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Python ndarray

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  1. As with other container objects in Python, the contents of an ndarray can be accessed and modified by indexing or slicing the array (using, for example, N integers), and via the methods and attributes of the ndarray. Different ndarrays can share the same data, so that changes made in one ndarray may be visible in another
  2. numpy.ndarray¶ class numpy.ndarray (shape, dtype=float, buffer=None, offset=0, strides=None, order=None) [source] ¶ An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an integer, a floating point number, or something else, etc.
  3. As with other container objects in Python, the contents of an ndarray can be accessed and modified by indexing or slicing the array (using, for example, N integers), and via the methods and attributes of the ndarray. Different ndarrays can share the same data, so that changes made in one ndarray may be visible in another. That is, an ndarray can be a view to another ndarray, and the data.
  4. Unlike the array class offered by the python standard library, the ndarray from numpy, offers different variants of fundamental types that can be stored. For example, the types int8, int16, int32, int64, float16, float32, float64, complex64, complex128 are all different variants of fundamental types supported by numpy.ndarray , based on the maximum value that can be represented and precision
  5. The most important object defined in NumPy is an N-dimensional array type called ndarray. It describes the collection of items of the same type. Items in the collection can be accessed using a zero-based index. Every item in an ndarray takes the same size of block in the memory. Each element in ndarray is an object of data-type object (called dtype)

In Numpy, number of dimensions of the array is called rank of the array.A tuple of integers giving the size of the array along each dimension is known as shape of the array. An array class in Numpy is called as ndarray. Elements in Numpy arrays are accessed by using square brackets and can be initialized by using nested Python Lists Python Alternative to MATLAB. ndarray- n-dimensional arrays. Fourier transforms and shapes manipulation. Linear algebra and random number generation. Numpy Tutorial - How to Install NumPy? You can use pip to install numpy-pip install numpy Then you can import it as->>> import numpy as np Numpy Tutorial - NumPy ndarray Die Werte werden innerhalb des halb-offenen Intervalles [start, stop) generiert. Wird diese Funktion mit Integer-Werten benutzt, ist sie beinahe äquivalent zu der built-in Python-Funktion range . arange liefert jedoch ein ndarray zurück, während range einen Listen-Iterator zurückliefert

The N-dimensional array (ndarray) — NumPy v1

numpy.ndarray() is a class, while numpy.array() is a method / function to create ndarray. In numpy docs if you want to create an array from ndarray class you can do it with 2 ways as quoted: 1- using array() , zeros() or empty() methods: Arrays should be constructed using array, zeros or empty (refer to the See Also section below) Die klassischen Arrays wie in Java gibt es in Python nicht. Allerdings können Sie sogenannte Listen erstellen, die ähnlich funktionieren. Außerdem können Sie Arrays per Modul nachrüsten, was wir.. A NumPy Ndarray is a multidimensional array of objects all of the same type. It is immensely helpful in scientific and mathematical computing. As such, they find applications in data science, machine learning, and artificial intelligence

numpy.ndarray — NumPy v1.20 Manua

Separator between array items for text output. If (empty), a binary file is written, equivalent to file.write(a.tobytes()). str: Required: format: Format string for text file output. Each entry in the array is formatted to text by first converting it to the closest Python type, and then using format % item. str: Require Beim Datentyp array.array handelt es sich um einen Wrapper für Arrays der Programmiersprache C. Dieses Array kann nur Elemente gleichen Typs enthalten (zum Beispiel nur Integer- oder Float-Werte). Im folgenden Beispiel soll ein Array mit zehn Integer-Werten erstellt werden. Im Gegensatz zur Liste, muss dazu ein type code angegeben werden Varun May 6, 2019 How to get Numpy Array Dimensions using numpy.ndarray.shape & numpy.ndarray.size() in Python 2019-05-06T07:55:11+05:30 Numpy, Python No Comment In this article we will discuss how to count number of elements in a 1D, 2D & 3D Numpy array, also how to count number of rows & columns of a 2D numpy array and number of elements per axis in 3D numpy array ndarray is a template library that provides multidimensional array objects in C++, with an interface and features designed to mimic the Python 'numpy' package as much as possible. More information can be found in the documentation at ndarray.github.io/ndarray. Installation. ndarray can be built and tested with CMake

