Add Numpy Array To Pandas Dataframe

Here we will create a two-dimensional numpy array with different data types and convert it into a dataframe. These rows and columns of the 2D Numpy Array will be the rows and columns of the pandas Dataframe. Another important type of object in the pandas library is the DataFrame. This object is similar in form to a matrix as it consists of rows and columns.

Both rows and columns can be indexed with integers or String names. One DataFrame can contain many different types of data types, but within a column, everything has to be the same data type. The NumPy library contains multidimensional array and matrix data structures (you'll find more information about this in later sections).

It providesndarray, a homogeneous n-dimensional array object, with methods to efficiently operate on it. NumPy can be used to perform a wide variety of mathematical operations on arrays. Here we are going to consider an two dimensional numpy array and convert into a Dataframe.

We can convert to dataframe by using these rows and columns. So far, we have learned in our tutorial how to create arrays and how to apply numerical operations on numpy arrays. If we program with numpy, we will come sooner or later to the point, where we will need functions to manipulate the shape or dimension of arrays. Furthermore, we will demonstrate the possibilities to add dimensions to existing arrays and how to stack multiple arrays.

We will end this chapter by showing an easy way to construct new arrays by repeating existing arrays. It first creates a random array of size with 4 rows and 3 columns. We then pass the array as an argument to the pandas.DataFrame() method, which generates DataFrame named data_df out of the array. By default, the pandas.DataFrame() method will insert default column names and row indices.

If you want to learn more about C and Fortran order, you canread more about the internal organization of NumPy arrays here. Essentially, C and Fortran orders have to do with how indices correspond to the order the array is stored in memory. In Fortran, when moving through the elements of a two-dimensional array as it is stored in memory, the firstindex is the most rapidly varying index. As the first index moves to the next row as it changes, the matrix is stored one column at a time. This is why Fortran is thought of as a Column-major language. In C on the other hand, the last index changes the most rapidly.

The matrix is stored by rows, making it a Row-major language. What you do for C or Fortran depends on whether it's more important to preserve the indexing convention or not reorder the data. In the above code we have imported the numpy and pandas library and then initialize an array. Now by using the pd.dataframe() function, we can easily add numpy arrays in dataframe.

Firstly we imported the numpy library and then initialize an array by using the np.array() function. After that, with the np.vstack() function we added one-dimensional array 'add_row' in it. Once you will print 'result' then the output will display new array elements.

Additionally, you've learned how to convert pandas dataframe with column names and indexes. Also, you've learned how to convert NumPy arrays with different column types to a dataframe and convert the column types of the column in the dataframe. In this section, you'll learn how to convert Numpy array to pandas dataframe without using any additional options such as column names or indexes.

NumPy is an open source library available in Python, which helps in mathematical, scientific, engineering, and data science programming. It is a very useful library to perform mathematical and statistical operations in Python. It works perfectly for multi-dimensional arrays and matrix multiplication. As you learned previously in this chapter, you can manually define numpy arrays as needed using the numpy.array() function. However, when working with larger datasets, you will want to import data directly into numpy arrays from data files (such as .txt and .csv). We have row indices and column names in the NumPy array itself.

Similarly, we select all the first row values from the second column and pass it as columns argument to set the column names. NumPy arrays are unique in that they are more flexible than normal Python lists. They are called ndarrays since they can have any number of dimensions . They hold a collection of items of any one data type and can be either a vector (one-dimensional) or a matrix (multi-dimensional).

NumPy arrays allow for fast element access and efficient data manipulation. In Python the numpy.add() function is used to add the values or elements in numpy arrays. It will check the condition if the shape of two numpy arrays is not the same then the shapes must be broadcastable to a common shape. First we will create an two dimensional numpy array for a range of integers using arange() function with 2 rows and 5 columns. In this section, you'll learn how to convert NumPy array to pandas dataframe with column names.

We can use numpy ndarray tolist() function to convert the array to a list. If the array is multi-dimensional, a nested list is returned. For one-dimensional array, a list with the array elements is returned.

