813 lines
20 KiB
Plaintext
813 lines
20 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"# Data Containers\n",
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"\n",
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"This notebook shows how to combine data into different types of \"containers\" (arrays, dictionaries, tuples, ...) inside your program."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Load Packages and Extra Functions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"printyellow (generic function with 1 method)"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"using Printf\n",
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"\n",
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"include(\"jlFiles/printmat.jl\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Arrays\n",
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"\n",
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"are used everywhere in finance and statistics/econometrics."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Vectors, Matrices and High-dimensional Arrays\n",
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"\n",
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"can be created in many ways: the code below demonstrates just a few of them. See the tutorial on Arrays for (many) more details.\n",
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"\n",
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"To access an array element, just do `A[2]` or similarly. Also, you can change an array element as in `B[2,1] = -999.`\n",
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"\n",
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"Notice that `D = [A B]` creates an independent copy, so later changing `B` does not affect `D`. However, if we define `E = B`, then a change of `B` will affect both itself and `E`.\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" 100 \n",
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" 101 \n",
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"\n",
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" 1 2 \n",
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" 0 10 \n",
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"\n",
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" 100 1 2 \n",
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" 101 0 10 \n",
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"\n"
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]
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}
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],
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"source": [
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"A = [100,101] #a vector\n",
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"printmat(A) #or display(A)\n",
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"\n",
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"B = [1 2; #a matrix\n",
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" 0 10]\n",
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"printmat(B)\n",
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"\n",
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"D = [A B] #a 2x3 matrix\n",
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"printmat(D)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"A[2] is 101\n",
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"\n",
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"B is now\n",
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" 1 2 \n",
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" -999 10 \n",
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"\n",
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"\n",
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"D is not affected\n",
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" 100 1 2 \n",
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" 101 0 10 \n",
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"\n"
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]
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}
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],
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"source": [
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"println(\"A[2] is \",A[2]) #access an element\n",
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"\n",
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"B[2,1] = -999 #change an element\n",
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"println(\"\\nB is now\")\n",
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"printmat(B)\n",
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"\n",
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"println(\"\\nD is not affected\")\n",
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"printmat(D) #D is not changed when B is"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"4×3×2 Array{Float64, 3}:\n",
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"[:, :, 1] =\n",
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" 0.0822035 0.727781 0.616084\n",
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" 0.700477 0.148329 0.0486485\n",
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" 0.497247 0.0274626 0.233258\n",
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" 0.908952 0.0319028 0.63753\n",
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"\n",
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"[:, :, 2] =\n",
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" 0.991477 0.725542 0.505041\n",
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" 0.999608 0.801481 0.636564\n",
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" 0.841383 0.160885 0.691288\n",
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" 0.473578 0.14428 0.724725"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"C = rand(4,3,2) #a 4x3x3 array\n",
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"display(C)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Arrays of Arrays (or other types)\n",
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"\n",
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"You can store very different things (a mixture of numbers, matrices, strings) in an array. For instance, if `a` is a vector, `str` is a string and `C` is a matrix, then `x = [a,str,C]` puts them into a vector.\n",
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"\n",
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"If you later change elements of the matrix `C` then it will affect `x` (discussed at the end of the notebook). "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1:10"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"\"Hazel\""