Creating arrays using numpy

NumPy - Ndarray Object - Tutorialspoin

Numpy ist ein vordefiniertes Paket in Python, das zur Ausführung leistungsfähiger mathematischer Operationen und zur Unterstützung eines N-dimensionalen Array-Objekts verwendet wird. Die Array-Klasse von Numpy ist als ndarray bekannt, was der Schlüssel zu diesem Framework ist. Objekte aus dieser Klasse werden als Numpy-Array bezeichnet The NumPy array numpy.ndarray and the Python built-in type list can be converted to each other.. Convert list to numpy.ndarray: numpy.array(); Convert numpy.ndarray to list: tolist(); For convenience, the term convert is used, but in reality, a new object is generated while keeping the original object Beginning in MATLAB R2018b, Python functions that accept numpy arrays may also accept MATLAB arrays without explicit conversion. When necessary, a numpy array can be created explicitly from a MATLAB array. For example, if you have a supported version of Python that is installed with the numpy library, you can do the following Size of the first dimension of numpy.ndarray: len () len () is the built-in function that returns the number of elements in a list or the number of characters in a string. For numpy.ndarray, len () returns the size of the first dimension. Equivalent to shape and also equal to size only for one-dimensional arrays Create a numpy ndarray from a tensor

Numpy ndarray - GeeksforGeek

  1. Erstellt: January-06, 2020 | Aktualisiert: June-25, 2020. Numpy hat auch eine append Funktion, um Daten an ein Array anzuhängen, genau wie die append Operation an List in Python. Aber in einigen Fällen ist append in NumPy auch ein wenig ähnlich wie die erweiternde Methode in Python list.. Array append. Lassen Sie uns zuerst die Syntax von ndarray.append auflisten
  2. numpy基础——ndarray对象. numpy 是使用python进行数据分析不可或缺的第三方库,非常多的科学计算工具都是基于 numpy 进行开发的。 ndarray对象是用于存放同类型元素的多维数组,是numpy中的基本对象之一,另一个是func对象。本文主要内容是:1 、简单介绍ndarray对象;2、ndarray对象的常用属性;3、如何.
  3. Python numpy.where() is an inbuilt function that returns the indices of elements in an input array where the given condition is satisfied. Python's numpy module provides a function to select elements based on condition. If you want to find the index in Numpy array, then you can use the numpy.where() function
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  5. An equivalent numpy array occupies much less space than a python list of lists. 3. How to inspect the size and shape of a numpy array? Every array has some properties I want to understand in order to know about the array. Let's consider the array, arr2d. Since it was created from a list of lists, it has 2 dimensions that can be shown as rows and columns, like in a matrix. Had I created one.

Mit Hilfe der numpy.ndarray .__ neg __()-Methode von Numpy kann jedes einzelne Element eines Arrays mit -1 multipliziert werden. Daher wird das resultierende Array mit Werten wie positiven Werten negativ und negative Werte werden positiv.. Syntax: ndarray .__ neg __ ($ self, /) Rückkehr:-selbst Beispiel 1: In diesem Beispiel sehen wir, dass wir nach dem Anwenden numpy.__neg__()das einfache. numpy.array() Python's Numpy module provides a function numpy.array() to create a Numpy Array from an another array like object in python like list or tuple etc or any nested sequence like list of list, numpy.array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0) Arguments Array is created in Python by importing array module to the python program. Then the array is declared as shown eblow. from array import * arrayName = array(typecode, [Initializers]) Typecode are the codes that are used to define the type of value the array will hold. Some common typecodes used are

Python | Numpy numpy.ndarray .__ lshift __() Kommentar verfassen / geeksforgeeks, Python / Von Acervo Lima. Mit Hilfe der Numpy numpy.ndarray.__lshift__()Methode können wir die Elemente, die übrig bleiben, um den Wert verschieben, der als Parameter in der numpy.ndarray.__lshift__()Methode angegeben wird. Syntax: ndarray .__ lshift __ ($ self, value, /) Rückgabe: self << value Beispiel 1: In. Example 2: Create Two-Dimensional Numpy Array with Random Values. To create a 2-D numpy array with random values, pass the required lengths of the array along the two dimensions to the rand() function. In this example, we will create 2-D numpy array of length 2 in dimension-0, and length 4 in dimension-1 with random values. Python Progra Die Kernfunktionalität von NumPy basiert auf der Datenstruktur ndarray (n-dimensionales Array), die auch als NumPy Array bezeichnet wird. Dessen wesentliche Bestandteile sind ein Zeiger auf einen zusammenhängenden Speicherbereich zusammen mit Metadaten , welche die darin gespeicherten Daten beschreiben: [5] [4

