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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"\n",
"<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n",
"___\n",
"# Matplotlib Exercises \n",
"Welcome to the exercises for reviewing matplotlib! Take your time with these, Matplotlib can be tricky to understand at first. These are relatively simple plots, but they can be hard if this is your first time with matplotlib, feel free to reference the solutions as you go along.\n",
"\n",
"Also don't worry if you find the matplotlib syntax frustrating, we actually won't be using it that often throughout the course, we will switch to using seaborn and pandas built-in visualization capabilities. But, those are built-off of matplotlib, which is why it is still important to get exposure to it!\n",
"\n",
"**NOTE: ALL THE COMMANDS FOR PLOTTING A FIGURE SHOULD ALL GO IN THE SAME CELL. SEPARATING THEM OUT INTO MULTIPLE CELLS MAY CAUSE NOTHING TO SHOW UP.**\n",
"\n",
"# Exercises\n",
"\n",
"**We will focus on two commons tasks, plotting a known relationship from an equation and plotting raw data points.**\n",
"\n",
"Follow the instructions to complete the tasks to recreate the plots using this data:\n",
"\n",
"----\n",
"----\n",
"\n",
"### Task One: Creating data from an equation\n",
"\n",
"It is important to be able to directly translate a real equation into a plot. Your first task actually is pure numpy, then we will explore how to plot it out with Matplotlib. The [world famous equation](https://en.wikipedia.org/wiki/Mass%E2%80%93energy_equivalence) from Einstein:\n",
"\n",
"$$E=mc^2$$\n",
"\n",
"\n",
"Use your knowledge of Numpy to create two arrays: E and m , where **m** is simply 11 evenly spaced values representing 0 grams to 10 grams. E should be the equivalent energy for the mass. You will need to figure out what to provide for **c** for the units m/s, a quick google search will easily give you the answer (we'll use the close approximation in our solutions).\n",
"\n",
"**NOTE: If this confuses you, then hop over to the solutions video for a guided walkthrough.**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The array m should look like this: \n",
"\n",
"[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]\n"
]
