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Android file transfer: How to move data between your phone and computer

Your smartphone is a powerful computer in your pocket — and with Android, part of that PC-like muscle means being able to plug your phone into any Windows, Mac, or Chrome OS system and then drag and drop files either way.

Unlike iPhones, Android devices allow you to access their file systems directly from a desktop, without the need for any cumbersome interfaces or complicated procedures. In fact, transferring files to or from an Android device is basically no different than plugging an external hard drive into your computer and moving data to or from it.

All you need is your phone, your computer, and a cable to connect ’em — with micro-USB or USB-C on the phone side and USB-A or USB-C on the computer side, depending on the specifics of your devices. (Most current Android phones use USB-C, whereas most pre-2016 devices have the older micro-USB standard. USB-A, meanwhile, is the traditional connector port you’re used to seeing on computers, though more and more models now also offer USB-C.) There’s a decent chance that the same cable that connects your phone to its wall charger will work.

Got it? Good. Here’s what you need to do next, depending on whether you have a Windows, macOS, or Chrome OS system:

Android file transfers for Windows computers

With Windows, things are as simple as can be. Just plug your phone into any open USB port on the computer, then turn on your phone’s screen and unlock the device.

Swipe your finger down from the top of the screen, and you should see a notification about the current USB connection. At this point, it’ll probably tell you your phone is connected only for charging.

android file transfer usb notification JR Raphael/IDG

After you connect your phone to your computer, a notification will let you prepare it for transferring files.

Tap the notification and select “Transfer files” or “File transfer” in the menu that appears. If media files are all you’re planning to move, you could also use the “Transfer photos” (sometimes listed as “PTP”) option, which’ll treat your phone like a digital camera. Once you’ve made your selection, go to your desktop and open up a File Explorer window using the method that makes the most sense for your Windows configuration:

  • Click the File Explorer icon in your taskbar
  • Open the Start menu and click This PC or Computer
  • Click the This PC, Computer, or My Computer icon on your desktop

Then look for an icon representing your phone alongside other portable devices and drives. Click or double-click that icon, and ta-da! You’re staring at your Android phone’s internal storage. You can now click around and browse folders, drag and drop files between your phone and PC, or manipulate the data in any way you want.

android file transfer windows JR Raphael/IDG

Your Android phone’s storage looks like any regular hard drive when viewed from a computer.

Android file transfers for Mac computers

Got a Mac? The Android file transfer process is a bit more complicated for you — but fear not, for it’s still pretty darn easy.

The main difference is that before things will work, you’ll need to download and install an official Google program called Android File Transfer. To use the program, your Mac must be running macOS 10.7 or later, and your Android device must have Android 3.0 or later — something that should pretty much be a given with any reasonably recent Android product.

Once the program’s in place on your Mac, just plug your phone into your computer, turn on your phone’s screen and unlock the device, and then look for the same USB status notification described above.

Tap the notification and select “Transfer files” or “File transfer.” The Android File Transfer program should then automatically open on your Mac, and you should be able to browse your phone’s storage and transfer files to your heart’s content.

If the official Android File Transfer program doesn’t work well for you — a vexingly common complaint among Mac users these days — consider the favorably reviewed third-party Commander One Pro as an alternative. It costs $30 for a single license, $100 for a five-user team license, or $150 for a 50-user company license.

Or — well, skip down to the final section of this story for one other option.

Android file transfers for Chrome OS computers

You’d expect file transfers between Android phones and Chromebooks to be as simple as can be, considering that Google’s the driving force behind both of those operating systems — and by golly, you’d be absolutely right.

Just like on a Windows system, all you’ve gotta do to connect your Android phone to a Chromebook is plug it into any open USB port, then tap the USB charging notification on the phone and select either “Transfer files” or “File transfer” from the prompt that appears — or select “Transfer photos” or “PTP” if you want your phone to be treated like a camera, with a focus exclusively on multimedia files.

