We use Boolean indexing to filter or select parts of the data. The operators are as follows:
Operators |
Symbol |
OR |
| |
AND |
& |
NOT |
~ |
These operators must be grouped using parentheses when used together. Using the earlier DataFrame from the previous section, here we display the trading dates for which NASDAQ closed above 4,300:
In [311]: sharesIndexDataDF.ix[(sharesIndexDataDF['PriceType']=='close') & \ (sharesIndexDataDF['Nasdaq']>4300) ]
Out[311]: PriceType Nasdaq S&P 500 Russell 2000 TradingDate 2014/02/27 close 4318.93 1854.29 1187.94 2014/02/28 close 4308.12 1859.45 1183.03 2 rows × 4 columns
You can also create Boolean conditions in which you use arrays to filter out parts of the data, as shown in the following...