We use Indexing and Slicing to access the values of a tensor.Indexing is used to access the value of a single element of the tensor, whereasSlicing is used to access the values of a sequence of elements.We use the assignment operator to modify the values of a tensor. Assigning new value/s using the assignment operator will modify the tensor with new value/s.StepsImport the required libraries. Here, the required library is torch.Define a PyTorch tensor.Access the value of a single element at particular index using indexing or access the values of sequence of elements using slicing.Modify the accessed values with new ... Read More

A PyTorch tensor is an n-dimensional array (matrix) containing elements of a single data type. A tensor is like a numpy array. The difference between numpy arrays and PyTorch tensors is that the tensors utilize the GPUs to accelerate the numeric computations. For the accelerated computations, the images are converted to the tensors.To convert an image to a PyTorch tensor, we can take the following steps −StepsImport the required libraries. The required libraries are torch, torchvision, Pillow.Read the image. The image must be either a PIL image or a numpy.ndarray (HxWxC) in the range [0, 255]. Here H, W, and ... Read More

To add single quotes to strings in an R data frame column, we can use paste0 function. This will cover the strings with single quotes from both the sides but we can add them at the initial or only at the last position.To add them on both the sides, we can use the following syntax −Data_frame$Column

To change the name of single column using setNames, we would need to specify the column name that needs to be changed.For example, if we have a data frame called df that contains three columns say Var1, var2, and Var3 and we want to change var2 to Var2 then we can use the command as follows −setNames(df,replace(names(df),names(df)=="var2","Var2"))Example 1Following snippet creates a sample data frame −x

When we write a long number in R, by default the printed output of that number is in scientific notation. To stop this printing behavior we can use sprint function.For example, if we have a data frame called df that contains a column say X having long numbers then we can stop printing of these numbers in scientific notation by using the below given command −df$X

Sometimes a variable has a character associated with the numerical values such as variable name etc. If we want to associate a character to numbers then paste0 function can be used.For example, if we have a data frame called df that contains a column say X then we can associate X to each value in the column by using the command given below −df$X

To remove only the first duplicate row by group, we can use filter function of dplyr package with duplicated function.For example, if we have a data frame called df that contains a grouping column say Grp then removal of only first duplicate row by group can be done by using the below command as follows −df%>%group_by(Grp)%>%filter(duplicated(Grp)|n()==1)Example 1Following snippet creates a sample data frame −Group

If we have string data stored in R data frame columns then we might want to sort the data frame rows in alphabetical order. This can be done with the help of apply and sort function inside transpose function.For example, if we have a data frame called df that contains string data then sorting of df in alphabetical order can be done by using the below given command −t(apply(df,1,sort))Example 1Following snippet creates a sample data frame −x1

To find the percentage of missing values in each column of an R data frame, we can use colMeans function with is.na function. This will find the mean of missing values in each column. After that we can multiply the output with 100 to get the percentage.Check out the below given examples to understand how it can be done.Example 1Following snippet creates a sample data frame −x1

To count the number of times a value occurs in a column of an R data frame, we can use table function for that particular column.For example, if we have a data frame called df that contains a column say Response then finding the number of times a value occurs in Response can be found by using the command given below −table(df$Response)Example 1Following snippet creates a sample data frame −x