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"2×2 Matrix{Int64}:\n",
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" 11 12\n",
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" 21 22"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"a = 1:10\n",
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"str = \"Hazel\"\n",
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"C = [11 12;21 22]\n",
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"x = [a,str,C] #element 1 of x is a\n",
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"\n",
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"foreach(display,x) #loops over the elements of x"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tuples and Named Tuples\n",
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"\n",
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"are very useful for collecting very different types of data (a number, a string, and a couple of vectors, say). \n",
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"\n",
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"Once created, you cannot change tuples (they are immutable). (Exception: *changing elements of an array* that belongs to the tuple will affect the tuple too.)\n",
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"\n",
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"Tuples are often used as inputs or outputs of functions.\n",
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"\n",
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"The next few cells show how to create (named) tuples, how to extract parts of them and what happens when you to try to change them."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(1:10, \"Hazel\", [11 12; 21 22])"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"(a = 1:10, str = \"Hazel\", C = [11 12; 21 22])"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"(a = 1:10, str = \"Hazel\", C = [11 12; 21 22])"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"a = 1:10 #how to create tuples and named tuples\n",
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"str = \"Hazel\"\n",
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"C = [11 12;21 22]\n",
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"\n",
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"t = (a,str,C) #a tuple, or tuple(a,str,C)\n",
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"display(t)\n",
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"\n",
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"nt = (a=a,str=str,C=C) #a named tuple, (a2=a,str2=str,C2=C) would also work\n",
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"display(nt)\n",
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"\n",
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"nt_ = (;a,str,C) #also a named tuple (Julia 1.5+), names are given by variables\n",
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"display(nt_)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"a2 and str2 are: 1:10 Hazel \n",
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"\n",
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"t[3] is [11 12; 21 22]\n",
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"\n",
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"nt.C is [11 12; 21 22]\n"
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]
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}
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],
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"source": [
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"(a2,str2,C2) = t #extract the tuple into variables (\"destructuring\")\n",
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"println(\"a2 and str2 are: $a2 $str2 \\n\")\n",
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"\n",
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"println(\"t[3] is \",t[3],\"\\n\") #can index into (tuple) t\n",
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"\n",
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"println(\"nt.C is \",nt.C) #we can use nt.C as a name (nt is a named tuple)\n",
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"\n",
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"#(a3,str3...) = t #in Julia 1.6, str3 will be a tuple "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"t[1] is 1:10\n",
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"\n",
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"nt.C is [11 12; 21 22]\n",
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"\n"
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]
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}
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],
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"source": [
|
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"println(\"t[1] is \",t[1],\"\\n\")\n",
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"#t[1] = -999 #cannot change the tuple, uncomment to get an error\n",
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"#t[4] = 34 #cannot add elements, uncomment to get an error\n",
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"\n",
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"println(\"nt.C is \",nt.C,\"\\n\")\n",
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"#nt.a = -999 #cannot change the tuple\n",
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"#n.D = 34 #cannot add elements"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Create a Tuple Dynamically (extra)\n",
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"\n",
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"when the values and (perhaps also the names) are created dynamically in the program.\n",
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"\n",
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"Suppose `values` and `names` in the next cell may differ in length from one run of the program to the next. Using `tuple(values...)` and `NamedTuple{names}(values)` allows you to still create tuples/named tuples."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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||
"text/plain": [
|
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"(1:10, \"Hazel\", [11 12; 21 22])"
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]
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||
},
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||
"metadata": {},
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||
