gender object age int dtype object gender category age int dtype object + extracting information extracting statistical information from dataframe object is facilitated by large collection of methods (functionsin pandas table gives selection of data inspection methods see for their practical use the code below provides several examples of useful methods the apply method allows one to apply general functions to columns or rows of dataframe these operations do not change the data the loc method allows for accessing elements (or rangesin data frame and acts similar to the slicing operation for lists and arrayswith the difference that the "stopvalue is includedas illustrated in the code below import numpy as np import pandas as pd ages [ , , , , , , , np random seed ( df pd dataframe (np random randn ( , index list('abc ')columns list('abcd ')print (dfdf df loc[" ":" "," ":" "create partial data frame print (df meana df[' 'mean (mean of 'acolumn print ('mean of column {format meana )expa df[' 'apply (np expexp of all elements in 'acolumn print (expaa - - - - - - - - - - - mean of column - nameadtype float the groupby method of dataframe object is useful for summarizing and displaying the data in manipulated ways it groups data according to one or more specified columnssuch that methods such as count and mean can be applied to the grouped data