Once you do that, the Chrome OS Files app should automatically appear on your Chromebook with your phone present as one of the storage options. The system will probably even prompt you to back up all of your phone’s media files to Google Drive; you can allow that, if you’d like, or dismiss it and simply drag and drop files in either direction as needed.

android file transfer chrome os JR Raphael/IDG

Pulling up your Android phone’s storage on a Chromebook is easy as can be — and typically includes a one-click option to copy all your device’s media files as well.

There’s really not much to it — nor should there be.

And if you want an even simpler way to take care of business…

Don’t like cables?

Hey, wait a minute — aren’t there apps and cloud services for this sort of thing? Sure there are, and we’ve got you covered there, too. Check out “Transferring files wirelessly between devices” in our in-depth Android file management guide for everything there is to know.

This article was initially published in August 2017 and updated in October 2019.

Copyright © 2019 IDG Communications, Inc.

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How to Combine Multiple Data Sets in Microsoft Excel Using Power Query

Microsoft Power Query is a useful tool to work with data inside of Microsoft Excel. It comes with a lot of features that make managing data sets simple yet powerful.

Power Query is most useful when working with multiple sets of data, rather than just one. It acts as a bridge between sets of data and Microsoft Excel.

To prove it, we’ll walk you through a common task where Power Query shines: combining two different data sets into one.

What Is Microsoft Power Query?

Microsoft Power Query is a tool included in Microsoft Excel for Windows. It’s only included in 2016 or newer versions, so check those versions to begin using. New users should make sure they’re pretty comfortable in Excel

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before starting to use Power Query.

What Power Query allows you to do is load data from a number of different sources, edit that data, and then import it into an Excel worksheet. Learn more about why you should start using Microsoft Power Query.

One of the source types from which you can pull data is other Excel sheets. To get the data for this Power Query demonstration, we are going to use two different Excel worksheets containing similar data sets, and then combine them into one.

Setting Up Your Data

Let’s take two Excel workbooks, one titled “Cars.xlsx” and one titled “Trucks.xlsx”. The contents of these sheets are simple. Each sheet contains a table describing certain vehicles categorized by columns: “Make”, “Model”, “Color”, and “Year”.

Excel Spreadsheet for Power Query

Excel Spreadsheet for Power Query

We are also creating a blank workbook titled “Vehicles.xlsx” that we will do our work in.

To keep things simple we are using two data sets with the same header information. Our objective here is to create a new table with both car and truck information.

Now that these workbooks are saved to the computer, let’s get to work with Power Query!

Loading Data Into the Power Query Editor

To begin, all you need to do is open the workbook you want to contain the finished data. In this case, the workbook is “Vehicles.xlsx”.

Power Query is so easy, you don’t even have to open the workbooks containing data to extract what you need. In “Vehicles.xlsx” navigate to the “Data” tab of your workbook options.

You will see the “Get Data” option in your toolbar. This option is the entry to Power Query and will allow you to choose your source of data.

You want to work with an Excel workbook, so choose the “From File” options followed by “From Workbook”.

Importing Data From Excel Into Power Query

The editor will open a file explorer and you can navigate to a workbook anywhere on your PC. You are going to choose the “Cars.xlsx” file first.

Once you select your file, the Power Query Navigator menu will load to show you a preview of the sheet you selected. Notice the file “Cars.xlsx” as well as the sheet is displayed in the Navigator. Click on the sheet and the table will load on the menu just as it appears in your worksheet! Click on “Transform Data” to open the data in the editor.

Navigator for Power Query Menu

Using the Power Query Editor

The Power Query editor is packed with a lot of options, don’t worry about those right now while you get familiar with the basics. At first glance, the data has been uploaded properly! It looks just like an Excel table. Data is organized in rows and columns, with named headers at the top.

Power Query Main Menu for Excel

On your right is a menu called “Query Settings” which contains an “Applied Steps” window. Steps are just changes made to your table. Keep an eye on this for later.

