out[ ]dtype('float 'this will introduce you to the basics of using numpy arraysand should be sufficient for following along with the rest of the book while it' not necessary to have deep understanding of numpy for many data analytical applicationsbecoming proficient in array-oriented programming and thinking is key step along the way to becoming scientific python guru whenever you see "array""numpy array"or "ndarrayin the textwith few exceptions they all refer to the same thingthe ndarray object creating ndarrays the easiest way to create an array is to use the array function this accepts any sequence-like object (including other arraysand produces new numpy array containing the passed data for examplea list is good candidate for conversionin [ ]data [ in [ ]arr np array(data in [ ]arr out[ ]array( ]nested sequenceslike list of equal-length listswill be converted into multidimensional arrayin [ ]data [[ ][ ]in [ ]arr np array(data in [ ]arr out[ ]array([[ ][ ]]in [ ]arr ndim out[ ] in [ ]arr shape out[ ]( unless explicitly specified (more on this later)np array tries to infer good data type for the array that it creates the data type is stored in special dtype objectfor examplein the above two examples we havein [ ]arr dtype out[ ]dtype('float 'the numpy ndarraya multidimensional array object www it-ebooks info