to_json() Flat Output

[r-barnes]

The to_json() I/O command current provides the following output:

split   dict like {index -> [index], columns -> [columns], data -> [values]}
records list like [{column -> value}, ... , {column -> value}]
index   dict like {index -> {column -> value}}
columns dict like {column -> {index -> value}}
values  just the values array

It would be handy if the output could also be provided in the format:

mdarray    [ [index1,value1a,value1b,...] , [index2,value2a,value2b,...], ... ]

This format is, for instance, used by the DyGraphs JS library for plotting data.

The following command provides the output I am looking for:

np.column_stack((df.index,df.as_matrix())).tolist()

(where df is a DataFrame)

[jreback]

Not nearly as efficient (as json is implemented in c), but you can do this (and its a python structure not JSON....but)

In [14]: df = DataFrame(np.arange(10).reshape(5,-1),columns=list('AB'))

In [15]: df
Out[15]: 
   A  B
0  0  1
1  2  3
2  4  5
3  6  7
4  8  9

In [16]: list(df.itertuples())
Out[16]: [(0, 0, 1), (1, 2, 3), (2, 4, 5), (3, 6, 7), (4, 8, 9)]

[jreback]

cc @Komnomnomnom

related is #5729

[im-n1]

Hi there,

this feature is really needed. These flat arrays [val, val, val, ...] are used by Javascript libraries.

All the solutions above don't work so my way was df.to_csv() where I get the flat rows and then I'm reading this csv. It's nasty but I had no choice.

[jreback]

well @grafa pull-requests are welcome.

[im-n1]

I would like to help but I'm not such experienced to deliver solution that matches Pandas code quality.

[jreback]

closing as dupe of #5729