Notebooks for Python for R Users: A Data Science Approach
- Command Line
- Rodeo
- IDLE
- Jupyter
- Beaker
Introductory Python https://nbviewer.jupyter.org/gist/decisionstats/ce2c16ee98abcf328177 Selecting Data in Pandas https://nbviewer.jupyter.org/gist/decisionstats/01fc540363f1081c5358
- Yelp with Beautiful Soup http://nbviewer.ipython.org/gist/decisionstats/3385dc84c39109f49b83
- Using PyCurl for Web Scraping
- Using Scrapy for Web Scraping
- Social Media Scraping
- Cricket Analysis
- MySQL
- MongoDB
- HDFS
- Spark
- Using SQL for Groupby https://nbviewer.jupyter.org/gist/decisionstats/284a86d0541d06489e92
- Using For Loops
- Apply and Lambda
- Converting data from one format to another ( str)
- Using grepl and gsub
- Subset of a DataFrame and List
- Conditional Manipulation
- Adult DataSet http://nbviewer.ipython.org/gist/decisionstats/4142e98375445c5e4174
- Big Diamonds Dataset
- Iris Dataset
- Basic Plots using MatplotLib
- Advanced Plots using Seaborn
- Data Visualization using GGPlot http://nbviewer.ipython.org/gist/decisionstats/df98ff9df42e7764d600
- Plots using Bokeh
- Anscombe Dataset http://nbviewer.jupyter.org/gist/decisionstats/3737642751895f470d5c07194302f53e
- Using Statsmodels (Boston Dataset)
- Using Pandas
- Using Scikit-learn
- Decision Trees
- Association Analysis
- Clustering Kmeans and Hierarchical
- Neural Networks
- ROC Curves for Models
- ETS Models
- Arima Models
- Measuring Code Speed
- Measuring Code Performance
- Word Cloud (corpus,stopwords,association,tdm)
- Sentiment Analysis
- Diamonds Dataset http://nbviewer.ipython.org/gist/decisionstats/c1684daaeecf62dd4bf4
- StatisticsViews Data Science Tutorial http://www.statisticsviews.com/details/feature/8868901/A-Tutorial-on-Python.html
Spatial Data using Python http://sensitivecities.com/so-youd-like-to-make-a-map-using-python-EN.html#.V4EneVgrJ-8 http://nbviewer.jupyter.org/gist/urschrei/74c6223d9f6a5dea4e75 http://spatialdemography.org/essential-python-geospatial-libraries/
#Datasets http://www.gunviolencearchive.org/ Washington Post https://github.com/washingtonpost/data-police-shootings