# Tag: arrays

## Substitute column values of a dataframe with the corresponding items in an array

I have a column in a dataframe which contains an array of numbers from 1 to 5 and I have an array containing five words. I would like to find the simplest, most compact and most elegant way in Python to “in place” replace the numbers in the column with the corresponding words. For example: I am certain that the

## Python find the unique values in a spesific column. 2d array

Good day. If I have the following array: How can I change the array to only show data from user pear? I want to collect all the values from column 1 of user pear. (12, 14) Or alrternatively how can I find the values that are unique in colum 2, e.g. apples, pear and bannana. And then filter by pear

## How to slice and calculate the pearson correlation coefficient between one big and small array with “overlapping” windows arrays

Suppose I have two very simple arrays with numpy: I would like to find which slice of array reference has the highest pearson’s correlation coefficient with array probe. To do that, I would like to slice the array reference using some sort of sub-arrays that are overlapped in a for loop, which means I shift one element at a time

## Why am I getting TypeError: list indices must be integers or slices and not the float value while finding Median of two sorted arrays?

I have two sorted arrays and I am trying to find median of two sorted arrays.For example,if input is nums1 = [1,3], nums2 =  then the output will median=2.00000 and if the input is p = [1,2], t = [3,4] then the output will be median=2.50000 I have added both the arrays together and sorted them and later by

## New list based on indices from another list in Python

I have an array X and a list A1. I want to create a new list B1 such that it consists of values from X corresponding to indices in A1. For example, the code should pick values from X for indices in A1 and so on…I present the current and expected outputs. The current output is The expected output is

## Transform a 3D numpy array to 1D based on column value

Maybe this is a very simple task, but I have a numpy.ndarray with shape (1988,3). I want to create a 1D array with shape=(1988,) that will have values corresponding to the column of my 3D array that has a value of 1. For example, How can I do this? Answer You can use numpy.nonzero: Output: array([0, 1, 2, 1, 0,

## Geometric series: calculate quotient and number of elements from sum and first & last element

Creating evenly spaced numbers on a log scale (a geometric progression) can easily be done for a given base and number of elements if the starting and final values of the sequence are known, e.g., with numpy.logspace and numpy.geomspace. Now assume I want to define the geometric progression the other way around, i.e., based on the properties of the resulting

## Nested arrays in Avro

I would like to store two-dimensional arrays of numbers in Avro. I have tried the following: But when I tried to read it with the parser: I get the following error: Answer It looks like you have one too many type keys. You schema should be this instead:

## TypeError: unsupported operand type(s) for /: ‘list’ and ‘int’ solution is an array

I solved an equation, the answer is an array. I am trying to use the answer for a new equation. I wrote a sample code to explain my problem! Answer I see you want to “use the answer for a new equation”. The previous equation solution is a, a list with 1 element  then you can use a in

## numpy slicing using multiple conditions where one of the conditions searches the neighborhood of an element

the problem is to take a black-white image, detect all the places where white borders on black, keep that white, and turn all other white pixels black. I know how to do this using normal for-loops and lists, but I want to do it w/ numpy, which I am not that familiar with. Here is what I have so far: