Loop a multidimensional array and only print two specific column values per row

Using a foreach loop without a key: foreach($array as $item) { echo $item[‘filename’]; echo $item[‘filepath’]; // To know what’s in $item echo ‘<pre>’; var_dump($item); } Using a foreach loop with a key: foreach($array as $i => $item) { echo $array[$i][‘filename’]; echo $array[$i][‘filepath’]; // $array[$i] is same as $item } Using a for loop: for ($i … Read more

Multidimensional associative arrays in Bash

You can’t do what you’re trying to do: bash arrays are one-dimensional $ declare -A PERSONS $ declare -A PERSON $ PERSON[“FNAME”]=’John’ $ PERSON[“LNAME”]=’Andrew’ $ declare -p PERSON declare -A PERSON='([FNAME]=”John” [LNAME]=”Andrew” )’ $ PERSONS[1]=([FNAME]=”John” [LNAME]=”Andrew” ) bash: PERSONS[1]: cannot assign list to array member You can fake multidimensionality by composing a suitable array index … Read more

Two dimensional array in python

You do not “declare” arrays or anything else in python. You simply assign to a (new) variable. If you want a multidimensional array, simply add a new array as an array element. arr = [] arr.append([]) arr[0].append(‘aa1’) arr[0].append(‘aa2’) or arr = [] arr.append([‘aa1’, ‘aa2’])

Axes from plt.subplots() is a “numpy.ndarray” object and has no attribute “plot”

If you debug your program by simply printing ax, you’ll quickly find out that ax is a two-dimensional array: one dimension for the rows, one for the columns. Thus, you need two indices to index ax to retrieve the actual AxesSubplot instance, like: ax[1,1].plot(…) If you want to iterate through the subplots in the way … Read more

How do you extract a column from a multi-dimensional array?

>>> import numpy as np >>> A = np.array([[1,2,3,4],[5,6,7,8]]) >>> A array([[1, 2, 3, 4], [5, 6, 7, 8]]) >>> A[:,2] # returns the third columm array([3, 7]) See also: “numpy.arange” and “reshape” to allocate memory Example: (Allocating a array with shaping of matrix (3×4)) nrows = 3 ncols = 4 my_array = numpy.arange(nrows*ncols, dtype=”double”) … Read more