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Merge pull request #2 from stefmolin/slide-links
Add slide links to all notebooks
2 parents e96aaaf + 289ae03 commit 16322dd

8 files changed

+109
-28
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‎.github/workflows/env-checks.yml

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@@ -49,9 +49,9 @@ jobs:
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- name: strip hardcoded Python version from environment for testing
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run: |
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if [[ ${{ matrix.os }} == "macos"* ]]; then
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sed -i '' -e '/- python/d' environment.yml;
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sed -i '' -e '/- python[>=]/d' environment.yml;
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else
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sed -i -e '/- python/d' environment.yml;
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sed -i -e '/- python[>=]/d' environment.yml;
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fi;
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# create the conda env

‎notebooks/1-getting_started_with_pandas.ipynb

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{
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"cell_type": "markdown",
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"id": "654d989b-ca3b-4815-94f8-fe640ebbe9d2",
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"metadata": {},
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=github)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-1)\n",
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-1)\n",
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"\n",
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"---\n",
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"\n"
@@ -1041,7 +1046,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 1.1 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 1.1` above to open the workbook.ipynb file\n",
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"\n",
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"# WARNING: if you complete the exercise here, your cell numbers\n",
@@ -1065,7 +1070,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 1.2 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 1.2` above to open the workbook.ipynb file\n",
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"\n",
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"# WARNING: if you complete the exercise here, your cell numbers\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 1.3 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 1.3` above to open the workbook.ipynb file"
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]
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 1.4 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 1.4` above to open the workbook.ipynb file"
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]
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎notebooks/2-data_wrangling.ipynb

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{
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"cell_type": "markdown",
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"id": "2ea64fb3-084e-4467-90ce-f3f6356cd3c3",
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"metadata": {},
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=github)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-2)\n",
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-2)\n",
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"\n",
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"---\n",
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"\n"
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 2.1 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 2.1` above to open the workbook.ipynb file\n",
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"\n",
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"# WARNING: if you complete the exercise here, your cell numbers\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 2.2 in the workbook.ipynb file"
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"# Complete this exercise in the workbook.ipynb file"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 2.3 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 2.3` above to open the workbook.ipynb file\n",
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"\n",
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"# WARNING: if you complete the exercise here, your cell numbers\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 2.4 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 2.4` above to open the workbook.ipynb file\n",
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"\n",
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"# WARNING: if you complete the exercise here, your cell numbers\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 2.5 in the workbook.ipynb file\n",
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"# Complete this exercise in the workbook.ipynb file\n",
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"# Click on `Exercise 2.5` above to open the workbook.ipynb file"
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]
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎notebooks/3-data_visualization.ipynb

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{
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"cell_type": "markdown",
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"id": "b0bcc073-5ee3-4447-97bc-b5cdaa8d9f8b",
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"metadata": {},
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=github)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-3)\n",
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-3)\n",
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"\n",
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"---\n",
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"\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 3.1 in the workbook.ipynb file"
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"# Complete this exercise in the workbook.ipynb file"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 3.2 in the workbook.ipynb file"
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"# Complete this exercise in the workbook.ipynb file"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# Complete exercise 3.3 in the workbook.ipynb file"
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"# Complete this exercise in the workbook.ipynb file"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# TIP: the solution to exercise 3.1 can be found at\n",
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"# TIP: the solution to Exercise 3.1 can be found at\n",
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"# https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/solution-3-1"
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]
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎slides/0-introduction.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "73de9609-9539-483a-a930-1f1b12b79a55",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html)\n",
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"\n",
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"---\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8b7dfb40-1ef0-4621-89c3-87c5b226c023",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎slides/1-getting_started_with_pandas.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "d7d8affa-124f-4132-88ba-6729aab0ff2e",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-1)\n",
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"\n",
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"---\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2c0397e0-4592-48dd-90d9-6a6dc95be2f9",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎slides/2-data_wrangling.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "0ceea5a6-c4bf-48f6-9644-d8d96b635abf",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-2)\n",
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"\n",
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"---\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a0745604-3c71-4c7f-8b5c-b6cc0ecec3c3",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎slides/3-data_visualization.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "c80f1fcd-b245-459f-9cb0-723ac3020ddd",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"[![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/section-3)\n",
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"\n",
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"---\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ca73b481-0ab1-442a-b602-a1dc4c51f396",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

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