cand_nm contbr_nm contbr_city contbr_st contbr_zip contbr_employer contbr_occupation contb_receipt_amt contb_receipt_dt receipt_desc memo_cd memo_text form_tp file_num name obamabarack ellmanira tempe az arizona state university professor -dec- nan nan nan sa you can probably think of many ways to start slicing and dicing this data to extract informative statistics about donors and patterns in the campaign contributions 'll spend the next several pages showing you number of different analyses that apply techniques you have learned about so far you can see that there are no political party affiliations in the dataso this would be useful to add you can get list of all the unique political candidates using unique (note that numpy suppresses the quotes around the strings in the output)in [ ]unique_cands fec cand_nm unique(in [ ]unique_cands out[ ]array([bachmannmichelleromneymittobamabarackroemercharles 'buddyiiipawlentytimothyjohnsongary earlpaulronsantorumrickcainhermangingrichnewtmccotterthaddeus ghuntsmanjonperryrick]dtype=objectin [ ]unique_cands[ out[ ]'obamabarackan easy way to indicate party affiliation is using dict: parties {'bachmannmichelle''republican''cainherman''republican''gingrichnewt''republican''huntsmanjon''republican''johnsongary earl''republican''mccotterthaddeus ''republican''obamabarack''democrat''paulron''republican''pawlentytimothy''republican''perryrick''republican'"roemercharles 'buddyiii"'republican' this makes the simplifying assumption that gary johnson is republican even though he later became the libertarian party candidate example federal election commission database www it-ebooks info