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The array E should look like this: \n",
"\n",
" [0.0e+00 9.0e+16 1.8e+17 2.7e+17 3.6e+17 4.5e+17 5.4e+17 6.3e+17 7.2e+17\n",
" 8.1e+17 9.0e+17]\n"
]
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Part Two: Plotting E=mc^2\n",
"\n",
"Now that we have the arrays E and m, we can plot this to see the relationship between Energy and Mass. \n",
"\n",
"**TASK: Import what you need from Matplotlib to plot out graphs:**"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**TASK: Recreate the plot shown below which maps out E=mc^2 using the arrays we created in the previous task. Note the labels, titles, color, and axis limits. You don't need to match perfectly, but you should attempt to re-create each major component.**"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"# DON\"T RUN THE CELL BELOW< THAT WILL ERASE THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Part Three (BONUS)\n",
"\n",
"**Can you figure out how to plot this on a logarthimic scale on the y axis? Place a grid along the y axis ticks as well. We didn't show this in the videos, but you should be able to figure this out by referencing Google, StackOverflow, Matplotlib Docs, or even our \"Additional Matplotlib Commands\" notebook. The plot we show here only required two more lines of code for the changes.**"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"# DONT RUN THE CELL BELOW! THAT WILL ERASE THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"---\n",
"---\n",
"\n",
"## Task Two: Creating plots from data points\n",
"\n",
"In finance, the yield curve is a curve showing several yields to maturity or interest rates across different contract lengths (2 month, 2 year, 20 year, etc. ...) for a similar debt contract. The curve shows the relation between the (level of the) interest rate (or cost of borrowing) and the time to maturity, known as the \"term\", of the debt for a given borrower in a given currency.\n",
"\n",
"The U.S. dollar interest rates paid on U.S. Treasury securities for various maturities are closely watched by many traders, and are commonly plotted on a graph such as the one on the right, which is informally called \"the yield curve\".\n",
"\n",