You can easily create new numpy arrays by importing numeric data from text files (.txt and .csv) using the loadtxt() function from numpy . Here, by "aligned" we mean that they share the same index. There are different ways to fill a DataFrame such as with a CSV file, a SQL query, a Python list, or a dictionary. Here we have created a DataFrame using a Python list of lists. Each nested list represents the data in one row of the DataFrame. We use the keyword columns to pass in the list of our custom column names.

NumPy gives you an enormous range of fast and efficient ways of creating arrays and manipulating numerical data inside them. While a Python list can contain different data types within a single list, all of the elements in a NumPy array should be homogeneous. The mathematical operations that are meant to be performed on arrays would be extremely inefficient if the arrays weren't homogeneous. In Python, the np.stack() is used for adding new elements row-wise in an array.

For example, suppose we have a list that contains integer values. Now we have to add those lists into np.vstack() function and it will return into numpy array. To convert a numpy array to pandas dataframe, we use pandas.DataFrame() function of Python Pandas library.

As needed, you can also import text files with text string values to numpy arrays using the genfromtxt() function from numpy. We pass the numpy array into the pandas.DataFrame() method to generate Pandas DataFrames from NumPy arrays. We can also specify column names and row indices for the DataFrame. We can create a data frame using the Pandas library or we can import an already built data frame (.csv file) and work on it.

If a dictionary is sent in, the keys may be used as the indices. A vector is an array with a single dimension (there's no difference between row and column vectors), while a matrix refers to an array with two dimensions. For 3-D or higher dimensional arrays, the termtensor is also commonly used. In the above example, we have defined two numpy arrays by using the np.array() function and we need to add these arrays to the dictionary. The first array will be considered a key to the dictionary and the second array items will be considered as values.

After that, we have declared a variable 'result' and assigned the zip() function for returning the iterator. In this function, we have to take the same size of arrays with the same number of rows and columns. If we are going to use the same size arrays in numpy.add() function than the second array elements add with the first array elements easily. In this section, you'll learn how to convert object type NumPy array which has different types of data in each column to a pandas dataframe.

Use the below snippet to convert the NumPy array to pandas dataframe with column names. You can convert NumPy Array to pandas dataframe with column names using the attribute columns and passing the column values as a list. By default, when we use the axis parameter, the np.sum function collapses the input from n dimensions and produces an output of lower dimensions.

For example, in a 2-dimensional NumPy array, the dimensions are the rows and columns. Again, we can call these dimensions, or we can call them axes. You can convert DataFrame into numpy array by using to_numpy() method. This returns object of type Numpy ndarray and It accepts threeoptionalparameters. Here we can see how to add numpy arrays in Python Pandas dataframe.

To do this task we are going to apply the np.vstack() method for adding the new row in an existing array. In Python, this function is used to add the sequence of input arrays row-wise and make them in a one-dimensional array. By using the numpy.add() function, we can easily solve this problem and get the solution of the addition of two arrays. In Python, the numpy.add() function is used to add the values or elements in numpy arrays. To convert Pandas DataFrame to Numpy Array, use the function DataFrame.to_numpy(). To_numpy() is applied on this DataFrame and the method returns object of type Numpy ndarray.

You can specify index, column and dtype as well to convert numpy.ndarray to dataframe. The numpy ndarray class is used to represent both matrices and vectors. To construct a matrix in numpy we list the rows of the matrix in a list and pass that list to the numpy array constructor. NumPy provides a suite of logical operations that can operate on arrays. Many of these map logical operations over array entries in the same fashion as NumPy's mathematical functions.

These functions return either a single boolean object, or a boolean-type array. Now let's compare this to the time required to explicitly loop over the array in Python and tally up the sum. There are also mathematical operations which are designed to operate on sequences of numbers, such as the sum function. Is an at least two-dimensional numpy.ndarray, then the first (left-most) index corresponds to row number and the second index corresponds to column number . Higher dimensions get absorbed in the shape of each table cell.

