Merge pull request #418 from cathydeng/master

remove $ for more beginner friendly docs

docs/tutorial/1_getting_started.rst

@@ -16,7 +16,7 @@ Installing csvkit
 
 Installing csvkit is easy::
 
-    $ sudo pip install csvkit
+    sudo pip install csvkit
 
 If you have problems installing, check out the common issues described in the :doc:`../install` section of the full documentation.
 
@@ -29,23 +29,23 @@ Getting the data
 
 Let's start by creating a clean workspace::
 
-    $ mkdir csvkit_tutorial 
-    $ cd csvkit_tutorial
+    mkdir csvkit_tutorial 
+    cd csvkit_tutorial
 
 Now let's fetch the data::
 
-    $ curl -L -O https://github.com/onyxfish/csvkit/raw/master/examples/realdata/ne_1033_data.xlsx
+    curl -L -O https://github.com/onyxfish/csvkit/raw/master/examples/realdata/ne_1033_data.xlsx
 
 in2csv: the Excel killer
 ========================
 
 For purposes of this tutorial, I've converted this data to Excel format. (NPR published it in CSV format.) If you have Excel you can open the file and take a look at it, but really, who wants to wait for Excel to load? Instead, let's make it a CSV::
 
-    $ in2csv ne_1033_data.xlsx
+    in2csv ne_1033_data.xlsx
 
 You should see a CSV version of the data dumped into your terminal. All csvkit utilities write to the terminal output ("standard out") by default. This isn't very useful, so let's write it to a file instead::
 
-    $ in2csv ne_1033_data.xlsx > data.csv
+    in2csv ne_1033_data.xlsx > data.csv
 
 ``data.csv`` will now contain a CSV version of our original file. If you aren't familiar with the ``>`` syntax, it literally means "redirect standard out to a file", but it may be more convenient to think of it as "save".
 
@@ -56,7 +56,7 @@ csvlook: data periscope
 
 Now that we have some data, we probably want to get some idea of what's in it. We could open it in Excel or Google Docs, but wouldn't it be nice if we could just take a look in the command line? Enter csvlook::
 
-    $ csvlook data.csv
+    csvlook data.csv
 
 Now at first the output of :doc:`/scripts/csvlook` isn't going to appear very promising. You'll see a mess of data, pipe character and dashes. That's because this dataset has many columns and they won't all fit in the terminal at once. To fix this we need to learn how to reduce our dataset before we look at it.
 
@@ -65,7 +65,7 @@ csvcut: data scalpel
 
 :doc:`/scripts/csvcut` is the original csvkit tool, the one that started the whole thing. With it, we can slice, delete and reorder the columns in our CSV. First, let's just see what columns are in our data::
 
-    $ csvcut -n data.csv
+    csvcut -n data.csv
       1: state
       2: county
       3: fips
@@ -83,28 +83,28 @@ csvcut: data scalpel
 
 As you'll can see, our dataset has fourteen columns. Let's take a look at just columns ``2``, ``5`` and ``6``::
 
-    $ csvcut -c 2,5,6 data.csv
+    csvcut -c 2,5,6 data.csv
 
 Now we've reduced our output CSV to only three columns.
 
 We can also refer to columns by their names to make our lives easier::
 
-    $ csvcut -c county,item_name,quantity data.csv
+    csvcut -c county,item_name,quantity data.csv
 
 Putting it together with pipes
 ==============================
 
 Now that we understand ``in2csv``, ``csvlook`` and ``csvcut`` we can demonstrate the power of csvkit's when combined with the standard command line "pipe". Try this command::
 
-    $ csvcut -c county,item_name,quantity data.csv | csvlook | head
+    csvcut -c county,item_name,quantity data.csv | csvlook | head
 
 All csvkit utilities accept an input file as "standard in", in addition to as a filename. This means that we can make the output of one csvkit utility become the input of the next. In this case, the output of ``csvcut`` becomes the input to ``csvlook``. This also means we can use this output with standard unix commands such as ``head``, which prints only the first ten lines of it's input. Here, the output of ``csvlook`` becomes the input of ``head``.
 
 Pipeability is a core feature of csvkit. Of course, you can always write your output to a file using ``>``, but many times it makes more sense to use pipes for speed and brevity.
 
 Of course, we can also pipe ``in2csv``, combining all our previous operations into one::
 
-    $ in2csv ne_1033_data.xlsx | csvcut -c county,item_name,quantity | csvlook | head
+    in2csv ne_1033_data.xlsx | csvcut -c county,item_name,quantity | csvlook | head
 
 Summing up
 ==========