Getting Data¶
The quandl
(or quandlget
) function takes one positional argument
(the Quandl code for the database you wish to download) and currently
supports six keyword arguments:
order
, which is the order in which the returned Dataset is sorted (default isdes
);rows
, which is the number of rows that the returned Dataset will have (default is100
);frequency
, which is the frequency desired for the Dataset (default isdaily
);transformation
, which is the calculation Quandl do to to Dataset prior to download (default isnone
);from
, which is the starting date for the Dataset (default is""
);to
, which is the ending date for the Dataset (default is""
);format
, which is the type returned by the function (default is"TimeArray"
, but you can use"DataFrame"
also).api_key
, which can be used to set your own API key from quandl.com
julia> quandl("GOOG/NASDAQ_QQQ")
100x5 TimeArray{Float64,2} 2013-12-31 to 2014-05-23
Open High Low Close Volume
2013-12-31 | 87.54 87.96 87.52 87.96 2.4896065e7
2014-01-02 | 87.55 87.58 87.02 87.27 2.9190009e7
2014-01-03 | 87.27 87.35 86.62 86.64 3.5727317e7
2014-01-06 | 86.65 86.76 86.0 86.32 3.2092437e7
⋮
2014-05-20 | 88.28 88.6 87.64 88.0 3.3715953e7
2014-05-21 | 88.16 88.89 88.11 88.84 3.6837678e7
2014-05-22 | 88.94 89.48 88.8 89.23 3.0617089e7
2014-05-23 | 89.33 89.9 89.12 89.88 2.2691254e7
You can also dowload your data into a DataFrame.
julia> quandl("GOOG/NASDAQ_QQQ", format="DataFrame")
100x6 DataFrame
|-------|------------|-------|-------|-------|-------|-----------|
| Row | Date | Open | High | Low | Close | Volume |
| 1 | 2014-05-30 | 91.33 | 91.45 | 90.83 | 91.31 | 2.99169e7 |
| 2 | 2014-05-29 | 91.05 | 91.31 | 90.86 | 91.3 | 3.30361e7 |
| 3 | 2014-05-28 | 90.97 | 91.1 | 90.64 | 90.72 | 3.04781e7 |
| 4 | 2014-05-27 | 90.28 | 91.02 | 90.2 | 91.0 | 2.97252e7 |
| 5 | 2014-05-23 | 89.33 | 89.9 | 89.12 | 89.88 | 2.26913e7 |
| 6 | 2014-05-22 | 88.94 | 89.48 | 88.8 | 89.23 | 3.06171e7 |
| 7 | 2014-05-21 | 88.16 | 88.89 | 88.11 | 88.84 | 3.68377e7 |
| 8 | 2014-05-20 | 88.28 | 88.6 | 87.64 | 88.0 | 3.3716e7 |
| 9 | 2014-05-19 | 87.47 | 88.46 | 87.3 | 88.32 | 3.2017e7 |
⋮
| 91 | 2014-01-21 | 88.43 | 88.59 | 87.81 | 88.55 | 2.64323e7 |
| 92 | 2014-01-17 | 88.12 | 88.37 | 87.67 | 87.88 | 3.69082e7 |
| 93 | 2014-01-16 | 88.28 | 88.51 | 88.16 | 88.38 | 3.42602e7 |
| 94 | 2014-01-15 | 88.0 | 88.54 | 87.94 | 88.37 | 3.98597e7 |
| 95 | 2014-01-14 | 86.3 | 87.72 | 86.3 | 87.65 | 3.71941e7 |
| 96 | 2014-01-13 | 87.18 | 87.48 | 85.68 | 86.01 | 4.88552e7 |
| 97 | 2014-01-10 | 87.24 | 87.4 | 86.58 | 87.3 | 3.80121e7 |
| 98 | 2014-01-09 | 87.62 | 87.64 | 86.72 | 87.02 | 2.36957e7 |
| 99 | 2014-01-08 | 87.11 | 87.55 | 86.94 | 87.31 | 2.721e7 |
| 100 | 2014-01-07 | 86.7 | 87.25 | 86.56 | 87.12 | 2.59132e7 |