Is a one-dimensional numpy.ndarray then it is treated as a single row table where each element of the array corresponds to a column. You now know how to import data from text files into numpy arrays, which will come in very handy as you begin to work with scientific data. Notice that the data from the .csv file has been imported as a two-dimensional array , contained within two set of brackets [].

You can also use np.loadtxt to import data from .csv files that contain rows and columns of data. Import data from text files (.txt, .csv) into numpy arrays. We can also set the column names and row indices using the index and columns parameter of the pandas.DataFrame() method.

Further, we can also change the data type of columns in a data frame. Considering our second data frame, it consists of some integer values and some floating values, let's try to change all of them to float. NumPy arrays are faster and more compact than Python lists. NumPy uses much less memory to store data and it provides a mechanism of specifying the data types. In the above code we have imported the numpy library and then create an array by using the np.array() function. Now our task is to add the last 2 elements with the first 2 elements.

In the above code, we have used the numpy.add() function and assign the arrays as an argument. Once you will print 'result' then the output will display the newly added elements in an array. Now use the numpy.insert() function and assign the axis, array, and index number as an argument. Once you will print 'new_output' then the output will display the newly added column elements in a given array. In the above code the numpy.add() function is adding the elements of 'array 1' to another numpy array 'array2'. Once you will print 'result' then the output will display the adding elements in an array.

Run df.to_numpy() statement converts the dataframe to numpy array and returns the numpy array. Now, we will convert this into pandas dataframes of float and integer types and integer type. If you don't pass any other arguments apart from data, you will get DataFrame of ndarray type,so this is how you can convert numpy.ndarray to dataframe. In this section, you'll learn how to concatenate the NumPy array to the existing pandas dataframe. This is also known as adding a NumPy array to pandas dataframe.

In this section, you'll learn how to convert NumPy array to pandas dataframe with index. In this tutorial, you'll learn the different methods available to create pandas dataframe from the NumPy Array. Numpy.arange() is an inbuilt numpy function that returns an ndarray object containing evenly spaced values within a defined interval. For instance, you want to create values from 1 to 10; you can use np.arange() in Python function. Basically, we're going to create a 2-dimensional array, and then use the NumPy sum function on that array.

Apple Watch Series 6 Deals

One of the best smartwatches out there, the Apple Watch Series 6 is an utterly gorgeous looking device. It oozes class and is sure to turn heads when you're at the gym or on a date. Packed full of features, its Always-On Retina display is 2.5 times brighter outdoors when your wrist is down so it looks great. Other features include the ability to track all your workouts and daily activities so you always know what's going on. Save $100 – Today's best Cyber Monday deal is the best-selling Apple Watch 6 that's on sale for just $299.

That's the best deal we've seen in months, and $50 less than the Black Friday price. The 40mm GPS-equipped Apple Watch features a new S6 processor, blood oxygen monitoring, an ECG app, and elevation tracking. Note that this Cyber Monday discount applies to the Red sport band, which is the only color currently in stock. The Apple Watch Series 6 remains a fantastic option for the vast majority of users, butd this Apple Watch Series 7 deal is even more attractive. Basically, with its latest technology, you will be incredibly happy with the Apple Watch Series 7, a it has everything you could need.

At its simplest, it has a GPS so it can track all your walks and workouts, knowing exactly where you've been. It also has the ability to measure your blood oxygen level via a new sensor and app, as well as check how your heart rhythm is doing via an ECG app. That's alongside ordinary activity tracking such as steps, calories, heart rate, and altitude. It's ideal for the active lifestyle tracking everything you do while rewarding you for good performance or beating your previous records. Black Friday sales have kicked off early, but great Apple deals are a challenge to find even during the biggest sales season of the year.

