do not assume that np.array does the right thing

[sdvillal]

Continuation of #217. The fix there only works for transposed arrays, but it still fails to fix errors with, for example, pandas dataframes:

import pandas as pd
import bcolz
df = pd.DataFrame(data={
    'a': np.arange(3),
    'b': np.arange(3)[::-1]
})
print(df)

   a  b
0  0  2
1  1  1
2  2  0

print(bcolz.carray(df))

[[0 1]
 [2 2]
 [1 0]]

This is the same example we had in #217, run with latest master (e260ca7) installed on latest anaconda. I'm working in a fix for this that will do the right thing (the first commit here is a step, but breaks other conversions).

[sdvillal]

This should now be ready to merge.

[FrancescAlted]

Well done!

[esc]

Yeah, looks pretty perfect.

[esc]

@sdvillal do you have more stuff lined up? Just asking because I'd get on with the 0.10.0 release otherwise.

[sdvillal]

@esc No, that was all for the moment.

[sdvillal]

Actually I just thought, for continuous integration to run all tests, we should install pandas in travis/appveyor (I guess using something like miniconda instead of pip to be nice to these services and speed-up builds).

[FrancescAlted]

👍