"output_type": "display_data"
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},
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||
{
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"data": {
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||
"text/plain": [
|
||
"(a = 1:10, b = \"Hazel\", c = [11 12; 21 22])"
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]
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||
},
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||
"metadata": {},
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||
"output_type": "display_data"
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}
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],
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"source": [
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"values = [a,str,C]\n",
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"\n",
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"t2 = tuple(values...) #or (values...,)\n",
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"display(t2)\n",
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"\n",
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"names = (:a, :b, :c)\n",
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"nt2 = NamedTuple{names}(values) #or (;zip(names,values)...)\n",
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"display(nt2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Dictionaries\n",
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"\n",
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"is a flexible way to collect different types of data. Dictionaries can (in contrast to tuples) be changed. Also, changing elements of an array that belongs to the dictionary will affect the dictionary too.\n",
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"\n",
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"A dictionary is organised as (key,value) pairs, where the key is the name of the element. You can loop over the elements (see below) and also change/add elements in a loop."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Dict{Symbol, Any} with 4 entries:\n",
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" :a => -999\n",
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" :verse2 => \"Stardust\"\n",
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" :str => \"Hazel\"\n",
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" :C => [11 12; 21 22]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"D[:C] is [11 12; 21 22]\n"
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]
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}
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],
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"source": [
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"a = 1:10\n",
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"str = \"Hazel\"\n",
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"C = [11 12;21 22]\n",
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"\n",
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"D = Dict(:a=>a,:str=>str,:C=>C) #dictionary, \"a\" instead of :a works too\n",
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"\n",
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"println(\"D[:C] is \",D[:C])\n",
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"\n",
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"D[:a] = -999 #can change an element\n",
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"\n",
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"D[:verse2] = \"Stardust\" #can add an element\n",
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"\n",
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"display(D)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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||
"metadata": {
|
||
"scrolled": true
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||
},
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||
"outputs": [
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{
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||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
|
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"a: -999\n",
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"verse2: Stardust\n",
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"str: Hazel\n",
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"C: [11 12; 21 22]\n"
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]
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}
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],
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"source": [
|
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"for (key,value) in D #loop over a dictionary\n",
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" println(\"$key: $value\")\n",
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"end"
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]
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},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
|
||
"source": [
|
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"## From a Dict to a NamedTuple and Back Again (extra)"
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]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 12,
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||
"metadata": {},
|
||
"outputs": [
|
||
{
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||
"data": {
|
||
"text/plain": [
|
||
"(a = -999, verse2 = \"Stardust\", str = \"Hazel\", C = [11 12; 21 22])"
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||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
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||
},
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||
{
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"data": {
|
||
"text/plain": [
|
||
"Dict{Symbol, Any} with 4 entries:\n",
|
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" :a => -999\n",
|
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" :verse2 => \"Stardust\"\n",
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" :str => \"Hazel\"\n",
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||
" :C => [11 12; 21 22]"
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||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
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||
],
|
||
"source": [
|
||
"nt = (;D...) #create a named tuple from a dict\n",
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"display(nt)\n",
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"\n",