The Apple Watch, however, is one of the few Apple products we do regularly see on sale during Black Friday. Usually, there are smaller Black Friday discounts on the flagship smartwatch model that Apple released in September and better sales on Apple's budget Apple Watches. Series 7 sales haven't materialized yet—and confusing matters, this year there are two budget Apple Watches on sale, the Apple Watch SE and the even cheaper Apple Watch Series 3. But despite rock-bottom prices on the Series 3, only the SE is worth your time. The Huawei Band 6 fitness tracker comes with a 1.47-inch AMOLED screen along with an SpO2 sensor, a heart-rate monitor and 14 days of battery life. The fitness band also features 5ATM water resistance and is available in four colours – black, green, pink and red.

There's the option to measure your blood oxygen level via a new sensor, track your heart rate and rhythm via an ECG function, plus you'll receive notifications any time something seems wrong or unusual. It's possible to track all your workouts here with new support for tai chi and Pilates, as well as regular favorites. The Mindfulness app also helps you keep in the moment a little more. Alternatively, listen to your favorite music or podcasts via automatic syncing. It all combines to create a watch that feels like a replacement to your phone but all on your wrist, saving you the need to carry even more devices.

However, this smartwatch is mostly an incremental upgrade from its predecessor. It maintains the same 18-hour battery life and it adds no new health features. But the enlarged display is a game-changer and makes it difficult to return to previous-generation models. The Series 7's big screen adapts wearable computing for more everyday applications, making it practical to be productive from your wrist. It offers GPS, an optical heart sensor, a stylish retina display, plus swim proofing for when you want to hit the pool. The Apple Watch SE is the lower-priced cousin to the more expensive versions of the Apple Watch and comes with everything you need in a smartwatch, with only a couple of small exclusions.

It has the same great design as the Apple Watch Series 6, has sleep tracking and a large suite of fitness and health tracking options, and has the same processor as the Apple Watch Series 5. Sure, it's not the latest processor around, but it's still more than good enough to offer reliable, zippy performance. Following the release of the Apple Watch Series 7, shoppers might be looking for the next best thing.

The device enables you to track your blood oxygen as well as your workouts. The always-on retina display has been updated, as it's now 2.5 times brighter outdoors to help you see when you've hit your targets. Plus it's powered by a faster S6 64-bit dual-core processor. Stretch your budget a little further and the Apple Watch SE is a great option. It's really stylish looking and comfortable, while packing in plenty of features. Up to two times faster than the Apple Watch Series 3, it's speedy to use plus it has a large Retina OLED display that looks fantastic.

Other features include built-in GPS, high and low heart rate notifications, plus a heads up if an irregular heart rhythm is detected. More everyday features include the ability to track your daily activities, measure workouts, and receive notifications and calls straight to your wrist. It's the kind of device that works jut as well in the evenings when you don't want to dig out your phone as it does when you're hitting the gym. The Apple Watch Series 7 is the latest Apple Watch and it's amazing, topping our list of the best smartwatches.

It might only be modestly discounted by $10, but it's worth every cent thanks to only recently being launched, so any Apple Watch Series 7 deal is a good one. Compared to the Series 6, you gain nearly 20% more screen area via its Always-On display which makes everything much easier to see and use. That display is also the most crack-resistant display yet on an Apple Watch with IPX6 dust resistance and a swim-proof design. It's capable of surviving so much more than earlier models, which is great for the more rugged explorer. As always, it'll track all your steps, calories burned, altitude, and much more while you're walking or working out, so it's ideal for competing with yourself or friends who also own an Apple Watch.

In addition, the Apple Watch Series 7 has a gorgeous always-on retina display that's 2.5 times brighter outdoors when your wrist is down than most previous models. It makes a huge difference when you're looking at it with the watch constantly feeling ready for action. It's speedy, too, thanks to a fast processor that means you can negotiate its menus super fast and efficiently. Other features include the ability to sync your favorite music and podcasts, as well as receive all your notifications to your wrist. It'll even encourage you to be more mindful with regular breathing exercises available through the watch. A few features have been removed to enable that lower price, of course.

There's no always-on display, and it won't get all the advanced options, like the electrocardiogram or blood oxygen monitors, available on the more expensive Apple Watches. But it has a two-day battery life and all the smartwatch features most people are going to need. At this price, it's an excellent way to dip an unsure toe into the smartwatch pool. Going with theApple Watch Series 6doesn't mean you're going to be sacrificing too much.