"**For this exercise, we will give you the data for the yield curves at two separate points in time. Then we will ask you to create some plots from this data.**\n",
"\n",
"## Part One: Yield Curve Data\n",
"\n",
"**We've obtained some yeild curve data for you from the [US Treasury Dept.](https://www.treasury.gov/resource-center/data-chart-center/interest-rates/pages/textview.aspx?data=yield). The data shows the interest paid for a US Treasury bond for a certain contract length. The labels list shows the corresponding contract length per index position.**\n",
"\n",
"**TASK: Run the cell below to create the lists for plotting.**"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"labels = ['1 Mo','3 Mo','6 Mo','1 Yr','2 Yr','3 Yr','5 Yr','7 Yr','10 Yr','20 Yr','30 Yr']\n",
"\n",
"july16_2007 =[4.75,4.98,5.08,5.01,4.89,4.89,4.95,4.99,5.05,5.21,5.14]\n",
"july16_2020 = [0.12,0.11,0.13,0.14,0.16,0.17,0.28,0.46,0.62,1.09,1.31]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**TASK: Figure out how to plot both curves on the same Figure. Add a legend to show which curve corresponds to a certain year.**"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# DONT RUN THE CELL BELOW! IT WILL ERASE THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**TASK: The legend in the plot above looks a little strange in the middle of the curves. While it is not blocking anything, it would be nicer if it were *outside* the plot. Figure out how to move the legend outside the main Figure plot.**"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"# DONT RUN THE CELL BELOW! IT WILL ERASE THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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H47FZWVln5PS2BW4zhvUAAOAGHkJP+Pjf+0HzDcEHAAC4BsEHAIAJaOHChUVDrV+yZMmlO3bsSByqzZo1awozMjJKZs+eXTxw3eOPP55dWFg4f9asWcXr1q3LHWwbGzduTC0uLp47Z86cecXFxXM3bdqU0rPu/fffT5wzZ868/Pz8+XfffXeez+eTJJ0+fTrq6quvnl1QUDD/6quvnl1TUxMlSQ8//PCUoqKieUVFRfNmz55dHBUVtfj06dNRw7wV/RB8AACYgD755JN9F7uNb3/727WbNm06OHD5m2++mbJ58+b0srKyz8vLyz9/+OGHqwbbRnZ2dtfmzZvLDxw48MULL7xw5N57772kZ913v/vdgmeeeabi6NGjew8fPhy/YcOGVEn68Y9/PPW6665rqqio2Hvdddc1PfLIIzmS9JOf/OT0vn37vti3b98Xjz32WOUVV1zRNGXKFO9o/k0c1QUAQIj85w278w5UNQ3ZqzJac3JSWv/f1SXHh2uXmJi48LXXXit/8sknp2zbtq1ckr71rW/ll5aWttx///11Pe2efvrpzL179yY8//zzxyXpySefzCwrK4t/7rnnKm+66abm/fv3xw7c9i9+8YusBx988FRCQoKVpOnTp3cPVsc111zT1vN48eLF7Z2dnZ62tjZTXV0d3dzc7Fm+fHmLJH3zm9+s+9WvfjXptttuO/v222+nb9++fb8kfec736n76le/eqmkE323+8tf/jJjzZo19cO9DwPR4wMAgIvdc8899e+8805aR0eHkaSXXnopc+3atXVDvebw4cPx27dvT1mwYEHRFVdccen27dtHFO5efPHFSfPmzWtNSEiwFRUVMVOnTu3qWVdQUNB56tSpGEmqq6uLLigo6PIv76qvr+/XUdPU1OTZsWNH2l133dUw2n8vPT4AAITISHpmwi01NdV3zTXXNL366qtpl112WXtXV5dZsmRJ21Cv8Xq9pqGhIerTTz/dt3379sQ777xz5vHjxz/zeAbvT9m5c2f8I488Mv3tt98+KEnWnn/gmzFmRDW/8soraYsXL24e7TCXRI8PAAATVkxMjO2ZMCxJPb06A61du7b2xRdfnLx+/frJd911V+1w283JyelcvXp1o8fj0dKlS1s9Ho+tqqoatDPl0KFDMatXr571/PPPHykuLu6QpMLCwq6eHh5JqqioiM3JyemSpMmTJ3dXVFTE+JfHZGRk9BtKe+211zJuu+22UQ9zSQQfAAAmrJkzZ3aUl5cntLW1mbq6uqgPPvggNVC7ZcuWtZw6dSp248aNk++5555hA8WKFSsa33333RRJ2rNnT1xXV5cnJycn4Dyf2traqJtvvnn2o48+WnnDDTe09CwvKCjoSkpK8m3dujXJ5/Pp5Zdfnrxy5cpGSfr617/e+Oyzz06WpGeffXbyjTfe2Njzurq6uqiPPvoo5c4772w8/6cNj+ADAMAEZIzRrFmzulasWNEwd+7c4tWrV19SXFzcOlj7W265paG0tLQ5Kyurd/hoxYoVl1x77bVFR44ciZsyZcqCp59+OlOS7r///tojR47EzZ49u/j222+fsX79+iODDXP99Kc/zT527FjcE088Ma3nUPQTJ05ES9IzzzxTsW7dusKCgoL5hYWFHWvWrDkjSY899tipbdu2pRYUFMzftm1b6mOPPXaqZ3svv/xy+pe//OWzqampvoA/cLj3JdAY28UqLS21O3fuDPp2AQAIJWPMLmtt6cVsY/fu3UdLSkqGHS4KpaqqqqhFixbNO3ny5Gcjfc3SpUtnPfDAA6dXrlzZFMraxsLu3bszS0pKCgOtG7bHxxgTb4z5yBiz2xjzuTHmsaBXCAAAguLo0aMxV1555dz77rvv9Eja19bWRhUWFs6Pj4/3TYTQM5yRHNXVIWmZtbbZGBMj6QNjzK+ttX8IcW0AAGCUCgsLu44ePbp3pO0zMzO9o2k/mNdffz31oYce6ncG57y8vI4tW7YcuthtB9Owwcc6Y2HN/qcx/hsXXwMAAL1WrVp1dtWqVV+Eu47hjGhyszEmyhjzqaRqSVustR8GaLPWGLPTGLOzpqYm2HUCAABctBEFH2ut11p7uaRcSUuMMfMDtFlvrS211pZmZWUFu04AAICLNqrD2a21jZLek3RjSKoBAAAIoZEc1ZVljEn3P06QtFzSRV/xFQAAYKyNpMdnqqRtxpg9kv4oZ47Pv4a2LAAAcDEWLlxYNNT6JUuWXLpjx44hLy66Zs2awoyMjJLZs2cXD1z3+OOPZxcWFs6fNWtW8bp163IDvV6SNm7cmFpcXDx3zpw584qLi+du2rQppWfd+++/nzhnzpx5+fn58+++++68nstrfOc738m95JJLiufMmTPva1/72sza2tqontf86Ec/ysnPz59fWFg4//XXXw94JuqhDBt8rLV7rLULrbULrLXzrbV/O9ofAgAAxtYnn3xy0aMz3/72t2s3bdp0cODyN998M2Xz5s3pZWVln5eXl3/+8MMPVw22jezs7K7NmzeXHzhw4IsXXnjhyL333ntJz7rvfve7Bc8880zF0aNH9x4+fDh+w4YNqZL09a9//eyBAwc+P3DgwBezZs1qf/jhh3MkadeuXfFvvPFGxv79+z9/++23DzzwwAP53d0Br5QxKK7ODgBAqPzqvjxVfzFkr8qoZc9r1S0/H/aq74mJiQtfe+218ieffHLKtm3byiXpW9/6Vn5paWnL/fffX9fT7umnn87cu3dvwvPPP39ckp588snMsrKy+Oeee67ypptuat6/f3/swG3/4he/yHrwwQdPJSQkWEmaPn36oOnjmmuu6b3S++LFi9s7Ozs9bW1tprq6Orq5udmzfPnyFkn65je/WferX/1q0m233Xb21ltvPdvzmquuuqplw4YNkyRpw4YN6bfeemt9QkKCLSoq6iwoKOh47733knq2MRJcqwsAABe755576t955520niu3v/TSS5lr166tG+o1hw8fjt++fXvKggULiq644opLt2/fPqJw9+KLL06aN29ea0JCgq2oqIiZOnVqV8+6goKCzr5Xa+/xwgsvZN54441nJOnEiROxeXl5nT3rpk2b1nn8+PHzgtlQ6PEBACBURtAzE26pqam+a665punVV19Nu+yyy9q7urrMkiVL2oZ6jdfrNQ0NDVGffvrpvu3btyfeeeedM48fP/7ZYBcqlaSdO3fGP/LII9Pffvvtg5IU6Fqhxph+z3/wgx/kREVF2XXr1tUP8ZpRnVSZ4AMAwAQVExNjeyYMS1JPr85Aa9eurX388cdz5syZ037XXXcNe4HVnJycztWrVzd6PB4tXbq01ePx2Kqqquhp06YFHPI6dOhQzOrVq2c9//zzR4qLizsk59IafXt4KioqYnNycnp7gP7hH/5h8m9+85v0999//0BPoMrNze3Xw3Py5MnY3NzcLo0CQ10AAExQM2fO7CgvL09oa2szdXV1UR988EHAo6CWLVvWcurUqdiNGzdOvueee+qH2+6KFSsa33333RRJ2rNnT1xXV5cnJycnYOipra2Nuvnmm2c/+uijlTfccEPvXJyCgoKupKQk39atW5N8Pp9efvnlyStXrmyUpA0bNqT+7Gc/y3nrrbfKU1JSepPbqlWrGt94442MtrY2s2/fvtijR4/GX3fddSOe3yMRfAAAmJCMMZo1a1bXihUrGubOnVu8evXqS4qLi1sHa3/LLbc0lJaWNmdlZXl7lq1YseKSa6+9tujIkSNxU6ZMWfD0009nStL9999fe+TIkbjZs2cX33777TPWr19/ZLBhrp/+9KfZx44di3viiSemFRUVzSsqKpp34sSJaEl65plnKtatW1dYUFAwv7CwsGPNmjVnJOn73/9+fktLS9SyZcvmFBUVzbvzzjvzJam0tLT9lltuqZ8zZ07xjTfeOOepp56qiI4e3eCVCTRedrFKS0vtzp07g75dAABCyRizy1pbejHb2L1799GSkpJhh4tCqaqqKmrRokXzTp48+dlIX7N06dJZDzzwwOmVK1c2hbK2sbB79+7MkpKSwkDr6PEBAGACOXr0aMyVV14597777js9kva1tbVRhYWF8+Pj430TIfQMh8nNAABMIIWFhV1Hjx7dO9L2mZmZ3tG0H8zrr7+e+tBDD/U7g3NeXl7Hli1bDl3stoOJ4AMAAC7aqlWrzq5ateqLcNcxHIa6AAAILp/P5wt42DhCz//e+wZbT/ABACC49tbU1KQRfsaez+czNTU1aZIGHbpjqAsAgCDq7u6+t6qq6rmqqqr5ooNhrPkk7e3u7r53sAYEHwAAgmjx4sXVkr4R7joQGEkUAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4BsEHAAC4xrDBxxiTZ4zZZowpM8Z8boz53lgUBgAAEGzRI2jTLemvrbUfG2NSJO0yxmyx1n4R4toAAACCatgeH2vtKWvtx/7HTZLKJE0PdWEAAADBNqo5PsaYQkkLJX0YimIAAABCacTBxxiTLOl1SQ9Ya88GWL/WGLPTGLOzpqYmmDUCAAAExYiCjzEmRk7oedla+0agNtba9dbaUmttaVZWVjBrBAAACIqRHNVlJD0vqcxa+1ToSwIAAAiNkfT4XCPpzyUtM8Z86r/dHOK6AAAAgm7Yw9mttR9IMmNQCwAAQEhx5mYAAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAaBB8AAOAa0eEuAACAUenukCr+TTq4RUqbLl11X7grwjhC8AEARL7G41L5FifsHN4udbVIUXHSwm+GuzKMMwQfAEDk6e6Ujv/BCToHt0g1Zc7ytHyp5HZp9g3SJV+WYpPCWyfGHYIPACAynD3phJzyLdKh96TOJskTIxVcLS28S5r9NSlzjmRMuCvFOEbwAQCEh7dbqvxIOviOdPBd6fRnzvLUXOmyVf5ena9IcSnhrRMTCsEHADB2mk5L5e86YefQNqnjjOSJlvKvkpY/5oSd7Ln06iBkCD4AgNDxeaXKnf6Jye9Ip3Y7y5NzpHnfcIavZlwnxaeFs0q4CMEHABBcLbX+Xp0t0qGtUluDZKKkvCXS9Y84vTpT5tOrg7Ag+AAALo7PJ538xOnRKd8infhYkpWSsqVLb5ZmLZdmLpUSJoW7UoDgAwC4AK31UvlWJ+iUvyu11kkyUu4V0tKHpNnLpZwSycMFAhBZCD4AgOH5fFLV7nPn1TmxU7I+KXGy06Mz+wZp5jIpMSPclQJDIvgAAALz+aT9b0n7Nju9Oi3Vkow0fZH0lQedsDPtcskTFe5KgREj+AAAznf6C2nz96Vjv3fm5sy83jkCa+b1UnJWuKsDLtiwwccY80+S/lRStbV2fuhLAgCETWeL9N4T0h+ekeJSpZU/l0ruoFcHE8ZIenxekPQ/Jf1zaEsBAITVvs3SWw9KZyulRd9yTijInB1MMMMGH2vtDmNMYehLAQCERUOF9OsfSAd+LWUXS6ufl/KvDHdVQEgwxwcA3Kq7U/rDz6X3/l4yHumGv5O+tE6Kigl3ZUDIBC34GGPWSlorSfn5+cHaLAAgFI7+zpm8XLNPKvpT6aa/l9Jyw10VEHJBCz7W2vWS1ktSaWmpDdZ2AQBB1FIrvfOwtPtfpPR86Y5XpUtvDHdVwJhhqAsA3MDnkz75Z2nLj50jt679vvSV/yzFJoa7MmBMjeRw9l9Kuk5SpjGmUtKPrbXPh7owAECQVH0m/ev3pcqPpIJrpT99Ssq6NNxVAWExkqO67hiLQgAAQdbRJG37b/ghWesAAA78SURBVNKH/+ichPCWf5RKbueq6HA1hroAYKKxVirbJP36h1LTKWnx3dL1j3BOHkAEHwCYWOqPSL9+UDr4jjTlMum2f5byrgh3VUDEIPgAwETQ3SH92/+Qdvx3yRMtff2/SUvWSlH8mQf6Yo8AgPHuyA5n8nLdQWneSunGJ6TUaeGuCohIBB8AGK+aq6V3/kba86o0qVD65gbnCuoABkXwAYDxxueVdv1vaevfSp2tzvl4vvzXUkxCuCsDIh7BBwDGk5OfOpeaOLFLuuQr0p88JWXODndVwLhB8AGA8aD9rLTtcemj9VLiZOnW/yVdtoZz8gCjRPABgEhmrfT5RuntH0nNp6Ur7pGWPSwlpIe7MmBcIvgAQKSqOyS99Z+kQ7+VppZId/yLNH1xuKsCxjWCDwBEmu4O6YOfSe8/KUXFSjf9VLriXskTFe7KgHGP4AMAkeTQNmnzX0v1h6TiW6Wv/1cpdWq4qwImDIIPAESCpirpN/9F2vu6lDFD+vON0sxl4a4KmHAIPgAQTu1npN2vSr/9idTdLn31h9K1fyXFxIe7MmBCIvgAwFjpapeqPpNOfuych+fEx85lJiRpxlLpT56UJs8Mb43ABEfwAYBQ8Hmlmv1OwOkJOqc/l3zdzvrkHOcIrZJ/J+VdKRVeyzl5gDFA8AGAi2Wt1Fjh9OCc2CWd/MQ5w3JXi7M+Lk2adrl09f3S9EVO4OEiokBYEHwAYLSaa/y9OB+f69FprXPWRcVJUxdIC+9yAs70RVLGTMnjCW/NACQRfABgaB3N0qlP+4ecxmP+lUbKnivNucnfk7NIyi6WomPDWjKAwRF8AKBHd6dU/bl/4vEnzn3tfsn6nPXp+U4vzhX/3rmfWiLFJYe3ZgCjQvAB4E4+n1RX3v8Iq6rPJG+Hsz5xshNu5q08N2SVlBnemgFcNIIPgInPWunsyT4hZ5cz+bjjrLM+JsmZfPyltdI0/+Tj9HyOsgImIIIPgInH55Wqy6Rjv/ff/iCdPeGs80RLU+ZLl612As60RVLWpVwHC3AJgg+A8a+r3enNqfg3J+Qc/0jqOOOsS5kq5V8l5X1Jyi11Qg9nRQZci+ADYPxprXfCzTF/0Dn5ieTtdNZlFUnz/0zKv1rKv5IhKwD9EHwARDZrpTPHnYDT06NTU+as88RI0xZKX1onFVzt9OokZoS3XgARjeADILIMNT8nLlXKW+LMz8m/yjnSKiYhvPUCGFcIPgDCq2d+zrHfSxW/Dzw/p8A/bJU9j0nIAC4KwQfA2Oqdn+Pv0WF+DoAxRPABEFqNx5zhqp4eHebnAAgjgg+A4PH5pOovzs3NOfYH6Wyls475OQAiAMEHwOh1d0qNFVLdIan+kFR/2Ln8w4lPAszPeYD5OQAiBsEHQGDeLqmhwgk19YfOhZy6Q87h5T0X7pSk+DQpYybzcwBEPIIP4Gbebqfnpv7wgN6bQ87cHOs91zYuVcqY4Zz9eMG/kybPdMLO5JlSwiRCDoBxgeADTHTebunMMX+gGdB703hM8nWfaxubIk2e4Uw6nr+qf7hJnEy4ATDuEXyAicDndYaf6vw9Nn17cBoqJF/XubYxSU64yVkgFf+ZE2wyZjjhJimLcANgQiP4AJHC53OGlnxepxem97H33OPudqeXpv7Qud6b+sNSw9Fz58KRpJhEJ8xkz5PmrjjXa5MxQ0qeQrgB4FoEH4w/1johwNshdXc4k3C9Hc6RRt7OPo87nOe9j7v87fs+9r+m53F3h9M74hsmgPi6ncm9w7bxOoGmX5tBXis7uvchOsEJMplzpEtv6hNuZkopOYQbAAiA4DPR+LznvsTP+1Lu+cLt7vMF3d2npyHA8pF8YQf8svcO2Ja3/8/2dQ0SVIYKJ53nws5oQ8KQjBQdJ0XFSdGxzon1PNGSx+PcmyjnMGxPVJ/HfZZHxw5Y7jm/Te9rowdsZ6TL/bVExUhpuf5wM9WpEQAwYpEdfPb/Wjr6wTBfJH2/IDzB+XIZ8TY9/t6GzsC9B/16GwZ7PIJeiIFf+oP2cHT2PwonEhhPgLDgccJFdJwUFevcomOd4BEVK8Wn+h/H9A8kvW3jBjyO8bcZZHuBHvduL06KiuzdAAAQPJH9F//ELmnXC/17IvqeO2TCGNDj0O9Lv88XfGyylJAx/Bd5z2NPzNDBbSS9GcMuHyo0RjHcAgCIKJEdfJb9jXPrq2d+x3lDMyOZkzHYfItRzMPo+7Ot71wwOa8nIlA46ds7QY8DAABjbfx94xrjDwrRkuLCXQ0AABhHRjQz0hhzozFmvzGm3Bjzw1AXBQAAEArDBh9jTJSkn0u6SdI8SXcYY+aFujAAAIBgG0mPzxJJ5dbaw9baTkmvSFoZ2rIAAACCbyTBZ7qk432eV/qX9WOMWWuM2WmM2VlTUxOs+gAAAIJmJMEn0PHI5509zlq73lpbaq0tzcrKuvjKAAAAgmwkwadSUl6f57mSToamHAAAgNAZSfD5o6TZxphLjDGxkm6XtCm0ZQEAAATfsOfxsdZ2G2P+o6TfSIqS9E/W2s9DXhkAAECQjegEhtbatyS9FeJaAAAAQopLOwMAANcg+AAAANcw1p53ZPrFb9SYGkkVQdpcpqTaIG0r2CK5Nimy66O2CxfJ9VHbhYnk2qTIri/YtRVYazknywQWkuATTMaYndba0nDXEUgk1yZFdn3UduEiuT5quzCRXJsU2fVFcm2ITAx1AQAA1yD4AAAA1xgPwWd9uAsYQiTXJkV2fdR24SK5Pmq7MJFcmxTZ9UVybYhAET/HBwAAIFjGQ48PAABAUIQl+Bhj/skYU22M2TtEm0eNMdYYM6vPsr/yLwvJDH5jTLwx5iNjzG5jzOfGmMcGafeCMabVGJPSZ9n/568tMxS19fk56caYDcaYfcaYMmPMVQHajPl7N+DnD/n7NcbcYIz5vTHG+J9HGWM+NcZcHeK68owx2/zv2+fGmO9FSm3+nzXs588Ys9YY82qf56nGmEPGmEvGoL6jxpjP/O/HzgDrw/V7vdT/c3puZ40xD4SztsH2AWNMhjFmizHmoP9+0oD12caYI8aYnD7LnjHG/DCItQ26H4S7vqH2AeNcL/JDf22vGufakX1fW2yMOWCMSeizbLMx5vZg1IYJxFo75jdJX5G0SNLeIdo8KmmPpL/ps+x3kj6XVBqiuoykZP/jGEkfSroyQLsX/LXd5X/u8T+vlJQZ4vfuRUn3+h/HSkqPhPfuAn6/r/T5dzwg6X8FaBMd5LqmSlrkf5wi6YCkeZFQ20g/f/42v5O03P/8Z5IeGqP6jg73+Q7Xe9dn21GSquSciyVstQ22D0j6qaQf+h//UNLfB3jtOkkv+R8v8u/LMcGqc6j9INz1DbUPSHpN0u3+x/8o6T8EeP0Tkv7O//gWSe+M5eeP2/i4he8HS4UD/ygMWP+opL+V9Ef/8xlyrhf2nvxf3pLukPSZpL2BdtCLrC9R0seSvhRg3QuSfiTpTf/zZZJ+0feLQdL3/XXtlfRAkGpKlXRE/rlZkfrejfD3O1XSIUnFksolZfR5b5+StE3SkyH+DP7/kr4WobUN9flb4P+9lfp/h7H+5e9J+q+Stkv66xDU1Pv5jtTfq6QbJP0uEmoLtA9I2i9pap969gd4nUfS7yUtlfRvkr7iX363pP8j6U1Jvw1inb37QSTV13cfkBOIauUPLZKukvSbQV6zX9LlkvZJmu1f/qicSdDvSPqXUH3+uI2P24guUhpGZyUdN8bMl7RS0quS/h9JMsZMk/T3khZLapD0jjHmFmvtry7mBxpjoiTtkjRL0s+ttR8O0vSgpJX+ruA7JL0k6Sb/Nhb76+zZYT80xmy31n5yMbXJCTA1kv63MabEX+f3rLUtAdqO+Xs3GtbaU8aYn8n5A3q/tba+z+o5cno0vKH6+caYQkkL5fyPMmJqG8nnz1q7xxjzG0lbJd1ire3sszrdWvvVUNQmycr5