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Merge pull request #192 from ryanleeallred/master
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Splits Module 3 Notebooks
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ryanleeallred authored Aug 14, 2019
2 parents 6fc53f4 + 4cee2c3 commit 222b669
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"name": "LS_DS_123_Make_Explanatory_Visualizations.ipynb",
"version": "0.3.2",
"provenance": [],
"collapsed_sections": []
"collapsed_sections": [],
"include_colab_link": true
},
"language_info": {
"codemirror_mode": {
Expand All @@ -27,6 +28,16 @@
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/ryanleeallred/DS-Unit-1-Sprint-2-Data-Wrangling-and-Storytelling/blob/master/module3-make-explanatory-visualizations/LS_DS_123_Make_Explanatory_Visualizations.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
Expand Down Expand Up @@ -304,11 +315,11 @@
"metadata": {
"id": "h-aIS1Vdn2RR",
"colab_type": "code",
"outputId": "7acbb0e3-2133-44e9-b684-8d0b5f9a4411",
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},
"source": [
"import numpy as np\n",
Expand Down Expand Up @@ -446,7 +457,7 @@
"\n",
"plt.show()"
],
"execution_count": 1,
"execution_count": 0,
"outputs": [
{
"output_type": "display_data",
Expand Down Expand Up @@ -662,63 +673,6 @@
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "NMEswXWh9mqw"
},
"source": [
"# ASSIGNMENT\n",
"\n",
"Replicate the lesson code. I recommend that you [do not copy-paste](https://docs.google.com/document/d/1ubOw9B3Hfip27hF2ZFnW3a3z9xAgrUDRReOEo-FHCVs/edit).\n",
"\n",
"# STRETCH OPTIONS\n",
"\n",
"#### 1) Reproduce another example from [FiveThityEight's shared data repository](https://data.fivethirtyeight.com/).\n",
"\n",
"#### 2) Reproduce one of the following using a library other than Seaborn or Matplotlib.\n",
"\n",
"For example:\n",
"- [thanksgiving-2015](https://fivethirtyeight.com/features/heres-what-your-part-of-america-eats-on-thanksgiving/) (try the [`altair`](https://altair-viz.github.io/gallery/index.html#maps) library)\n",
"- [candy-power-ranking](https://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/) (try the [`statsmodels`](https://www.statsmodels.org/stable/index.html) library)\n",
"- or another example of your choice!\n",
"\n",
"#### 3) Make more charts!\n",
"\n",
"Choose a chart you want to make, from [Visual Vocabulary - Vega Edition](http://ft.com/vocabulary).\n",
"\n",
"Find the chart in an example gallery of a Python data visualization library:\n",
"- [Seaborn](http://seaborn.pydata.org/examples/index.html)\n",
"- [Altair](https://altair-viz.github.io/gallery/index.html)\n",
"- [Matplotlib](https://matplotlib.org/gallery.html)\n",
"- [Pandas](https://pandas.pydata.org/pandas-docs/stable/visualization.html)\n",
"\n",
"Reproduce the chart. [Optionally, try the \"Ben Franklin Method.\"](https://docs.google.com/document/d/1ubOw9B3Hfip27hF2ZFnW3a3z9xAgrUDRReOEo-FHCVs/edit) If you want, experiment and make changes.\n",
"\n",
"Take notes. Consider sharing your work with your cohort!\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
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""
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@@ -0,0 +1,122 @@
{
"nbformat": 4,
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"metadata": {
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"name": "LS_DS_123_Make_Explanatory_Visualizations_Assignment.ipynb",
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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/ryanleeallred/DS-Unit-1-Sprint-2-Data-Wrangling-and-Storytelling/blob/master/module3-make-explanatory-visualizations/LS_DS_123_Make_Explanatory_Visualizations_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "NMEswXWh9mqw"
},
"source": [
"# ASSIGNMENT\n",
"\n",
"### 1) Replicate the lesson code. I recommend that you [do not copy-paste](https://docs.google.com/document/d/1ubOw9B3Hfip27hF2ZFnW3a3z9xAgrUDRReOEo-FHCVs/edit).\n",
"\n",
"### 2) Reproduce one of the following using the matplotlib or seaborn libraries:\n",
"\n",
"- [thanksgiving-2015](https://fivethirtyeight.com/features/heres-what-your-part-of-america-eats-on-thanksgiving/) (try the [`altair`](https://altair-viz.github.io/gallery/index.html#maps) library)\n",
"- [candy-power-ranking](https://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/) (try the [`statsmodels`](https://www.statsmodels.org/stable/index.html) library)\n",
"- or another example of your choice!\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "7SY1ZHawyZvz",
"colab_type": "code",
"colab": {}
},
"source": [
"# Your Work Here"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "0wSrBzmJyWaV",
"colab_type": "text"
},
"source": [
"# STRETCH OPTIONS\n",
"\n",
"### 2) Reproduce another example from [FiveThityEight's shared data repository](https://data.fivethirtyeight.com/).\n",
"\n",
"\n",
"### 3) Make more charts!\n",
"\n",
"Choose a chart you want to make, from [Visual Vocabulary - Vega Edition](http://ft.com/vocabulary).\n",
"\n",
"Find the chart in an example gallery of a Python data visualization library:\n",
"- [Seaborn](http://seaborn.pydata.org/examples/index.html)\n",
"- [Altair](https://altair-viz.github.io/gallery/index.html)\n",
"- [Matplotlib](https://matplotlib.org/gallery.html)\n",
"- [Pandas](https://pandas.pydata.org/pandas-docs/stable/visualization.html)\n",
"\n",
"Reproduce the chart. [Optionally, try the \"Ben Franklin Method.\"](https://docs.google.com/document/d/1ubOw9B3Hfip27hF2ZFnW3a3z9xAgrUDRReOEo-FHCVs/edit) If you want, experiment and make changes.\n",
"\n",
"Take notes. Consider sharing your work with your cohort!"
]
},
{
"cell_type": "code",
"metadata": {
"id": "dRJkKftiy5BJ",
"colab_type": "code",
"colab": {}
},
"source": [
"# More Work Here"
],
"execution_count": 0,
"outputs": []
}
]
}

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