On the far left clicking on the “Queries” icon will expand the menu and show the name of the table you are currently working in. Power Query can take multiple tables at one time and will display them all in this toolbar.

In order to append two tables together, they both need to be uploaded into Power Query. You have one, let’s grab the other.

Adding a Second Data Source

Inside of the editor, at the top right corner, is the “New Source” button. This button allows you to select an additional data source and add it to the Power Query Editor.

Menu of Power Query for Excel

Choose “File” and then “Excel” to open the file explorer. Navigate to “Trucks.xlsx” to select the file for importing.

Just like the first Query, the Navigator will pop up allowing you to choose your table from the worksheet. Select the worksheet click “OK”. You will now see both the tables from the cars and trucks worksheets in the Queries toolbar. Clicking on either table will display the data contained in that worksheet.

Displaying Power Query Menu for Cars and Trucks

Appending the Data Tables

Once you’ve done all the preparation, combining the data tables is actually quite simple. Click onto the “cars” table, and in the toolbar select “Append Queries” within the “Combine” section.

The Append window will pop up and prompt for a table that you wish to join to your selected table. Remember that you are on the “cars” table and appending the “trucks” table to it. Click on the trucks table under “Table to append” and choose “OK”

Appending Data Sets in Power Query for Excel

Here is the result:

Appended Power Query Table for Excel

Notice that all the car data and truck data are together on the same table. The data sets are now joined! Also notice the Power Query has created a new “step” in your list, an “Appended Query” step.

Loading the Data to Your Worksheet

The last thing to do is take this data stored on the Power Query editor and load it onto your worksheet.

In the top left corner click on “Close & Load” to place the newly created table onto the Vehicles sheet in table format. Upon clicking, the following will happen:

  • The editor will save your Query steps and exit
  • The Workbook will appear with the data loaded as an Excel Table
  • Excel will also open the Workbook Queries menu on the right side of your sheet

Completed Excel Table from Power Query Upload

You’re ready to work with your brand new table, all without ever opening up the worksheets.

More Things You Can Do With Microsoft Excel

Now that you’ve learned how to append data using Power Query you have a powerful new tool to simplify data. Now that data is loaded into Excel to use you can work with it just like any table. You can create graphs and charts from Excel tables

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or summarize data using Pivot Tables

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How to Import Excel Data Into Python Scripts Using Pandas

Microsoft Excel is the most widely-used spreadsheet software in the world, and for good reason: the user-friendly interface and powerful built-in tools make it simple to work with data.

But if you want to do more advanced data processing, you’ll need to go beyond Excel’s capabilities and start using a scripting/programming language like Python. Rather than manually copying your data into databases, here’s a quick tutorial on how to load your Excel data into Python using Pandas.

Note: If you’ve never used Python before, this tutorial may be a tad difficult. We recommend starting with these websites for learning Python

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and these basic Python examples to get you started

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What Is Pandas?

Python Data Analysis Library (“Pandas”) is an open-source library for the Python programming language that’s used for data analysis and data manipulation.

Pandas loads data into Python objects known as Dataframes, which store data in rows and columns just like a traditional database. Once a Dataframe is created it can be manipulated using Python, opening up a world of possibilities.

Installing Pandas

Note: You must have Python 2.7 or later to install Pandas.

To begin working with Pandas on your machine you will need to import the Pandas library. If you’re in search of a heavyweight solution you can download the Anaconda Python Distribution, which has Pandas built-in. If you don’t have a use for Anaconda, Pandas is simple to install in your terminal.

Pandas is a PyPI package, which means you can install using PIP for Python via the command line. Modern Mac systems come with PIP. For other Windows, Linux, and older systems it’s easy to learn how to install PIP for Python

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Once you’ve opened your terminal, the latest version of Pandas can be installed using the command:

>> pip install pandas

Pandas also requires the NumPy library, let’s also install this on the command line:

>> pip install numpy

You now have Pandas installed and ready to create your first DataFrame!

