dax smi cac ftse figure closing stock indices for various european stock markets consider the kasandr data set from the uci machine learning repositorywhich can be downloaded from tar bz this archive file has size of mbso it may take while to download uncompressing the file ( via -zipyields directory de containing two large csv filestest_de csv and train_de csvwith sizes mb and gbrespectively such large data files can still be processed efficiently in pandasprovided there is enough memory the files contain records of user information from kelkoo web logs in germany as well as meta-data on usersoffersand merchants the data sets have attributes and and rowsrespectively the data sets are anonymized via hex strings (aload train_de csv into pandas dataframe object deusing read_csv('train_de csv'delimiter '\ 'if not enough memory is availableload test_de csv instead note that entries are separated here by tabsnot commas time how long it takes for the file to loadusing the time package (it took seconds for train_de csv to load on one of our computers (bhow many unique users and merchants are in this data set visualizing data involving more than two features requires careful designwhich is often more of an art than science (ago to vincent arel-bundocks' website (url given in section and read the orange data set into pandas dataframe object called orange remove its first (unnamedcolumn (bthe data set contains the circumferences of orange trees at various stages in their development find the names of the features (cin pythonimport seaborn and visualize the growth curves (circumference against ageof the treesusing the regplot and facetgrid methods