python - dsolve error: &#39;numpyPython Numpy | Numpy in Python

Know miscellaneous operations on arrays, such as finding the mean or max (array.max(), array.mean()). No need to retain everything, but have the reflex to search in the documentation (online docs, help(), lookfor())!! For advanced use: master the indexing with arrays of integers, as well as broadcasting. Know more NumPy functions to handle various array operations array([[ nan, nan, nan, nan], [ 1. , 2. , 48.646, 60.636], [ 2. , 3. , 48.921, 62.104], [ 3

In this method, we use the NumPy ndarray sum to calculate the sum of each individual row of the array. After which we divide the elements if array by sum . Let us see this through an example NumPy arrays werden in zusammenhängenden Blöcken gespeichert Speicher. Wenn Sie möchten, fügen Sie Zeilen oder Spalten zu einer bestehenden Palette, wird das gesamte array kopiert werden muss, um einen neuen block von Speicher, die Schaffung von Lücken für die neuen Elemente gespeichert werden Boolean Array using dtype='bool' in NumPy - Python Let's take an example: import numpy as np import random array = [] for _ in range(10): num = random.randint(0,1) array.append(num) print(f'Original Array={array}') # prints the original array with 0's and 1's nump_array = np.array(array,dtype='bool') print(f'numpy boolean array:{nump_array}') # prints the converted boolean arra Code: Alles auswählen. data_temp= [] for i in range ( 0 ,len (data)): data_temp.append (data [i] [n]) nun habe ich die eine spalte extrahiert! darauf führe ich berechnungen aus, ändere Werte und möchte diesen ARray wieder in meinen ursprünglichen Array einfügen: Code: Alles auswählen To print out the entire two dimensional array we can use python for loop as shown below. We use end of line to print out the values in different rows. from array import * T = [[11, 12, 5, 2], [15, 6,10], [10, 8, 12, 5], [12,15,8,6]] for r in T: for c in r: print(c,end = ) print(

>>> np.random.rand(3,2) array([[ 0.14022471, 0.96360618], [ 0.37601032, 0.25528411], [ 0.49313049, 0.94909878]]) >>> np.random.random_integers(low=0, high=9, size=(3. Für die Erzeugung von NumPy-Arrays bedeutet dies, dass man am besten die Größe bereits zu Beginn festlegt und dann aus den vielen zur Verfügung stehenden Methoden eine geeignete auswählt, um das Array mit Werten zu füllen. In NumPy ist es sehr einfach, die Dokumentation nach einem bestimmten Text zu durchsuchen Boost.NumPy was originally written by Jim Bosch as part of the ndarray C++ library, then reorganized into a standalone component, cleaned up, and documented as part of a Boost-sponsored Google Summer of Code by Ankit Daftery, mentored by Stefan Seefeld. Philip Miller contributed the CMake build system Python-Vergleichsoperatoren im Überblick: Operator Beispiel Bedeutung == x = [1,2,3] list(np.array(x)==3) >>>[False, False, True] Ist gleich!= x = [1,2,3] list(np.array(x)!=3) >>>[True, True, False] Ist ungleich > x = [1,2,3] list(np.array(x)>2) >>>[False, False, True] Größer < x = [1,2,3] list(np.array(x)<2) >>>[True, False, False] Kleiner >= x = [1,2,3] list(np.array(x)>=2

