I want to create an empty set up to the value n entered by the user and assign the values in the for loop into this set. But for this, it is necessary to create as many for loops as the user inputs, it is not possible to do this. How can I do it? The code below works correctly,
Tag: indices
Set indices without manually typing them (too many), regular numerical sequences as indices
I have a pandas dataframe with 1111 rows and want to reindex the rows having the following names: First 11 rows: Next 100 rows: next 1000 rows: Additionally, for the last 900 rows, I need the block above, substituting the first 1s (1s after the p) with 2s, next block with 3s, next block with 4s, …, last block with
Create Dataframe by calling indices of df1 that are listed in df2
I’m new to Python Pandas and struggling with the following problem for a while now. The following dataframe df1 values show the indices that are coupled to the values of df2 that should be called df2 contains the values that belong to the indices that have to be called. For example, df1 shows the value ‘0’ in column ‘Name161’. Then
In TensorFlow, how can I get nonzero values and their indices from a tensor with python?
I want to do something like this. Let’s say we have a tensor A. And I want to get nonzero values and their indices from it. There are similar operations in Numpy. np.flatnonzero(A) return indices that are non-zero in the flattened A. x.ravel()[np.flatnonzero(x)] extract elements according to non-zero indices. Here’s a link for these operations. How can I do somthing
Randomly extract x items from a list using python
Starting with two lists such as: I want to have the user input how many items they want to extract, as a percentage of the overall list length, and the same indices from each list to be randomly extracted. For example say I wanted 50% the output would be I have achieved this using the following code: But I was