### An annoying thing with Python slices

You of course know that Python slices are awesome:

```a = 'ABCDEFG'
a[:3] -> 'ABC'
a[2:5] -> 'CDE'
```

And more interestingly:

```a[-3:] -> 'EFG'
```

and

```a[6:4:-1] -> 'GF'
```

But you can see that the reverse slicing is starting to stretch the fence-post we are familiar with. Python uses zero based, inclusive-exclusive indexing. This corresponds to a C syntax of `(for i = n; i < m; i++)`. When you reverse it the slice goes `(for i = m - 1; i > n - 1; i--)`.

As you can imagine this starts to get ugly and at one point it gets to be wrong:

Say, as is often the case, you are not taking static, pre-determined slices but rather slices determined at runtime. Say you are taking slices between `n` and `m` or `[n, m)`.

The forward slice is `a[n:m]`
The backward slice is `a[m-1:n-1:-1]` right? Because of the fence posts?

Well yes, except what happens when `n = 0`? The forward slice is fine but the reverse slice resolves to `a[m-1:-1:-1]`

This is where Python becomes a little too clever. As you will recall from our earlier examples, negative indices indicate offsets from the end of the object. So, the last slice returns empty.

The correct slice is `a[m-1:None:-1]` or `a[m-1::-1]` and the logic for this is cumbersome:

`a[m-1:n-1 if n > 0 else None:-1]`

The simpler way is to do `a[n:m][::-1]`.

### Flowing text in inkscape (Poster making)

You can flow text into arbitrary shapes in inkscape. (From a hint here).

You simply create a text box, type your text into it, create a frame with some drawing tool, select both the text box and the frame (click and shift) and then go to text->flow into frame.

UPDATE:

Trying to enter sentence so that text forms the number three...any ideas?
The solution:
Type '3' using the text toolConvert to path using object->pathSize as necessaryRemove fillUngroupType in actual text in new text boxSelect the text and the '3' pathFlow the text

### Pandas panel = collection of tables/data frames aligned by index and column

Pandas panel provides a nice way to collect related data frames together while maintaining correspondence between the index and column values:

import pandas as pd, pylab #Full dimensions of a slice of our panel index = ['1','2','3','4'] #major_index columns = ['a','b','c'] #minor_index df = pd.DataFrame(pylab.randn(4,3),columns=columns,index=index) #A full slice of the panel df2 = pd.DataFrame(pylab.randn(3,2),columns=['a','c'],index=['1','3','4']) #A partial slice df3 = pd.DataFrame(pylab.randn(2,2),columns=['a','b'],index=['2','4']) #Another partial slice df4 = pd.DataFrame(pylab.randn(2,2),columns=['d','e'],index=['5','6']) #Partial slice with a new column and index pn = pd.Panel({'A': df}) pn['B'] = df2 pn['C'] = df3 pn['D'] = df4 for key in pn.items: print pn[key] -> output …

### Drawing circles using matplotlib

Use the pylab.Circle command

import pylab #Imports matplotlib and a host of other useful modules cir1 = pylab.Circle((0,0), radius=0.75, fc='y') #Creates a patch that looks like a circle (fc= face color) cir2 = pylab.Circle((.5,.5), radius=0.25, alpha =.2, fc='b') #Repeat (alpha=.2 means make it very translucent) ax = pylab.axes(aspect=1) #Creates empty axes (aspect=1 means scale things so that circles look like circles) ax.add_patch(cir1) #Grab the current axes, add the patch to it ax.add_patch(cir2) #Repeat pylab.show()