Aside from the main improvements of a refreshed case and larger screen, the Series 6 and 7 share thesame processor alongside a matching array of blood oxygen, heart rate, and other fitness sensors. So for those who don't need the latest and greatest or don't want to pay more cash for Series 7, going with the Apple Watch Series 6 delivers plenty of savings in the meantime. The feature-richApple Watch 6tracks activity, workouts, and calories and includes a sleep app that helps you establish a regular bedtime routine to get a better night's rest. The Series 6 also comes with new health features such as blood oxygen monitoring and an ECG app that alerts you when an irregular heart rate is detected. The waterproof smartwatch still keeps you connected with the ability to take calls and reply to texts directly from your wrist. Aside from the main improvements of a refreshed case and larger screen, theSeries 6and 7 share the same processor and a matching array of blood oxygen, heart rate, and other fitness sensors.

So for those who don't need the latest and greatest or don't want to wait for a more sizable discount on Series 7, going with the Apple Watch Series 6 delivers plenty of savings in the meantime. While it's no longer officially a part of Apple's wearable lineup, you can still buy the Apple Watch Series 6 at several retailers. The Apple Watch comes in two sizes, 40mm and 44mm, which start at $399 and $429, respectively. We'll likely see small discounts for the Series 7 this holiday season. Due to increased costs driven by global supply-chain issues, you shouldn't anticipate huge price drops or even the quality of discounts we saw for the Series 6 last year.

The Series 7 is our top Apple Watch pick and offers features the SE doesn't have, such as an always-on display, blood-oxygen measurement, ECG, more crack-resistant glass, and faster charging. If you're upgrading from an older model and want the special features or have the cash, the Series 7 is still the model to get—you just might not see huge Black Friday discounts for it. The fitness features is where the Series 6 really shows off its skill set.

The Series 6 allows you to measure your heart rhythm with the ECG app and your blood oxygen, also known as SpO2 tech. The SpO2 has an all-new red light sensor that monitors the colour of your blood and the level of oxygen in it, and uploads this information to the Apple Health app. You can also track your daily activity, altitude and measure a selection of workouts, including running, cycling, swimming and yoga. For a more in-depth review, read T3's Apple Watch Series 6 review.

The best-sellingApple Watch 6tracks activity, workouts, and calories, and includes a sleep app that helps you establish a regular bedtime routine to get a better night's rest. The Series 6 also comes with new health features such as blood oxygen monitoring and an ECG app, which alerts you when an irregular heart rate is detected. You're also able to take calls, get directions and reply to texts directly from your wrist without your phone.

Starting Apple Watch Series 6 pricing remains the same as the Series 5 with 40mm GPS models with an aluminum case and sport band ringing in at $399. Shoppers can also elect to purchase a larger 44mm Apple Watch 6, with retail prices as low as $429. Individuals looking for cellular connectivity can also pick up a Wi-Fi + Cellular Apple Watch, with prices for the upgraded styles starting at $499. While all of the Apple Watch models and colorways covered here are encased in aluminum, Apple does make a more premium range built out of stainless steel and titanium. These offerings have similar designs to their aluminum counterparts, with slightly refined colors and finishings — polished for the stainless steel, brushed for the titanium.

However, they start at much steeper prices of $749 and above, and they are functionally the same, save for some exclusive digital watch faces Apple reserves for these premium models. Overall, the upmarket stainless, titanium, and Hermès edition Apple Watches also don't usually get the discounts and sales as the aluminum models. Despite its entry-level status, the Apple Watch Series 3 is still an excellent smartwatch. It offers many of the same features found in the newer models like solid fitness tracking, a water proof design, and Apple Music streaming capabilities. The major trade-offs are that you get a slightly dated design and you don't get access to the ECG app, which measures the electrical activity of your heart.

