You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@toree.apache.org by lb...@apache.org on 2016/05/06 18:46:26 UTC
[2/2] incubator-toree git commit: [skip ci] Added dataframe to the
TOC of the sample notebook
[skip ci] Added dataframe to the TOC of the sample notebook
Project: http://git-wip-us.apache.org/repos/asf/incubator-toree/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-toree/commit/4463bf46
Tree: http://git-wip-us.apache.org/repos/asf/incubator-toree/tree/4463bf46
Diff: http://git-wip-us.apache.org/repos/asf/incubator-toree/diff/4463bf46
Branch: refs/heads/master
Commit: 4463bf460fd5bb04e2fe818e9127b4ec79678564
Parents: 5a2b79e
Author: Gino Bustelo <lb...@apache.org>
Authored: Fri May 6 13:42:48 2016 -0500
Committer: Gino Bustelo <lb...@apache.org>
Committed: Fri May 6 13:42:48 2016 -0500
----------------------------------------------------------------------
etc/examples/notebooks/magic-tutorial.ipynb | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-toree/blob/4463bf46/etc/examples/notebooks/magic-tutorial.ipynb
----------------------------------------------------------------------
diff --git a/etc/examples/notebooks/magic-tutorial.ipynb b/etc/examples/notebooks/magic-tutorial.ipynb
index 3d3ca28..e6d6a62 100644
--- a/etc/examples/notebooks/magic-tutorial.ipynb
+++ b/etc/examples/notebooks/magic-tutorial.ipynb
@@ -16,6 +16,7 @@
" 1. [AddJar](#addjar)\n",
" 1. [AddDeps](#adddeps)\n",
"1. [Cell Magics](#cell-magics)\n",
+ " 1. [DataFrame](#dataframe)\n",
" 1. [Html](#html)\n",
" 1. [JavaScript](#javascript)\n",
" 1. [PySpark](#pyspark)\n",
@@ -516,7 +517,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "### %%DataFrame\n",
+ "### %%DataFrame<a name=\"dataframe\"></a><span style=\"float: right; font-size: 0.5em\"><a href=\"#top\">Top</a></span>\n",
"The `%%DataFrame` magic is used to convert a Spark SQL DataFrame into various formats. Currently, `json`, `html`, and `csv` are supported. The magic takes an expression, which evauluates to a dataframe, to perform the conversion. So, we first need to create a DataFrame object for reference."
]
},