Master Series Tutorial
Clara Vanliere
Fill Series in Excel is a smart and intelligent solution to fill your rows with legitimate data and save time with one hundred percent accuracy. One-step and Excel will automatically fill the entire spreadsheet with the correct data based on your inputs.
This tutorial on Fill Series in Excel will help you master the Fill Series method and save time in day-to-day business data analytics. The tutorial will explain the fundamentals of the Fill Series in Excel.
Fill Series in Excel is an automated way of entering valid data into the rows using Excel's predefined and intelligent prediction functionalities. Fill Series can add the data instantly into the selected range of cells. The values are separated by equal intervals of units like days, steps, months, etc.
The following example has January in its first cell. By dragging the cell, you can see the cells followed by January are getting filled automatically with the help of the fill series. At the bottom, you can see another option that stores a few additional functions to smartly decide which one to be implemented, as shown in the image below.
The next example is about the WeekDay fill series in Excel. The weekday application for fill series in excel is similar to the months series. You can write the first day or any day of the week and simply drag the cell over the next consecutive cell and fill the relevant data in the succeeding cells, as shown in the image below.
Now comes the tricky part. If you wish to exclude a few days, say, Sunday and Saturday. This can be done by editing a couple of options in the filter or format menu in the bottom right corner, as shown below.
With this, you are concluding this tutorial on Fill Series in Excel. If you have any queries regarding any of the concepts discussed in this tutorial, please feel free to let us know in the comments section below.
SUMIFS in Excel can be your next step in learning data analytics. SUMIFS in Excel will help you perform the summation operations in excel with customized conditions based on the business requirements.
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Welcome! You are about to start on a journey to learn how to create web applications with Python and the Flask framework. In this first chapter, you are going to learn how to set up a Flask project. By the end of this chapter you are going to have a simple Flask web application running on your computer!
All the code examples presented in this book are hosted on a GitHub repository. Downloading the code from GitHub can save you a lot of typing, but I strongly recommend that you type the code yourself, at least for the first few chapters. Once you become more familiar with Flask and the example application you can access the code directly from GitHub if the typing becomes too tedious.
At the beginning of each chapter, I'm going to give you three GitHub links that can be useful while you work through the chapter. The Browse link will open the GitHub repository for Microblog at the place where the changes for the chapter you are reading were added, without including any changes introduced in future chapters. The Zip link is a download link for a zip file including the entire application up to and including the changes in the chapter. The Diff link will open a graphical view of all the changes that were made in the chapter you are about to read.
If you don't have Python installed on your computer, go ahead and install it now. If your operating system does not provide you with a Python package, you can download an installer from the Python official website. If you are using Microsoft Windows along with WSL or Cygwin, note that you will not be using the Windows native version of Python, but a UNIX-friendly version that you need to obtain from Ubuntu (if you are using WSL) or from Cygwin.
The Python interpreter is now waiting at an interactive prompt, where you can enter Python statements. In future chapters you will learn what kinds of things this interactive prompt is useful for. But for now, you have confirmed that Python is installed on your system. To exit the interactive prompt, you can type exit() and press Enter. On the Linux and Mac OS X versions of Python you can also exit the interpreter by pressing Ctrl-D. On Windows, the exit shortcut is Ctrl-Z followed by Enter.
In Python, packages such as Flask are available in a public repository, from where anybody can download them and install them. The official Python package repository is called PyPI, which stands for Python Package Index (some people also refer to this repository as the "cheese shop"). Installing a package from PyPI is very simple, because Python comes with a tool called pip that does this work.
Interestingly, this method of installing packages will not work in most cases. If your Python interpreter was installed globally for all the users of your computer, chances are your regular user account is not going to have permission to make modifications to it, so the only way to make the command above work is to run it from an administrator account. But even without that complication, consider what happens when you install a package in this way. The pip tool is going to download the package from PyPI, and then add it to your Python installation. From that point on, every Python script that you have on your system will have access to this package. Imagine a situation where you have completed a web application using version 2 of Flask, which was the most current version of Flask when you started, but now it has been superseded by version 3. You now want to start a second application, for which you'd like to use version 3, but if you upgrade the version 1 that you have installed you risk breaking your older application. Do you see the problem? It would be ideal if it was possible to have Flask version 2 installed and accessible to your old application, while also install Flask version 3 for your new one.
To address the issue of maintaining different versions of packages for different applications, Python uses the concept of virtual environments. A virtual environment is a complete copy of the Python interpreter. When you install packages in a virtual environment, the system-wide Python interpreter is not affected, only the copy is. So the solution to have complete freedom to install any versions of your packages for each application is to use a different virtual environment for each application. Virtual environments have the added benefit that they are owned by the user who creates them, so they do not require an administrator account.
With this command, I'm asking Python to run the venv package, which creates a virtual environment named venv. The first venv in the command is an argument to the -m option which is the name of the Python virtual environment package, and the second is the virtual environment name that I'm going to use for this particular environment. If you find this confusing, you can replace the second venv with a different name that you want to assign to your virtual environment. In general, I create my virtual environments with the name venv in the project directory, so whenever I cd into a project I find its corresponding virtual environment.
Note that in some operating systems you may need to use python instead of python3 in the command above. Some installations use python for Python 2.x releases and python3 for the 3.x releases, while others map python to the 3.x releases and do not have a python3 command at all.
When you activate a virtual environment, the configuration of your terminal session is modified so that the Python interpreter stored inside it is the one that is invoked when you type python. Also, the terminal prompt is modified to include the name of the activated virtual environment. The changes made to your terminal session are all temporary and private to that session, so they will not persist when you close the terminal window. If you work with multiple terminal windows open at the same time, it is perfectly fine to have different virtual environments activated on each one.
Note that the above installation commands do not specify which version of Flask you want to install. The default when no version is specified is to install the latest version available in the package repository. This tutorial is designed for version 3 of Flask, but should also work with version 2. The above command will install the latest 3.x version, which should be appropriate for most users. If for any reason you prefer to follow this tutorial on a 2.x release of Flask, you can use the following command to install the latest 1.x version:
If you go to the Flask's quick start page, you are welcomed with a very simple example application that has just five lines of code. Instead of repeating that trivial example, I'm going to show you a slightly more elaborate one that will give you a good base structure for writing larger applications.
The application will exist in a package. In Python, a subdirectory that includes a __init__.py file is considered a package, and can be imported. When you import a package, the __init__.py executes and defines what symbols the package exposes to the outside world.
The script above creates the application object as an instance of class Flask imported from the flask package. The __name__ variable passed to the Flask class is a Python predefined variable, which is set to the name of the module in which it is used. Flask uses the location of the module passed here as a starting point when it needs to load associated resources such as template files, which I will cover in Chapter 2. For all practical purposes, passing __name__ is almost always going to configure Flask in the correct way. The application then imports the routes module, which doesn't exist yet.
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