rFhJz1przzuaJty/V0m3S/ploBURUJskTbHWnupTT3aAOn3GmP8g6beSNllrd/RZfZWkBQNqv2AB9oOw1xdoHzDOFIJGa223v1mlpOkBams1xvwnSTskPWWtPdhn9WJJ11pr2y60NkwM42Fy8yty/pjdImljn+VXSHrPWlvj3xleltO9fFGstV5r7eWSciUt8QeHwbzhr+1Lkt7vs/xaSRuttS3W2mZ/uy9fbG2SouV0Lf/CWrtQUouc7ujBjOl7dwF+LinKWvvCgOX/J8ShJ1nS63J64s5GUm2j+Pz9XNIJa+22ActfDdQ4SK6x1i6SE/DvM8YM9pkJ1+81VtI35PQ6DCYstY2WtfZTOb16zwxYtSWIoWck+8GY1zfIPmACNR3k9W9KagxQ2yZCD6TxEXzelPTnko4N2DkD7QhBY61tlDN0cOMQzV6R9BM5O7uvz/JQ1VYpqbJPL8AGOUFoMGF570bK/54F+uMVqAcrKIwxMXL+2L9srX0jkmob8POH+/z5/LeBQlaftfak/75aTpBeMki7cL13N0n62Fp7erAG4f69SjptjJkqSf776iHaBvodB6XOIfaDiKhPOm8fqJWUbozpGaXIlXQyXLVhfIv44ONP6D+Q9PiAVR9K+qoxJtPfNXqHnLkNF8wYk2WMSfc/TpC0XM448WC1HZP0kM7/n8UOSbcYYxKNMUmS/kz9e4QuiLW2Ss7w1aX+RddL+mKI9mP23o0H/iN6npdUZq19Ktz1DDTaz99YMsYkGf9RjP7P9A1y/scfSe7QIMNcEWSTpL/wP/4LOfNrxtQw+0FY6xtsH7DWWjlzsFaHqzZMHOE6nP2XcsbZLzXGVBpj7hmqvbX2FWvtxwOWnZIzwXibpN1y/qd3sTvCVEnbjDF7JP1RTk/Ovw5T27PW2kMDln0sZ8LkR3JCxnNBmN/T4y8lveyv8XI5k1mHqm+s3rteo/39jqFr5PSALetz6PPN4S6qj1F//sbQFEkfGGN2y/lcb7bWvh3mmnoZYxIlfU3OsHLYDbEPPCHpa8aYg3LqfSIM5Q21H4S7vqH2gR9I+r4xplzSZDnhDRg1ztwMAABcI+KHugAAAIKF4AMAAFyD4AMAAFyD4AMAAFyD4AMAAFyD4AMAAFyD4AMAAFyD4AMAAFzj/wLfWaXxukrEZQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**TASK: While the plot above clearly shows how rates fell from 2007 to 2020, putting these on the same plot makes it difficult to discern the rate differences within the same year. Use .suplots() to create the plot figure below, which shows each year's yield curve.**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [],
"source": [
"# DONT RUN THE CELL BELOW! IT WILL ERASE THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**BONUS CHALLENGE TASK: Try to recreate the plot below that uses twin axes. While this plot may actually be more confusing than helpful, its a good exercise in Matplotlib control.**"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"# CODE HERE"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"# DONT RUN THE CELL BELOW! IT ERASES THE PLOT!"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([0. , 0.2, 0.4, 0.6, 0.8, 1. , 1.2, 1.4]),\n",
" <a list of 8 Text yticklabel objects>)"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 2 Axes>"
]
},
"metadata": {
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