Pythonのlen関数で様々な型のオブジェクトのサイズを取得 | note

Python NumPy Tutorial - NumPy ndarray & NumPy Array

Method 1: numpy.any() to check if the NumPy array is empty in Python. numpy.any() method is used to test whether any array element along a given axis evaluates to True. Syntax: numpy.any(a, axis = None, out = None, keepdims = <no value>) Parameters: array: Input array whose elements need to be checked. axis: Axis along which array elements are evaluated You can treat lists of a list (nested list) as matrix in Python. However, there is a better way of working Python matrices using NumPy package. NumPy is a package for scientific computing which has support for a powerful N-dimensional array object As for all objects in MATLAB, structs are, in fact, arrays of structs, where a single struct is an array of shape (1, 1). octave:11> my_struct = struct('field1', 1, 'field2', 2) my_struct = { field1 = 1 field2 = 2 } octave:12> save -6 octave_struct.mat my_struct. We can load this in Python: >>> Python arrays are a data structure like lists. They contain a number of objects that can be of different data types. In addition, Python arrays can be iterated and have a number of built-in functions to handle them. Python has a number of built-in data structures, such as arrays

Adding to an array using array module. If we are using the array module, the following methods can be used to add elements to it: By using + operator: The resultant array is a combination of elements from both the arrays. By using append () function: It adds elements to the end of the array Deklarieren Sie ein Array in Python, indem Sie das Modul array importieren. Wenn Sie wirklich ein Array mit der Fähigkeit initialisieren möchten, nur homogene Elemente zu enthalten, wird das Modul array aus der Bibliothek array importiert. Das Array wird mit den Klammern und im Wesentlichen zwei Parametern definiert. Der erste Parameter ist ein Typcode, der den Typ der Elemente definiert. Dictionaries are Python's implementation of a data structure that is more generally known as an associative array. A dictionary consists of a collection of key-value pairs. Each key-value pair maps the key to its associated value. You can define a dictionary by enclosing a comma-separated list of key-value pairs in curly braces ({}) The numpy.asarray() converts a tuple of lists to array, but it will create a two-dimensional array, and to convert it into a one-dimensional array, use the array.flatten() method. Using np.array() method to convert tuple to array. The numpy.array() method takes a Python object as an argument and returns an array. We will pass a tuple object to the np.array() function and it will convert that tuple to an array

Numerisches Python: Funktionen zur Erzeugung von Numpy Array

Python Crash Course: Master Python Programming; Array duplicates: If the array contains duplicates, the index() method will only return the first element. Find multiple occurences. If you want multiple to find multiple occurrences of an element, use the lambda function below. get_indexes = lambda x, xs: [i for (y, i) in zip(xs, range(len(xs))) if x == y] Find in string arrays. To find an. NumPy N-dimensional Array. NumPy is a Python library that can be used for scientific and numerical applications and is the tool to use for linear algebra operations. The main data structure in NumPy is the ndarray, which is a shorthand name for N-dimensional array. When working with NumPy, data in an ndarray is simply referred to as an array. It is a fixed-sized array in memory that contains. Das deutsche Python-Forum. Seit 2002 Diskussionen rund um die Programmiersprache Python. Python-Forum.de. Foren-Übersicht. Python Programmierforen. Allgemeine Fragen. Array sortieren. Wenn du dir nicht sicher bist, in welchem der anderen Foren du die Frage stellen sollst, dann bist du hier im Forum für allgemeine Fragen sicher richtig. 4 Beiträge • Seite 1 von 1. kl.feigling89 User. 1 This is a design principle for all mutable data structures in Python. Another thing you might notice is that not all data can be sorted or compared. For instance, [None, 'hello', 10] doesn't sort because integers can't be compared to strings and None can't be compared to other types. Also, there are some types that don't have a defined ordering relation. For example, 3+4j < 5+7j isn.

Ich bin neu in der python-Programmierung, und ich habe mich nur gefragt, wenn Sie Zugriff auf ein 2D-array in python mithilfe von Punkten/Koordinaten? Beispiel Sie haben einen Punkt: Punkt = (1,2) haben, und Sie haben eine matrix, dann werden Sie Zugriff auf einen bestimmten Teil der matrix mit einer Koordinate. Matrix[Punkt] = eine Probe Wert hier. Dank, Vincent. Informationsquelle Autor. Python ndarray shape object is useful to display the array shape precisely, array dimensions. If it is one dimensional, it returns the number of items. If it is two dimensional, returns the rows, columns. Generally, Python assigns a proper data type to an array that we create. However, the Python array function also allows you to specify the data type of an array explicitly using dtype. Using. It accepts the array and the index of the element to remove. The method returns a new array without the removed element: [10, 20, 30, 50, 60, 70, 80, 90, 100] Conclusion. There are different ways to remove an array element in Python. Sometimes we might want to remove an element by index and sometimes by value ndarray, a fast and space-efficient multidimensional array providing vectorized arithmetic operations and sophisticated broadcasting capabilities. Standard mathematical functions for fast operations on entire arrays of data without having to write loops. Tools for reading / writing array data to disk and working with memory-mapped file 2.6. Image manipulation and processing using Numpy and Scipy¶. Authors: Emmanuelle Gouillart, Gaël Varoquaux. This section addresses basic image manipulation and processing using the core scientific modules NumPy and SciPy

