DataFrame.plot() raised an error when both color and style keywords were passed and there was no color symbol in the style strings (GH9671) • Not showing a DeprecationWarning on combining list-likes with an Options('aapl','yahoo') In [19]: aapl.get_call_data().iloc[0:5,0:1] Out[19]: Last Strike Expiry Type Symbol 60 2015-10-16 call AAPL151016C00060000 51.00 65 2015-10-16 call AAPL151016C00065000 47.84 70 2015-10-16 get_near_stock_price(expiry=aapl.expiry_dates[0:3]).iloc[0:5,0:1] Out[21]: Last Strike Expiry Type Symbol 111 2015-10-23 call AAPL151023C00111000 2.44 2015-10-30 call AAPL151030C00111000 4.45 112 2015-10-16

Options(’aapl’,’yahoo’) In [19]: aapl.get_call_data().iloc[0:5,0:1] Out[19]: Last Strike Expiry Type Symbol 1.2. v0.15.1 (November 9, 2014) 11 pandas: powerful Python data analysis toolkit, Release 0.15 get_near_stock_price(expiry=aapl.expiry_dates[0:3]).iloc[0:5,0:1] Out[21]: Last Strike Expiry Type Symbol 113 2014-12-20 call AAPL141220C00113000 2.03 2014-12-26 call AAPL141226C00113000 2.53 114 2014-12-12 datetime64[ns](1), float64(1), int64(1), object(1), timedelta64[ns](1) memory usage: 303.5+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used

Options(’aapl’,’yahoo’) In [19]: aapl.get_call_data().iloc[0:5,0:1] Out[19]: Last Strike Expiry Type Symbol 80 2014-11-14 call AAPL141114C00080000 29.05 84 2014-11-14 call AAPL141114C00084000 24.80 85 2014-11-14 get_near_stock_price(expiry=aapl.expiry_dates[0:3]).iloc[0:5,0:1] Out[21]: Last Strike Expiry Type Symbol 109 2014-11-22 call AAPL141122C00109000 1.48 2014-11-28 call AAPL141128C00109000 1.79 110 2014-11-14 datetime64[ns](1), float64(1), int64(1), object(1), timedelta64[ns](1) memory usage: 303.5+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used Quandl • FRED • Fama/French • World Bank • OECD • Eurostat • TSP Fund Data • Nasdaq Trader Symbol Definitions • Stooq Index Data • MOEX Data 5.4.2 quandl/Python Quandl API for Python wraps the

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used Quandl • FRED • Fama/French • World Bank • OECD • Eurostat • TSP Fund Data • Nasdaq Trader Symbol Definitions • Stooq Index Data • MOEX Data 5.4.2 quandl/Python Quandl API for Python wraps the

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used Quandl • FRED • Fama/French • World Bank • OECD • Eurostat • TSP Fund Data • Nasdaq Trader Symbol Definitions • Stooq Index Data • MOEX Data 5.4.2 quandl/Python Quandl API for Python wraps the

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True]display.large_repr : ‘truncate’/’info’ For DataFrames

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used process table contents using Math- Jax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True] display.large_repr [‘truncate’/’info’] For DataFrames

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used process table contents using Math- Jax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True] display.large_repr [‘truncate’/’info’] For DataFrames

will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. io.excel.xls.writer xlwt The default Excel writer engine for ‘xls’ files. io.excel.xlsm.writer datetime64[ns](1), float64(1), int64(1), ˓→object(1), timedelta64[ns](1) memory usage: 289.1+ KB The + symbol indicates that the true memory usage could be higher, because pandas does not count the memory used process table contents using Math- Jax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True] display.large_repr [‘truncate’/’info’] For DataFrames