"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sylchE7jCpQP"
},
"source": [
"# Module 10: Logscale\n",
"\n",
"In this module, we will learn why we want to use log scale for some types of data and strategies for using log scale. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "9xAAtok8CpQS",
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import numpy as np\n",
"import scipy.stats as ss\n",
"import vega_datasets"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XPs_sZrtCpQT"
},
"source": [
"## Ratio and logarithm\n",
"\n",
"If you use linear scale to visualize ratios, it can be quite misleading. As learned in the class, ratio values larger than 1 can vary between 1 and infinite, while ratio values smaller than 1 can vary only between 0 and 1. For instance, the ratios of 100:1 (100/1) or 1000:1 (1000/1) are represented as 100 and 1000. The corresponding distances from 1:1 (1) are 99 and 999, respectively. On the other hand, the ratios of 1:100 (1/100) or 1:1000 (1/1000) are represented as 0.01 and 0.001. The corresponding distances from 1:1 (1) are 0.99 and 0.999, respectively. In other words, there is no symmetry between symmetric ratios! \n",
"\n",
"You can watch my video [Why you should use logarithmic scale when visualizing ratios](https://www.youtube.com/watch?v=Q9azoaH7gds). \n",
"\n",
"To see this clearly, let's first create some ratios."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "02uwOpjPCpQT",
"jupyter": {
"outputs_hidden": false
},
"outputId": "400ffda2-d774-4e8e-d544-5454d8fd3426"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1.e-03 1.e-02 1.e-01 1.e+00 1.e+01 1.e+02 1.e+03]\n"
]
}
],
"source": [
"x = np.array([1, 1, 1, 1, 10, 100, 1000])\n",
"y = np.array([1000, 100, 10, 1, 1, 1, 1 ])\n",
"ratio = x/y\n",
"print(ratio)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ZOV3oQV3CpQU"
},
"source": [
"**Q: Plot on the linear scale using the [`scatter()`](http://matplotlib.org/examples/shapes_and_collections/scatter_demo.html) function. Also draw a horizontal line at ratio=1 for a reference. The x-axis will be simply the data ID that refers to each ratio data point. Y-axis will be the ratio values.**"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "lsamHuF0CpQU",
"jupyter": {
"outputs_hidden": false
},
"outputId": "6ca653d8-a7da-415f-919d-2cc40052959d"
},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Ratio')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"X = np.arange(len(ratio))\n",
"\n",
"# YOUR SOLUTION HERE"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "tiPVu02nCpQV"
},
"source": [
"**Q: Is this a good visualization of the ratio data? Why? Why not? Explain.**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "33JTlQ07CpQV"
},
"source": [
"# YOUR SOLUTION HERE"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "wOC-1c-WCpQW"
},
"source": [
"**Q: Can you fix it?**"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"id": "gCKaobcWCpQW",
"jupyter": {
"outputs_hidden": false
},
"outputId": "852092fc-1a3f-42ae-e77d-712ee58656d3"
},
"outputs": [],
"source": [
"# YOUR SOLUTION HERE"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "yCRyKvTbCpQW"
},
"source": [
"## Log-binning\n",
"\n",
"One way to draw a histogram in log-scale, with a broadly distributed data, is by using log-binning. \n",
"\n",
"Let's first see what happens if we do not use the log scale for a dataset with a heavy tail.\n",
"\n",