Prepping the Excel Data

For this example, let’s use a sample data set: an Excel workbook titled Cars.xlsx.

Excel Table For Python Pandas

This data set displays the make, model, color, and year of cars entered into the table. The table is displayed as an Excel range. Pandas is smart enough to read the data appropriately.

This workbook is saved to the Desktop directory, here is the file path used:


You will need to know the file path of the workbook to utilize Pandas. Let’s begin by opening up Visual Studio Code to write the script. If you don’t have a text editor, we recommend either Visual Studio Code or Atom Editor

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Writing the Python Script

Now that you have your text editor of choice, the real fun begins. We’re going to bring together Python and our Cars workbook to create a Pandas DataFrame.

Importing the Python Libraries

Open your text editor and create a new Python file. Let’s call it

In order to work with Pandas in your script, you will need to import it into your code. This is done with one line of code:

import pandas as pd

Here we are loading the Pandas library and attaching it to a variable “pd”. You can use any name you would like, we are using “pd” as short for Pandas.

To work with Excel using Pandas, you need an additional object named ExcelFile. ExcelFile is built into the Pandas ecosystem, so you import directly from Pandas:

from pandas import ExcelFile

Working With the File Path

In order to give Pandas access to your workbook, you need to direct your script to the location of the file. The easiest way to do this is by providing your script with the full path to the workbook.

Recall our path in this example: /Users/grant/Desktop/Cars.xlsx

You will need this file path referenced in your script to extract the data. Rather than referencing the path inside of the Read_Excel function, keep code clean by storing the path in a variable:

Cars_Path = '/Users/grant/Desktop/Cars.xlsx'

You are now ready to extract the data using a Pandas function!

Extract Excel Data Using Pandas.Read_Excel()

With Pandas imported and your path variable set, you can now utilize functions in the Pandas object to accomplish our task.

The function you will need to use is appropriately named Read_Excel. The Read_Excel function takes the file path of an Excel Workbook and returns a DataFrame object with the contents of the Workbook. Pandas codes this function as:


The “path” argument is going to be the path to our Cars.xlsx workbook, and we have already set the path string to the variable Cars_Path.

You’re ready to create the DataFrame object! Let’s put it all together and set the DataFrame object to a variable named “DF”:

DF = pd.read_excel(Cars_Path)

Lastly, you want to view the DataFrame so let’s print the result. Add a print statement to the end of your script, using the DataFrame variable as the argument:


Time to run the script in your terminal!

Running the Python Script

Open your terminal or command line, and navigate to the directory which houses your script. In this case, I have “” located on the desktop. To execute the script, use the python command followed by the script file:

Python Script In Terminal

Python will pull the data from “Cars.xlsx” into your new DataFrame, and print the DataFrame to the terminal!

Python DataFrame In Terminal

A Closer Look at the DataFrame Object

At first glance, the DataFrame looks very similar to a regular Excel table. Pandas DataFrames are easy to interpret as a result.

Your headers are labeled at the top of the data set, and Python has filled in the rows with all your information read from the “Cars.xlsx” workbook.

Notice the leftmost column, an index starting at 0 and numbering the columns. Pandas will apply this index to your DataFrame by default, which can be useful in some cases. If you do not want this index generated, you can add an additional argument into your code:

DF = pd.read_excel(Cars_Path, index=False)

Setting the argument “index” to False will remove the index column, leaving you with just your Excel data.

Doing More With Python

Now that you have the ability to read data from Excel worksheets, you can apply Python programming any way you choose. Working with Pandas is a simple way for experienced Python programmers to work with data stored in Excel Workbooks.

The ease with which Python can be used to analyze and manipulate data is one of the many reasons why Python is the programming language of the future

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Image Credit: Rawpixel/Depositphotos

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How to Import Data from Another Google Sheet

Google Sheets Logo

Should you need to import data from another spreadsheet in Google Sheets, you can do it a couple of ways. Whether you want to pull the data from another sheet in the file or an entirely different spreadsheet, here’s how.