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"D2 = Dict(pairs(nt)) #create a dict from a named tuple\n",
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"display(D2)"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
|
||
"source": [
|
||
"## A Potential Pitfall in Adding to a Dict (extra)\n",
|
||
"\n",
|
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"If you have created a dict with only numbers by \n",
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"```\n",
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"D = Dict(:aa=>1)\n",
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"``` \n",
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||
"then you cannot add eg. a string by `D[:cc] = \"hello\"` since `D` is only set up to accept variables of the type `Int`. "
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 13,
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||
"metadata": {},
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||
"outputs": [
|
||
{
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||
"data": {
|
||
"text/plain": [
|
||
"Dict{Any, Any} with 2 entries:\n",
|
||
" :aa => 1\n",
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" :cc => \"hello\""
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"D = Dict(:aa=>1)\n",
|
||
"#D[:cc] = \"hello\" #error since D only accepts Int\n",
|
||
"\n",
|
||
"D = Dict{Any,Any}(:aa=>1) #this works\n",
|
||
"D[:cc] = \"hello\"\n",
|
||
"display(D)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Create a Dictionary Dynamically (extra)\n",
|
||
"\n",
|
||
"See below for examples.\n",
|
||
"\n",
|
||
"Remark: if you have the names as an array of strings (`names = [\"a\",\"b\",\"c\"]`), but want symbol names (`:a` etc), then use `Symbol.(names)`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Dict{Symbol, Any} with 3 entries:\n",
|
||
" :a => 1:10\n",
|
||
" :b => \"Hazel\"\n",
|
||
" :c => [11 12; 21 22]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"names = (:a, :b, :c) #or [\"a\",\"b\",\"c\"]\n",
|
||
"values = [a,str,C]\n",
|
||
"\n",
|
||
"D = Dict(zip(names,values))\n",
|
||
"display(D)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Dict{Any, Any} with 3 entries:\n",
|
||
" :a => 1:10\n",
|
||
" :b => \"Hazel\"\n",
|
||
" :c => [11 12; 21 22]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"D = Dict() #empty dictionary\n",
|
||
"for i = 1:length(values) #loop\n",
|
||
" D[names[i]] = values[i] #add this to the dictionary\n",
|
||
"end\n",
|
||
"display(D)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Your Own Tailor Made Data Type\n",
|
||
"\n",
|
||
"It is sometime conventient to define your own `struct` as a container. The `struct` command creates an immutable type (you cannot change it, except for elements of arrays that belong to it). There is also a `mutable struct` approach."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"x1: MyType(1:10, \"Hazel\", [11 12; 21 22])\n",
|
||
"x1.s: Hazel\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"a = 1:10\n",
|
||
"str = \"Hazel\"\n",
|
||
"C = [11 12;21 22]\n",
|
||
"\n",
|
||
"struct MyType #change to `mutable struct` to be able to change it later\n",
|
||
" x #can be anything\n",
|
||
" s::String #has to be a String\n",
|
||
" z::Array #has to be an Array\n",
|
||
"end\n",
|
||
"\n",
|
||
"x1 = MyType(a,str,C) #has to specify all arguments\n",
|
||
"\n",
|
||
"println(\"x1: \",x1)\n",
|
||
"println(\"x1.s: \",x1.s)\n",
|
||
"\n",
|
||
"#x1 = MyType(1:10,10,[1;2]) #error since 10 is not a string\n",
|
||
"#x1.x = 3 #error since we cannot change"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## A Potential Pitfall in Using Arrays in Structures (extra)\n",
|
||
"\n",
|
||
"It is also possible to specify array types (for instance, `z::Array{Float64}` instead of just `z::Array`). This has the effect of converting (if possible) an input array to Float64. While this might have its uses, it also comes with a potential drawback: the conversion breaks the link between the input array and the array inside `MyType`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### DataFrames and Other Things\n",
|
||
"\n",
|
||
"See [DataFrames.jl](https://juliadata.github.io/DataFrames.jl/stable/) for how to work with DataFrames."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# A Potential Pitfall when Using an Array in another Data Container (extra)\n",
|
||
"\n",
|
||
"Suppose you create an array of arrays (or a tuple or a dictionary) called `y`, and that the array `C` is one of the elements.\n",
|
||
"\n",
|
||
"If you later change *elements* of `C` then it will affect `y` as well (and vice versa). This happens with *arrays*, since they are designed to conserve memory space. For instance, even if `C` is a very large array (several GB, say), creating `y=[\"hello\",C]` will require very little additional memory space.\n",
|
||
"\n",
|
||
"If you want an independent copy, use `copy(C)`, for instance, `y=[\"hello\",copy(C)]`.\n",
|
||
"\n",
|
||
"In contrast, if you change the shape of `C` then it will *not* affect `y` (but you don't save any memory)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"3-element Vector{Any}:\n",
|
||
" 1:10\n",
|
||
" \"Hazel\"\n",
|
||
" [-999 12; 21 22]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(1:10, \"Hazel\", [-999 12; 21 22])"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Dict{Symbol, Any} with 3 entries:\n",
|
||
" :a => 1:10\n",
|
||
" :str => \"Hazel\"\n",
|
||
" :C => [-999 12; 21 22]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"MyType(1:10, \"Hazel\", [-999 12; 21 22])"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"a = 1:10\n",
|
||
"str = \"Hazel\"\n",
|
||
"C = [11 12;21 22]\n",
|
||
"\n",
|
||
"x = [a,str,C]\n",
|
||
"t = (a,str,C)\n",
|
||
"d = Dict(:a=>a,:str=>str,:C=>C)\n",
|
||
"e = MyType(a,str,C)\n",
|
||
"\n",
|
||
"C[1,1] = -999 #changing an element of C affects x,t,d,e\n",
|
||
"\n",
|
||
"display(x)\n",
|
||
"display(t)\n",
|
||
"display(d)\n",
|
||
"display(e)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(1:10, \"Hazel\", [-999 12; 21 22])"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"C = 0 #changing the shape of C does not affect x,t,d\n",
|
||
"display(t)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"@webio": {
|
||
"lastCommId": null,
|
||
"lastKernelId": null
|
||
},
|
||
"anaconda-cloud": {},
|
||
"kernelspec": {
|
||
"display_name": "Julia 1.6.0",
|
||
"language": "julia",
|
||
"name": "julia-1.6"
|
||
},
|
||
"language_info": {
|
||
"file_extension": ".jl",
|
||
"mimetype": "application/julia",
|
||
"name": "julia",
|
||
"version": "1.6.0"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 1
|
||
}
|