"**Q: Load the movie dataset from `vega_datasets` and remove the NaN rows based on the following columns: `IMDB Rating`, `IMDB Votes`, `Worldwide_Gross`, `Rotten Tomatoes Rating`.**"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "0qBZGnGZCpQX"
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
Title
\n",
"
US_Gross
\n",
"
Worldwide_Gross
\n",
"
US_DVD_Sales
\n",
"
Production_Budget
\n",
"
Release_Date
\n",
"
MPAA_Rating
\n",
"
Running_Time_min
\n",
"
Distributor
\n",
"
Source
\n",
"
Major_Genre
\n",
"
Creative_Type
\n",
"
Director
\n",
"
Rotten_Tomatoes_Rating
\n",
"
IMDB_Rating
\n",
"
IMDB_Votes
\n",
"
\n",
" \n",
" \n",
"
\n",
"
4
\n",
"
Slam
\n",
"
1009819.0
\n",
"
1087521.0
\n",
"
NaN
\n",
"
1000000.0
\n",
"
Oct 09 1998
\n",
"
R
\n",
"
NaN
\n",
"
Trimark
\n",
"
Original Screenplay
\n",
"
Drama
\n",
"
Contemporary Fiction
\n",
"
None
\n",
"
62.0
\n",
"
3.4
\n",
"
165.0
\n",
"
\n",
"
\n",
"
8
\n",
"
Pirates
\n",
"
1641825.0
\n",
"
6341825.0
\n",
"
NaN
\n",
"
40000000.0
\n",
"
Jul 01 1986
\n",
"
R
\n",
"
NaN
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
Roman Polanski
\n",
"
25.0
\n",
"
5.8
\n",
"
3275.0
\n",
"
\n",
"
\n",
"
9
\n",
"
Duel in the Sun
\n",
"
20400000.0
\n",
"
20400000.0
\n",
"
NaN
\n",
"
6000000.0
\n",
"
Dec 31 2046
\n",
"
None
\n",
"
NaN
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
86.0
\n",
"
7.0
\n",
"
2906.0
\n",
"
\n",
"
\n",
"
10
\n",
"
Tom Jones
\n",
"
37600000.0
\n",
"
37600000.0
\n",
"
NaN
\n",
"
1000000.0
\n",
"
Oct 07 1963
\n",
"
None
\n",
"
NaN
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
None
\n",
"
81.0
\n",
"
7.0
\n",
"
4035.0
\n",
"
\n",
"
\n",
"
11
\n",
"
Oliver!
\n",
"
37402877.0
\n",
"
37402877.0
\n",
"
NaN
\n",
"
10000000.0
\n",
"
Dec 11 1968
\n",
"
None
\n",
"
NaN
\n",
"
Sony Pictures
\n",
"
None
\n",
"
Musical
\n",
"
None
\n",
"
None
\n",
"
84.0
\n",
"
7.5
\n",
"
9111.0
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Title US_Gross Worldwide_Gross US_DVD_Sales \n",
"4 Slam 1009819.0 1087521.0 NaN \\\n",
"8 Pirates 1641825.0 6341825.0 NaN \n",
"9 Duel in the Sun 20400000.0 20400000.0 NaN \n",
"10 Tom Jones 37600000.0 37600000.0 NaN \n",
"11 Oliver! 37402877.0 37402877.0 NaN \n",
"\n",
" Production_Budget Release_Date MPAA_Rating Running_Time_min \n",
"4 1000000.0 Oct 09 1998 R NaN \\\n",
"8 40000000.0 Jul 01 1986 R NaN \n",
"9 6000000.0 Dec 31 2046 None NaN \n",
"10 1000000.0 Oct 07 1963 None NaN \n",
"11 10000000.0 Dec 11 1968 None NaN \n",
"\n",
" Distributor Source Major_Genre Creative_Type \n",
"4 Trimark Original Screenplay Drama Contemporary Fiction \\\n",
"8 None None None None \n",
"9 None None None None \n",
"10 None None None None \n",
"11 Sony Pictures None Musical None \n",
"\n",
" Director Rotten_Tomatoes_Rating IMDB_Rating IMDB_Votes \n",
"4 None 62.0 3.4 165.0 \n",
"8 Roman Polanski 25.0 5.8 3275.0 \n",
"9 None 86.0 7.0 2906.0 \n",
"10 None 81.0 7.0 4035.0 \n",
"11 None 84.0 7.5 9111.0 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# YOUR SOLUTION HERE"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mHesgk87CpQX"
},
"source": [
"If you simply call `hist()` method with a dataframe object, it identifies all the numeric columns and draw a histogram for each.\n",
"\n",
"**Q: draw all possible histograms of the movie dataframe. Adjust the size of the plots if needed.**"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"id": "9ob4iXNCCpQX",
"jupyter": {
"outputs_hidden": false
},
"outputId": "4b246a8b-a97a-4a5d-deab-7f831acd8906"
},
"outputs": [
{
"data": {
"image/png": 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