Example 2: Python Numpy Zeros Array - Two Dimensional. To create a two-dimensional array of zeros, pass the shape i.e., number of rows and columns as the value to shape parameter. In this example, we shall create a numpy array with 3 rows and 4 columns. Python Program. import numpy as np #create 2D numpy array with zeros a = np.zeros((3, 4)) #print numpy array print(a) Run. Please observe. My Dashboard; Pages; Python Lists vs. Numpy Arrays - What is the difference? Non-Credit. Home; Modules; UCF Library Tools; Keep Learnin Introduction to 3D Arrays in Python. Before starting with 3d array, one thing to be clear that arrays are in every programming language is there and does some work in python also. Every programming language its behavior as it is written in its compiler. Many people have one question: Do we need to use a list in the form of 3d array, or we have Numpy. And the answer is we can go with the simple.

Python list is a useful object for doing various operations where multiple values can be stored in a single variable that works like the numeric array of other programming languages. Different types of arrays can be generated by using the NumPy library of Python. How to convert python NumPy array to python list is explained in this article So in Python 3.x, the range() function got its own type.In basic terms, if you want to use range() in a for loop, then you're good to go. However you can't use it purely as a list object. For example you cannot slice a range type.. When you're using an iterator, every loop of the for statement produces the next number on the fly. Whereas the original range() function produced all numbers. Wieder überprüft Python, ob ein weiterer Wert in der Liste vorhanden ist. Dies ist nach den ersten 3 Werten nicht mehr der Fall. Unsere Liste verfügt nur über diese 3 Werte. Die for-Schleife ist beendet. Dabei ist es egal, ob in der Liste Zeichenketten oder Zahlen oder ein Mischmasch steht. vornamen = ['Axel', 108, 'Elke', 30, 'Martin', 22] Wir haben mit dem letzten Beispiel eine gemischte.

python - What is the difference between ndarray and array

When looping over an array or any data structure in Python, there's a lot of overhead involved. Vectorized operations in NumPy delegate the looping internally to highly optimized C and Fortran functions, making for cleaner and faster Python code. Counting: Easy as 1, 2, 3 As an illustration, consider a 1-dimensional vector of True and False for which you want to count the number of. To create an array of random integers in Python with numpy, we use the random.randint() function. Into this random.randint() function, we specify the range of numbers that we want that the random integers can be selected from and how many integers we want. In the code below, we select 5 random integers from the range of 1 to 100. So, first, we must import numpy as np. We then create a variable. Note: When people say arrays in Python, more often than not, they are talking about Python lists.If that's the case, visit the Python list tutorial.. In this tutorial, we will focus on a module named array.The array module allows us to store a collection of numeric values Beginning in MATLAB R2018b, Python functions that accept numpy arrays may also accept MATLAB arrays without explicit conversion. When necessary, a numpy array can be created explicitly from a MATLAB array Performance of Numpy Array vs Python List. Cory Gough. Jul 22, 2019 · 4 min read. Most of us have been told numpy arrays have superior performance over python lists, but do you know why? The.

Python: Arrays erstellen und verwenden - so geht's - CHI

What is Array in Python? An array is a container used to contain a fixed number of items. But, there is an exception that values should be of the same type. The following are two terms often used with arrays. Array element - Every value in an array represents an element. Array index - Every element has some position in the array known as the index. Let's now see how Python represents an. A Python array is constructed with a type signature and sequence of initial values. For the possible type signatures, refer to the Python documentation for the array module. Notice that when a Python array is assigned to a variable typed as memory view, there will be a slight overhead to construct the memory view. However, from that point on the variable can be passed to other functions. Numpy is a pre-defined package in python used for performing powerful mathematical operations and support an N-dimensional array object. Numpy's array class is known as ndarray, which is key to this framework. Objects from this class are referred to as a numpy array. The difference between Multidimensional and Numpy Arrays is that numpy arrays are homogeneous, i.e. it can contain an only integer, string, float, etc., values and their size are fixed. The multidimensional list can be.