Import Data from Another Sheet

This first method requires you to have more than one sheet inside of a document. You can see whether your document has more than one sheet by looking at the bottom of the page. And to add another one, just hit the plus sign (+) to create a new one.

Multiple sheets inside of a document are located at the bottom of the page.

Fire up your browser, head to Google Sheets, and open up a spreadsheet. Click and highlight the cell where you want to import the data.

RELATED: The Beginner’s Guide to Google Sheets

Click an empty cell where you want the data to go.

Next, you need to type in a formula that references the cell from the other sheet. If your sheets are named, you will want to put its name in place of <SheetName> and the cell you want to reference after the exclamation mark. It should look something like this:


Type = followed by the name of the sheet and the cell you want to import.

Hit the “Enter” key and the data from the other sheet will show up in that cell.

Like magic, the cell gets populated with the data.

Import Data from Another Document

In addition to importing data from a sheet within a spreadsheet, you can reference cell(s) from a completely different document. The formula is slightly modified from the previous one but works almost identically.

RELATED: How to Import an Excel Document into Google Sheets

Fire up the document you want to import data from and write down the range of cells to reference. For this guide, we want the range A22:E27.

Write down the cell range you want to import. We are using A22:E27 for this guide.

Next, copy the complete URL of the spreadsheet to the clipboard. Click the address bar, and then use the keyboard shortcut Ctrl+C (Windows/Chrome OS) or Cmd+C (macOS).

Select and copy the URL to your clipboard.

Now, head back to the Google Sheets home page and open the spreadsheet where you want to import the data.

Click on an empty cell and type =IMPORTRANGE("<URL>" , "<CellRange>") , where <URL> is the link you copied and <CellRange> denotes the cells you want to import that you wrote down. Paste the URL between the quotation marks by pressing Ctrl+V (Windows/Chrome OS) or Cmd+V (macOS), type in the range, and then hit Enter. It should look like this:

=IMPORTRANGE("" , "A22:E27")

Note: If you have more than one sheet in the other document, you must specify which one you want to reference. For example, if you’re importing from Sheet2, you would type “Sheet2!A22:E27” instead.

Hit Enter and you should see the error “#REF!”. This is normal, Google Sheets just needs you to allow it access to the other sheet. Select the cell with the error and then click “Allow Access.”

Allow your spreadsheet to access the other one and click "Allow Access."

It should take a couple of seconds to load, but when it’s finished, the data range will import everything directly into your spreadsheet.

Again, like magic, all the data from the range of cells is imported into your document.

Although cell formatting—such as colors—doesn’t follow data over when importing from other sheets, these are the best ways to reference external cells in Google Sheets.

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Dive Into Big Data With This Huge MATLAB and LabVIEW Training Bundle

Over the next decade, biotechnology and computer science are likely to shape our world. Artificial brains will take decisions and smart cities will run themselves. But to make that happen, someone needs to build programs and algorithms for analyzing vast amounts of data. If you want to dive into this lucrative niche, the Essential MATLAB & LabVIEW Mega Bundle is a great place to start. The bundle contains nine courses, covering some of the key development tools used by programmers, engineers and scientists. Right now, you can get the training for $29 at MakeUseOf Deals.

MATLAB, LabVIEW, and More

There are many frameworks for building algorithms and simulations. But in the scientific community, MATLAB and LabVIEW are usually favored. To break into biotech or design the future, it’s a good idea to know the tools.

This bundle gives you a comprehensive education. Through 342 video tutorials, you learn how to build advanced algorithms, data simulations and visualizations, and GUIs. You don’t need any previous experience with code, and each of the nine courses provides plenty of hands-on practice.

Along the way, you will learn to build data models with Simulink, connected systems with labVIEW, and polished user-facing apps with MATLAB.

62 Hours for $29

Order now for $29 to get lifetime access to all 62 hours of video instruction, worth $1,800.

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