform, Add Column, View, Tools, and Help. Each of these tabs has a crucial role in assisting the analyst in manipulating data to his desired choice. We also have different tabs below it, which we can use to transform our data. We can play around with these different menus to generate the new cleaned and structured data format we want. Another key thing to note is our Data Pane at the center, the left Pane, and Query settings on the Right. The Data Pane at the center is where we have our view and see what’s going on in our data, while the Pane on the left shows us the number of ongoing queries with each query name displayed. The Right Pane is also regarded as Query Settings, which displays all steps related to each query. Did you find this post helpful? Let us know in the comments section below and follow for more educative posts.

                                                                  Photo by Fotis Fotopoulos on Unsplash In our last tutorial, we discussed why Selenium is the best automation tool and demonstrated how we could run a simple test case in Python. As we said, Selenium is compatible with leading programming languages like Python, Java, Ruby, and others. We can use it with any of our popular browsers like Chrome, Firefox, Edge, and lots more. Today, we’ll discuss the top commands we need to know when working with Selenium in Python. Commands for Searching Specific Web Elements The list of commands we will first discuss is the commands used for automating and searching web pages. They are also called Locators in Selenium. Now, to identify these specific elements on a web page, we will use the findElement() command. Here is the list of the commands; find_element_by_xpath: This can be used to locate and return the first element with the XPath syntax. Xpath can also be implemented when working with an XML document, and mainly XPath is used when the code isn’t working successfully with ID, class, or name. We can implement XPath in our script as shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 9 #We will use the driver.get to open the wiki main page 10 driver.get(“https://en.wikipedia.org/wiki/Main_Page”) 11 12 #we copy our xpath of the elements we are interested in from the Inspect element in browser 13 elements = driver.find_element_by_xpath(‘//*[@id=”n-contents”]/a/span’) 14 15 16 print(elements) 17 18 #we then close the browser 19 driver.close() 20 21   2. find_element_by_id: We use the find_element_by_id to return first element with id attribute value matching the location of our item. If no element was found, the NoSuchElementException would be raised. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 #We will use the driver.get to open the wiki main page 9 driver.get(“https://en.wikipedia.org/wiki/Main_Page”) 10 #we specify the id of the element we want to search for here 11 elements = driver.find_element_by_id(‘mw-navigation’) 12 13 print(elements) 14 15 #we then close the browser 16 driver.close() 17   3. find_element_by_name: We can also find our element by name. To do that, we use the find_element_by name locator and pass the name attribute. This will return the first element found during the search. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 #We will use the driver.get to open the wiki main page 9 driver.get(“https://en.wikipedia.org/w/index.php?title=Special:UserLogin&returnto=Wikipedia%3AAbout”) 10 #we specify the name of the element we want to search for here 11 elements = driver.find_element_by_name(‘wploginattempt’) 12 13 print(elements) 14 15 #we then close the browser 16 driver.close()   4. find_element_by_class_name: To use the find_element by class name locator, we use it along by specifying the element’s class name. This will give us the first element found in our search. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 #We will use the driver.get to open the wiki main page 9 driver.get(“https://en.wikipedia.org/wiki/Main_Page”) 10 #we specify the class name of the element we want to search for here 11 elements = driver.find_element_by_class_name(‘mw-parser-output’) 12 13 print(elements) 14 15 #we then close the browser 16 driver.close() 17   5. find_element_by_link_text: We use this find_element_by_link_text to find a particular hyperlinked text in a page. To use this locator, we specify the name of the hyperlinked text inside our locator. This will return the first element found in our search. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 #We will use the driver.get to open the wiki main page 9 driver.get(“https://en.wikipedia.org/wiki/Main_Page”) 10 #we specify the name of the element we want to search for here 11 elements = driver.find_element_by_link_text(‘Contents’) 12 13 print(elements) 14 15 #we then close the browser 16 driver.close()   6. find_element_by_css_selector: It is possible to find an element using the CSS selector. We specify the CSS selector we want to use inside the locator during the search. The first element with the matching selector will be returned, and if no element was returned, the NoSuchElementException would be raised. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window 7 driver.maximize_window() 8 #We will use the driver.get to open the wiki main page 9 driver.get(“https://en.wikipedia.org/w/index.php?title=Special:UserLogin&returnto=Wikipedia%3AAbout”) 10 #we specify the css selector of the element we want to search for here 11 elements = driver.find_element_by_css_selector(‘input.wploginattempt’) 12 print(elements) 13 14 #we then close the browser 15 driver.close()   7. find_element_by_tag_name: Just as we mentioned the CSS selector earlier, we can also find our element using the Html Tag name. This tag name will be used inside the find_element_by_tag_name locator. This will return the first element that matches the tag name; if no element, a NoSuchElementException will be raised. An example is shown below; 1 #we import our library 2 from selenium import webdriver 3 4 #here we paste link to our exe file in the webdriver.chrome method 5 driver = webdriver.Chrome(r’C:\Users\CNDRO\Documents\Selenium_project\Browser\chromedriver.exe’) 6 #we maximize our window

This tutorial will discuss why you need to use a layout container in your dashboard. Layout Containers are perfect for neatly arranging objects when creating your dashboard. Arranging objects in a dashboard has always been a struggle for some Developers, who find this confusing. We must be intentional about arranging our worksheets in an orderly manner on our dashboard. Setting them well gives the dashboard a cleaner look for the audience or users. This is why containers are the solution to standardize the size and layout of the dashboard when viewed via different device lenses(Desktop, Tablet, Phone). Before we move into using Layout Containers in Tableau, let’s discuss critical things to consider while planning our dashboard. Define your Audience — You need to define your audience and what they want to see on their dashboard. Also, ask if your dashboard is user-friendly, whereby the audience can quickly grasp what you did and, what are the metrics important to your audiences’ businesses. Layout — The layout, which is the subject of our discussion today, is also vital when planning a dashboard. You should always separate your dashboards into sections, making navigating easier for your users. Design Purposeful Dashboard — When designing your dashboard, it has to be purposeful, whereby you consider the impact it has on the users or audience. It would help if you also consider how your audience would understand the dashboard. How to Get Started with Layout Containers Containers, like we said, allow us to group our objects, i.e., worksheets, images, filters, and lots more, together. We can move the container anywhere we want, and our dashboard objects will maintain the size we allocate. We have two types of Layout containers; Horizontal and Vertical. Horizontal Containers — The horizontal containers help group worksheets and dashboard components from left to right across our page. There is no limit to the number of containers we can place within other containers. Vertical Containers — Vertical containers help users group worksheets from top to bottom down along a page. So we may have a horizontal container on the left-hand side and a vertical container to our right where the sheet has a drop-down filter. From the image below, you can find the Horizontal and Vertical containers under the Objects sections. You drag it inside your Dashboard working area to use either of it. Steps to follow while Inserting Containers Always have an outer Container: Whenever you’re designing your dashboard, it’s always good to have an outer container that contains both the dashboard title and its content. Insert Dashboard Title and more Containers: Now that you’ve inserted an outer container, you can bring in more containers per your desired choice of placing content. Then you go further by typing in your dashboard title, which should be at the top of the view. Also, Inside our containers, we can put temporary blank contents in to help us arrange our contents well while placing the worksheets in them. Populate Containers with Worksheets: So now we can remove those blanks and populate them with our worksheets accordingly, and we put in mind to arrange them for easy navigation for our users or according to our audience priority. We have a simple representation in the image below. Also, you must always check your items’ hierarchy when working on your layout. This is very important as it lets you quickly change how objects are layered and grouped on your dashboard. The view tells you that Items at the top of the list appear in the front, while items at the bottom appear at the back. A simple representation of the items hierarchy is shown below; Hope you found this post helpful. Let’s know your thoughts in the comments section below. Thanks for reading.