the help of dtypes property we can categorize each attributes data type it can be understood with the help of following python scriptexample from pandas import read_csv path " :\iris csvdata read_csv(pathprint(data dtypesoutput sepal_length float sepal_width float petal_length float petal_width float dtypeobject from the above outputwe can easily get the datatypes of each attribute statistical summary of data we have discussed python recipe to get the shape number of rows and columnsof data but many times we need to review the summaries out of that shape of data it can be done with the help of describe(function of pandas dataframe that further provide the following statistical properties of each every data attributecount mean standard deviation minimum value maximum value median example from pandas import read_csv from pandas import set_option path " :\pima-indians-diabetes csvnames ['preg''plas''pres''skin''test''mass''pedi''age''class'data read_csv(pathnames=names