(python-analysis-draw)=
# Walkthrough: Simple analysis using the Draw command 
**(10 minutes)**

:::{admonition} Moving to the next level
:class: note

It may be that all the analysis tasks that your supervisor will ask you
to do can be performed using the `Draw` command, the `Treeviewer`, the
`FitPanel`, and other simple techniques discussed in the early chapters of
the [ROOT Users
Guide](https://root.cern/root/htmldoc/guides/users-guide/ROOTUsersGuide.html).

However, it's more likely that these simple commands will only be useful
when you get started; for example, you can draw a histogram of just one
variable to see what the histogram limits might be. Let's start with the
same tasks you did with Treeviewer.[^f89]$^,$[^f90]
:::

If you didn't copy the example n-tuple file in {ref}`the basics`, do so now:

    > cp ~seligman/root-class/experiment.root $PWD

Open the sample ROOT TTree in the notebook with the following:

:::{code-block} python
from ROOT import TFile, gROOT
myFile = TFile("experiment.root")
tree1 = gROOT.FindObject("tree1")
:::

:::{admonition} Let's understand what this does
:class: note

The first command imports specific ROOT classes into Python (see the
previous page).

That third command means: Look through everything we've read in (the
"everything" is `gROOT`) and find the object whose name is `tree1`.

If you've done {ref}`cpath`, note that in Python we have to read in the
n-tuple explicitly.
:::

In a notebook, you can't use {ref}`the Scan method <variables-root>` to look at the contents of
the tree, but you
can display the names of the variables and the size of the `TTree`:

    tree1.Print()

You can see that the variables stored in the TTree are **`event`**,
**`ebeam`**, **`px`**, **`py`**, **`pz`**, **`zv`**, and **`chi2`**.

Create a histogram of one of the variables. For example:

:::{code-block} python
    from ROOT import TCanvas
    my_canvas = TCanvas()
    tree1.Draw("ebeam")
    my_canvas.Draw()
:::

While we have to explicitly Draw a canvas, we can re-use a
previously-defined canvas (the same way command-line ROOT keeps re-using
c1).

Using the Draw commands, make histograms of the other variables.

[^f89]: I duplicate some of the descriptions from the Treeviewer
    discussion, in case you decided to rush into programming and skip
    the simple tools.

[^f90]: If you're experienced with Python, you may ask why I'm not
    including [NumPy](https://numpy.org/),
    [SciPy](https://scipy.org/), and
    [Matplotlib](https://matplotlib.org/) in this tutorial. I want to
    focus on the ROOT toolkit, even though many tasks (especially in
    the {ref}`advanced exercises` and {ref}`expert exercises`) can be
    more easily accomplished using those additional packages. I
    wrestled with this issue for a while, before deciding that there
    are hundreds of web pages on these standard Python tools but few sites on ROOT. But
    I may change my mind next year!