The Apple Watch 3 is a great fitness tracker and smartwatch for those on a budget. The waterproof watch offers heart rate notifications, workout detection, Apple Music, and Siri support for a low price. It's now $40 under the Apple Store's price, but hurry, as this model goes in and out of stock.

Like the Series 6, the Series 7 features a blood oxygen sensor and an EKG function designed to detect unusual heart rhythms. The Series 7 ships with a new cable that allows for faster charging. Sean Riley has been covering tech professionally for over a decade now. Most of that time was as a freelancer covering varied topics including phones, wearables, tablets, smart home devices, laptops, AR, VR, mobile payments, fintech, and more. Sean is the resident mobile expert at Laptop Mag, specializing in phones and wearables, you'll find plenty of news, reviews, how-to, and opinion pieces on these subjects from him here.

We strive to help our readers find the best deals on quality products and services, and we choose what we cover carefully and independently. The prices, details, and availability of the products and deals in this post may be subject to change at anytime. Be sure to check that they are still in effect before making a purchase. Smartwatches are one of the newest and biggest fitness crazes, with their incredible ability to monitor your heart rate, track your workout and measure your sleep patterns. With so many smartwatches to choose from – especially from Apple – it's important to consider which is the right model for you and your lifestyle.

It comes with upgrades like the S6 processor and new sensors for blood oxygen monitoring and better sleep tracking. The Series 6 is made of 100% recycled aluminum that comes in gold, graphite, blue and Red finishes. It includes a rebranded fitness app with new workouts and a handwashing feature. The first Apple Watch deals on the new Series 7 are here.

It features a larger/brighter display, better durability , and up to 33% faster charging. 1.39-inch AMOLED Sapphire display along with a ceramic back. Along with all fitness-oriented features like heart-rate monitoring, the watch also supports tracking for various winter events like skiing and snowboarding. Other features include Bluetooth calling, and 2 weeks of battery life. The best priced Apple Watch you can currently buy is the Series 3, which is under £200 at the majority of retailers.

This version is your best bet for a decent deal during the Christmas shopping period. The Apple Watch 3 remains a component smartwatch today, but with the Apple Watch SE available for $80 more , there's almost no reason to choose it in 2021. Apple spiced up things in the wearable district by introducing not one but two new models last year, and also in different price segments. The Apple Watch Series 6 is undoubtedly the high-tier device most people would aim for, but the Watch SE can offer an amazing value to those on a budget or upgrading from much older generations.

Carriers and big retailers now offer price promos and package deals just in time for Valentine's day. Now, if you're already sold on the idea of owning an Apple Watch or you want to upgrade, but you don't know where to start from, here are the best Apple Watch deals right now. To start off the week, Woot is now launching a 1-day refurbished Apple sale, discounting a selection of iPhones and Apple Watch models starting at $140.

Shipping is free for Prime members, with a $6 fee applying otherwise and everything is slated to arrive by Christmas. Leading the way is theApple Watch Series 6 44mm GPS at$349.99in a variety of styles. Down from $429, you're looking at $79 in savings alongside the best price we've seen since Apple released the Series 7 successor earlier this fall.

Just like all of the other discounts today, you'll find a 90-day warranty. Keep an eye on your heart with notifications for high and low heart rate. Apple Watch Series 6 also has great safety features like fall detection, Emergency SOS, and international emergency calling.

As far as materials, display, brightness, water resistance, and connectivity, they're the same watch. In our Apple Watch Series 6 review, we also found the watch's new sleep tracking app to be helpful, although not as insightful as Fitbit's software. In terms of pricing, the 40mm model starts at $399 and the 44mm model starts at $499 .

However, the best Apple Watch deals we've seen on the Series 6 have dropped its price as low as $249. Keep in mind these deals are getting harder to find as stock of Apple's previous-gen watch diminishes. The Series 6 also has the sensor that enables an EKG function designed to detect unusual heart rhythms. Keep in mind that the prices above are for GPS-only models. Adding a cellular connection will cost you about $100 more, plus monthly fees for the service. So it's best to ask yourself if you really need it before you shell out the extra bucks.