diff --git a/README.md b/README.md
index a3018bd..3201d1a 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# IMB-Data-Visualization-With-Python
-## My data visualization projects using pandas and matplotlib, seaborn, and Folium.
+## My data visualization projects using pandas, matplotlib, seaborn, and Folium.
Objective: enhance my skills in advanced data visualization.
diff --git a/Yun-1-1-1-Introduction-to-Matplotlib-and-Line-Plots-py-v2.0.ipynb b/Yun-1-1-1-Introduction-to-Matplotlib-and-Line-Plots-py-v2.0.ipynb
index b1a8154..493a627 100644
--- a/Yun-1-1-1-Introduction-to-Matplotlib-and-Line-Plots-py-v2.0.ipynb
+++ b/Yun-1-1-1-Introduction-to-Matplotlib-and-Line-Plots-py-v2.0.ipynb
@@ -1,20 +1,5 @@
{
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- "metadata": {
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- },
- "source": [
- "
\n",
- "\n",
- "
Introduction to Matplotlib and Line Plots
"
- ]
- },
{
"cell_type": "markdown",
"metadata": {
@@ -37,49 +22,6 @@
"------------"
]
},
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "## Table of Contents\n",
- "\n",
- "\n",
- "\n",
- "1. [Exploring Datasets with *pandas*](#0)
\n",
- "1.1 [The Dataset: Immigration to Canada from 1980 to 2013](#2)
\n",
- "1.2 [*pandas* Basics](#4)
\n",
- "1.3 [*pandas* Intermediate: Indexing and Selection](#6)
\n",
- "2. [Visualizing Data using Matplotlib](#8)
\n",
- "2.1 [Matplotlib: Standard Python Visualization Library](#10)
\n",
- "3. [Line Plots](#12)\n",
- "
\n",
- "
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "# Exploring Datasets with *pandas* \n",
- "\n",
- "*pandas* is an essential data analysis toolkit for Python. From their [website](http://pandas.pydata.org/):\n",
- ">*pandas* is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, **real world** data analysis in Python.\n",
- "\n",
- "The course heavily relies on *pandas* for data wrangling, analysis, and visualization. We encourage you to spend some time and familizare yourself with the *pandas* API Reference: http://pandas.pydata.org/pandas-docs/stable/api.html."
- ]
- },
{
"cell_type": "markdown",
"metadata": {
@@ -4948,6 +4890,7 @@
"execution_count": 88,
"metadata": {
"button": false,
+ "collapsed": true,
"jupyter": {
"outputs_hidden": false
},
@@ -6127,51 +6070,6 @@
"* `scatter` for scatter plots\n",
"* `hexbin` for hexbin plot"
]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "### Thank you for completing this lab!\n",
- "\n",
- "This notebook was originally created by [Jay Rajasekharan](https://www.linkedin.com/in/jayrajasekharan) with contributions from [Ehsan M. Kermani](https://www.linkedin.com/in/ehsanmkermani), and [Slobodan Markovic](https://www.linkedin.com/in/slobodan-markovic).\n",
- "\n",
- "This notebook was recently revised by [Alex Aklson](https://www.linkedin.com/in/aklson/). I hope you found this lab session interesting. Feel free to contact me if you have any questions!"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "This notebook is part of a course on **Coursera** called *Data Visualization with Python*. If you accessed this notebook outside the course, you can take this course online by clicking [here](http://cocl.us/DV0101EN_Coursera_Week1_LAB1)."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "
\n",
- "\n",
- "Copyright © 2019 [Cognitive Class](https://cognitiveclass.ai/?utm_source=bducopyrightlink&utm_medium=dswb&utm_campaign=bdu). This notebook and its source code are released under the terms of the [MIT License](https://bigdatauniversity.com/mit-license/)."
