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# Overview of the first day
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Remainder of the morning:
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* Introduction to Jupyter notebook
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* Recap of the basic python and numpy syntax
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Afternoon:
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* Introduction to Jupyter notebook/lab
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* Introduction to Pandas fundamentals
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![:scale 80%](./img/issuetracker.png)
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Report bugs, typo's, suggestions... as issues ([New issue](https://github.com/jorisvandenbossche/DS-python-data-analysis/issues/new))
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Report bugs, typo's, suggestions... as issues ([New issue](https://github.com/jorisvandenbossche/DS-python-data-analysis/issues/new)) or just by mail.
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or see the [contributing guidelines](https://github.com/jorisvandenbossche/DS-python-data-analysis/blob/master/CONTRIBUTING.md)
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# Python, the basics...
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1. `python_recap/00-jupyter_introduction.ipynb`
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2. `python_recap/python_rehearsal.ipynb`
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# Pandas
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# Install remaining packages
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```
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conda install pyproj
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conda install -c conda-forge plotnine
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conda install -c conda-forge mplleaflet
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```
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## Then start with *case study 1:* Bike count (`case1_bike_count.ipynb`)
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# Overview of the second day
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1. *Case study:* Bike count
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2. Pandas: indexing part II
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3. Pandas: groupby operations
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4. *Case study:* Processing observations field study data
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5. Visualization: Introduction to matplotlib and plotnine
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5. Visualization: Introduction to matplotlib and seaborn
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6. Pandas: reshaping data
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7. *Case study:* Bacterial resistance lab study
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## Continue with *case study 3:* Bacterial resistance (`case3_bacterial_resistance_lab_experiment.ipynb`)
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2. *Case study:* Analyse observations field study data
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3. *Case study:* Analyse air quality sensor data
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4. *Case study:* Process air quality sensor data
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5. Visualization: overview other tools
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5. Visualization: overview visualization landscape
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6. Closing remarks
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