Dataframe

DataFrame is a library that implements an API similar to Python's Pandas or R's data.frame().

Installation

The package can be installed as:

  1. Add dataframe to your list of dependencies in mix.exs: 
```elixir
def deps do
  [{:dataframe, "~> 0.1.0"}]
end
```

Usage

Creation

iex(1)>  data = DataFrame.new(DataFrame.Table.build_random(6,4), DataFrame.DateRange.new("2016-09-12", 6), [1,3,4,5])
              1             3             4             5
2016-09-12    0.3216495192  0.3061978162  0.5240627861  0.3014870998
2016-09-13    0.7085624128  0.1027917034  0.0274851281  0.4999253931
2016-09-14    0.5409299230  0.7234486655  0.0902951353  0.9265397862
2016-09-15    0.8144437609  0.7566869039  0.5943981962  0.4555049347
2016-09-16    0.0228473208  0.9033617026  0.6984988237  0.9858222366
2016-09-17    0.6401066584  0.2700256640  0.4256911712  0.1085587668

Exploring

DataFrame.head(data, 2)
              1             3             4             5
2016-09-12    0.3216495192  0.3061978162  0.5240627861  0.3014870998
2016-09-13    0.7085624128  0.1027917034  0.0274851281  0.4999253931
DataFrame.tail(data, 1)
              1             3             4             5
2016-09-17    0.6401066584  0.2700256640  0.4256911712  0.1085587668

Transposing

DataFrame.transpose(data)
              2016-09-12    2016-09-13    2016-09-14    2016-09-15    2016-09-16    2016-09-17
1             0.3216495192  0.7085624128  0.5409299230  0.8144437609  0.0228473208  0.6401066584
3             0.3061978162  0.1027917034  0.7234486655  0.7566869039  0.9033617026  0.2700256640
4             0.5240627861  0.0274851281  0.0902951353  0.5943981962  0.6984988237  0.4256911712
5             0.3014870998  0.4999253931  0.9265397862  0.4555049347  0.9858222366  0.1085587668

Sorting

Sorting index (defaults bigger to smaller)

DataFrame.sort_index(data)
              1             3             4             5
2016-09-17    0.6401066584  0.2700256640  0.4256911712  0.1085587668
2016-09-16    0.0228473208  0.9033617026  0.6984988237  0.9858222366
2016-09-15    0.8144437609  0.7566869039  0.5943981962  0.4555049347
2016-09-14    0.5409299230  0.7234486655  0.0902951353  0.9265397862
2016-09-13    0.7085624128  0.1027917034  0.0274851281  0.4999253931
2016-09-12    0.3216495192  0.3061978162  0.5240627861  0.3014870998

Sorting by a column (false to sort smaller to bigger)

DataFrame.sort_values(data, 4, false)
              1             3             4             5
2016-09-13    0.7085624128  0.1027917034  0.0274851281  0.4999253931
2016-09-14    0.5409299230  0.7234486655  0.0902951353  0.9265397862
2016-09-17    0.6401066584  0.2700256640  0.4256911712  0.1085587668
2016-09-12    0.3216495192  0.3061978162  0.5240627861  0.3014870998
2016-09-15    0.8144437609  0.7566869039  0.5943981962  0.4555049347
2016-09-16    0.0228473208  0.9033617026  0.6984988237  0.9858222366

Selecting

By name:

DataFrame.loc(data, DataFrame.DateRange.new("2016-09-15", 2), [3,4])
              3             4
2016-09-15    0.5417848216  0.5546980818
2016-09-16    0.6621771048  0.5763923325
DataFrame.at(data, "2016-09-15", 4)
0.5546980818725673

By position:

DataFrame.iloc(data, 4..6, 2..4)
              4             5
2016-09-16    0.6984988237  0.9858222366
2016-09-17    0.4256911712  0.1085587668
DataFrame.iat(data, 0, 0)
0.31553155828919915

The library is in very early stages of development. No effort has been made to optimize its performance. Expect it to be slow.

Development

Run tests

mix test

TODO