- ]
}
],
"metadata": {
diff --git a/Yun-2-2-1-Area-Plots-Histograms-and-Bar-Charts-py-v2.0.ipynb b/Yun-2-2-1-Area-Plots-Histograms-and-Bar-Charts-py-v2.0.ipynb
index ab481c4..e80e6f7 100644
--- a/Yun-2-2-1-Area-Plots-Histograms-and-Bar-Charts-py-v2.0.ipynb
+++ b/Yun-2-2-1-Area-Plots-Histograms-and-Bar-Charts-py-v2.0.ipynb
@@ -4,25 +4,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
- "new_sheet": false,
- "run_control": {
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- }
- },
- "source": [
- "
\n",
- "\n",
- "Area Plots, Histograms, and Bar Plots
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "deletable": true,
- "editable": true,
"new_sheet": false,
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@@ -38,34 +19,6 @@
"cell_type": "markdown",
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- "deletable": true,
- "editable": true,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "## Table of Contents\n",
- "\n",
- "\n",
- "\n",
- "1. [Exploring Datasets with *pandas*](#0)
\n",
- "2. [Downloading and Prepping Data](#2)
\n",
- "3. [Visualizing Data using Matplotlib](#4)
\n",
- "4. [Area Plots](#6)
\n",
- "5. [Histograms](#8)
\n",
- "6. [Bar Charts](#10)
\n",
- "
\n",
- "
"
- ]
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- "collapsed": false,
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- "editable": true,
"jupyter": {
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},
@@ -3601,7 +3389,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
@@ -3616,7 +3403,6 @@
"execution_count": 36,
"metadata": {
"button": false,
- "deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
@@ -3658,7 +3444,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
"new_sheet": false,
"run_control": {
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@@ -3707,8 +3492,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
"new_sheet": false,
"run_control": {
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@@ -3729,8 +3512,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
"new_sheet": false,
"run_control": {
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@@ -3753,9 +3534,6 @@
"execution_count": 37,
"metadata": {
"button": false,
- "collapsed": false,
- "deletable": true,
- "editable": true,
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@@ -3792,9 +3570,6 @@
"execution_count": 38,
"metadata": {
"button": false,
- "collapsed": false,
- "deletable": true,
- "editable": true,
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@@ -3832,8 +3607,6 @@
"cell_type": "markdown",
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- "deletable": true,
- "editable": true,
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@@ -3862,9 +3635,6 @@
"execution_count": 55,
"metadata": {
"button": false,
- "collapsed": false,
- "deletable": true,
- "editable": true,
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@@ -3909,8 +3679,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
"new_sheet": false,
"run_control": {
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@@ -3928,9 +3696,6 @@
"execution_count": 53,
"metadata": {
"button": false,
- "collapsed": false,
- "deletable": true,
- "editable": true,
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@@ -3983,8 +3748,6 @@
"cell_type": "markdown",
"metadata": {
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- "deletable": true,
- "editable": true,
"new_sheet": false,
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@@ -4003,8 +3766,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
"new_sheet": false,
"run_control": {
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@@ -4019,7 +3780,6 @@
"execution_count": 130,
"metadata": {
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- "deletable": true,
"new_sheet": false,
"run_control": {
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@@ -4063,7 +3823,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
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"run_control": {
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@@ -4087,8 +3846,6 @@
"cell_type": "markdown",
"metadata": {
"button": false,
- "deletable": true,
- "editable": true,
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@@ -4106,7 +3863,6 @@
"execution_count": 143,
"metadata": {
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- "deletable": true,
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@@ -4183,7 +3939,6 @@
"cell_type": "markdown",
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- "deletable": true,
"new_sheet": false,
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@@ -4211,64 +3966,13 @@
"plt.show()\n",
"-->"
]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "deletable": true,
- "editable": true,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "### Thank you for completing this lab!\n",
- "\n",
- "This notebook was originally created by [Jay Rajasekharan](https://www.linkedin.com/in/jayrajasekharan) with contributions from [Ehsan M. Kermani](https://www.linkedin.com/in/ehsanmkermani), and [Slobodan Markovic](https://www.linkedin.com/in/slobodan-markovic).\n",
- "\n",
- "This notebook was recently revamped by [Alex Aklson](https://www.linkedin.com/in/aklson/). I hope you found this lab session interesting. Feel free to contact me if you have any questions!"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "deletable": true,
- "editable": true,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "This notebook is part of a course on **Coursera** called *Data Visualization with Python*. If you accessed this notebook outside the course, you can take this course online by clicking [here](http://cocl.us/DV0101EN_Coursera_Week2_LAB1)."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "button": false,
- "deletable": true,
- "editable": true,
- "new_sheet": false,
- "run_control": {
- "read_only": false
- }
- },
- "source": [
- "
\n",
- "\n",
- "Copyright © 2019 [Cognitive Class](https://cognitiveclass.ai/?utm_source=bducopyrightlink&utm_medium=dswb&utm_campaign=bdu). This notebook and its source code are released under the terms of the [MIT License](https://bigdatauniversity.com/mit-license/)."
- ]
}
],
"metadata": {
"kernelspec": {
- "display_name": "Python",
+ "display_name": "Python 3",
"language": "python",
- "name": "conda-env-python-py"
+ "name": "python3"
},
"language_info": {
"codemirror_mode": {
@@ -4280,7 +3984,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.7"
+ "version": "3.6.3"
},
"widgets": {
"state": {},