Data, Data Everywhere

“In God we trust, all others must bring data.” - W. Edwards Deming

How data is stored

Data streams itself right from when the gates of a stock exchange open to when it closes. Such data contains vital information that is archived each day. Some of the many types of information recieved after trading hours are - opening price, closing price, volumne of shares, highest price, lowest price, etc. for each enterprise.

bulbea helps you access such information (both - archived and the latest). Simply create a Share with a known source and ticker as follows:

>>> import bulbea as bb
>>> share = bb.Share(source = 'YAHOO', ticker = 'GOOGL')
                  Open        High         Low       Close      Volume  Adjusted Close
2004-08-19   99.999999  104.059999   95.959998  100.339998  44659000.0       50.220219
2004-08-20  101.010005  109.079998  100.500002  108.310002  22834300.0       54.209210
2004-08-23  110.750003  113.479998  109.049999  109.399998  18256100.0       54.754754

Data is accessed through the Quandl API stored remotely at sources in the form of CSV (Comma-Seperated Values) files. Information retrieved from such a CSV file is then wrapped around a pandas.DataFrame object.

Comma, Seperated, Value?

CSV files store tabular data in simple plain text (well, fits the need). Each row containing values associated to each attribute of a table are stored in a single line, where each value is seperated by a delimiter, you guessed it right, a comma. For instance, a data set containing the weight (in kilograms) and height (in inches) of members of my family would look something like the following:


Almost always, the top-most line (also called as the header) should denote the attribute names seperated by the delimiter.

You can save a share object in a CSV format as follows:


By default, the save method saves a share as a CSV file in the working directory with a file name of the format - <source>_<ticker>_<start>_<end>.csv. You could also name the file anything you like as follows:

>>> = 'mycsvfile.csv')