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How to Create a Python Array? You can create an array using the following piece of code-class array.array(typecode[,initializer]) This creates a new array with items of the type specified by the type code. You can optionally provide an initializer value- a list. Let's try creating an array in Python. >>> arr=array.array('i',[1,3,4]) >>> arr. Outpu Array like object of float, integer, and Unicode characters can be created using the python array module. Let's look at the basic syntax for the same. d is type code for float type for both float and double, i is type code for integer type for char, short, int, long, and u is type code for Unicode type. Syntax: array_name= array (data_type, value_list), #data_type and value. Python: array - This module defines an object type which can compactly represent an array of basic values: characters, integers, floating point numbers and methods with examples - w3resourc History. The Python programming language was not originally designed for numerical computing, but attracted the attention of the scientific and engineering community early on. In 1995 the special interest group (SIG) matrix-sig was founded with the aim of defining an array computing package; among its members was Python designer and maintainer Guido van Rossum, who extended Python's syntax (in. # importing library import numpy # initilizing list lst = [1, 7, 0, 6, 2, 5, 6] # converting list to array arr = numpy.array(lst) # displaying list print (List.

Python abstract class (ABC module) Unified Social Credit Code verification python implementation __python; Python: Database Operations; Python Study Notes 1-assignment and string; Python Study Notes 2-column (list) Python: collection operation summary; The difference between OS and sys two modules in Python To convert JSON to a Python dict use this: import json. json_data = ' {name: Brian, city: Seattle}'. python_obj = json.loads (json_data) print python_obj [name] print python_obj [city] Convert JSON to Python Object (List) JSON data can be directly mapped to a Python list. import json NumPy Matrix Transpose. 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 In this tutorial, you'll learn how to perform many Python NumPy array operations such as adding, deleting, sorting, and extracting values, row, and columns. Skip to content. Search for: Menu. Home; Linux; Server Administration; Web Development; Python; iOS Development; Tech Tips; Python Python NumPy array tutorial . Ayesha Tariq Published: February 2, 2019 Last updated: May 2, 2021. NumPy is a.

Python: How to Select Rows from Pandas DataFramepandasNumPy配列の行・列ごとの合計、平均、最大、最小などを算出 | note

from array import array <array> = array('<typecode>', <collection>) # Array from collection of numbers. <array> = array('<typecode>', <bytes>) # Array from bytes object. <array> = array('<typecode>', <array>) # Treats array as a sequence of numbers. <bytes> = bytes(<array>) # Or: <array>.tobytes() <file>.write(<array>) # Writes array to the binary file The main purpose of this python post is to share with you the following python programs: python program to count occurrences of in array using count. python program to count occurrences of in array using for loop. python program toRead More Python Count the Occurrences in an Arra (Another Python module called array defines one-dimensional arrays, so don't confuse the arrays of NumPy with this other type.) It also defines functions of ndarrays (ufuncs or universal functions) which operate on each element of the array. Replacements for the standard functions of the math module exist. (Math module functions cannot be used directly on ndarrays because they only. In this article, we will create a python function that will produce an array with the numbers 0 to N-1 in it. For example, the following code will result in an array containing the numbers 0 to 4: arr(5) // => [0,1,2,3,4] There are a few rules we need to follow here:-when the user passes in 0 to the above function, the function will return an empty list. when the user passes in an empty. Python Numpy Array length output Enter the Total Array Items = 4 Enter the 1 Array value = 20 Enter the 2 Array value = 90 Enter the 3 Array value = 120 Enter the 4 Array value = 50 Integer Numpy Array Items = [ 20 90 120 50] Integer Numpy Array Length = A numpy array is a grid of values, all of the same type, and is indexed by a tuple of nonnegative integers. The number of dimensions is the rank of the array; the shape of an array is a tuple of integers giving the size of the array along each dimension. We can initialize numpy arrays from nested Python lists, and access elements using square brackets

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