Use asterisk for top-level bullets in markdown
@@ -32,7 +32,7 @@ Tablesaw supports data visualization by providing a wrapper for the Plot.ly Java
#### Statistics
-- Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc.
+* Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc.
### Getting started
@@ -53,13 +53,13 @@ Add tablesaw-core and tablesaw-jsplot to your project:
### Documentation and support:
-- Start here: https://jtablesaw.github.io/tablesaw/gettingstarted
-- Then see our documentation page: https://jtablesaw.github.io/tablesaw/ and the [Tablesaw User Guide](https://jtablesaw.github.io/tablesaw/userguide/toc).
+* Start here: https://jtablesaw.github.io/tablesaw/gettingstarted
+* Then see our documentation page: https://jtablesaw.github.io/tablesaw/ and the [Tablesaw User Guide](https://jtablesaw.github.io/tablesaw/userguide/toc).
And *always* feel free to ask questions or make suggestions here on the [issues tab](https://github.com/jtablesaw/tablesaw/issues).
### Integrations
-- We recommend trying Tablesaw inside [Jupyter notebooks](http://arogozhnikov.github.io/2016/09/10/jupyter-features.html), which lets you experiment with Tablesaw in a more interactive manner. Get started by [installing BeakerX](http://beakerx.com/documentation) and trying [the sample Tablesaw notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb)
-- You may utilize Tablesaw with many machine learning libraries. To see an example of using Tablesaw with [Smile](https://haifengl.github.io/smile/) check out [the sample Tablesaw Jupyter notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb)
-- You may use [quandl4j-tablesaw](http://quandl4j.org) if you'd like to load financial and economic data from [Quandl](https://www.quandl.com) into Tablesaw. This is demonstrated in [the sample Tablesaw notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb) as well
+* We recommend trying Tablesaw inside [Jupyter notebooks](http://arogozhnikov.github.io/2016/09/10/jupyter-features.html), which lets you experiment with Tablesaw in a more interactive manner. Get started by [installing BeakerX](http://beakerx.com/documentation) and trying [the sample Tablesaw notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb)
+* You may utilize Tablesaw with many machine learning libraries. To see an example of using Tablesaw with [Smile](https://haifengl.github.io/smile/) check out [the sample Tablesaw Jupyter notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb)
+* You may use [quandl4j-tablesaw](http://quandl4j.org) if you'd like to load financial and economic data from [Quandl](https://www.quandl.com) into Tablesaw. This is demonstrated in [the sample Tablesaw notebook](https://github.com/twosigma/beakerx/blob/master/doc/groovy/Tablesaw.ipynb) as well
