add kaggle datasets to README, plus other tweaks

shera-amit · Jun 17, 2016 · 1d58125 · 1d58125
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commit 1d58125
Showing 1 changed file with 5 additions and 5 deletions.
diff --git a/README.md b/README.md
@@ -1,12 +1,10 @@
 # Python pandas Q&A video series
 
-Materials from the Data School video series about Python's pandas library.
+Read about the series, and view all of the videos on one page: [Easier data analysis in Python with pandas](http://www.dataschool.io/easier-data-analysis-with-pandas/).
 
-Read more about the series, and view all of the videos on one page: [Easier data analysis in Python with pandas](http://www.dataschool.io/easier-data-analysis-with-pandas/)
+### Code
 
-### [IPython/Jupyter Notebook](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb)
-
-Commented code and resources links from each video
+The [IPython/Jupyter Notebook](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb) contains commented code and resources links from each video.
 
 ### Videos ([playlist](https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y))
 
@@ -38,5 +36,7 @@ Filename | Description | Raw File | Original Source | Other
 [chipotle.tsv](data/chipotle.tsv) | Online orders from the Chipotle restaurant chain | [bit.ly/chiporders](http://bit.ly/chiporders) | [The Upshot](https://github.com/TheUpshot/chipotle) | [Upshot article](http://www.nytimes.com/interactive/2015/02/17/upshot/what-do-people-actually-order-at-chipotle.html)
 [drinks.csv](data/drinks.csv) | Alcohol consumption by country | [bit.ly/drinksbycountry](http://bit.ly/drinksbycountry) | [FiveThirtyEight](https://github.com/fivethirtyeight/data/tree/master/alcohol-consumption) | [FiveThirtyEight article](http://fivethirtyeight.com/datalab/dear-mona-followup-where-do-people-drink-the-most-beer-wine-and-spirits/)
 [imdb_1000.csv](data/imdb_1000.csv) | Top rated movies from IMDb | [bit.ly/imdbratings](http://bit.ly/imdbratings) | [IMDb](http://www.imdb.com/search/title?groups=top_1000&sort=user_rating&view=simple) | [Web scraping script](https://github.com/justmarkham/DAT5/blob/master/code/08_web_scraping.py)
+[titanic_test.csv](data/titanic_test.csv) | Testing set from Kaggle's Titanic competition | [bit.ly/kaggletest](http://bit.ly/kaggletest) | [Kaggle](https://www.kaggle.com/c/titanic) | [Data dictionary](https://www.kaggle.com/c/titanic/data)
+[titanic_train.csv](data/titanic_train.csv) | Training set from Kaggle's Titanic competition | [bit.ly/kaggletrain](http://bit.ly/kaggletrain) | [Kaggle](https://www.kaggle.com/c/titanic) | [Data dictionary](https://www.kaggle.com/c/titanic/data)
 [u.user](data/u.user) | Demographic information about MovieLens users | [bit.ly/movieusers](http://bit.ly/movieusers) | [GroupLens](http://grouplens.org/datasets/movielens/100k/) | [Data dictionary](http://files.grouplens.org/datasets/movielens/ml-100k-README.txt)
 [ufo.csv](data/ufo.csv) | Reports of UFO sightings from 1930-2000 | [bit.ly/uforeports](http://bit.ly/uforeports) | [National UFO Reporting Center](http://www.nuforc.org/webreports.html) | [Web scraping script](https://github.com/josiahdavis/josiahdavis.github.io/blob/master/supporting%20material/get_ufo_data.py)