figure - sample csv file we can convert this file into dataframe with the help of the following code leveraging pandas in [ ]import pandas as pd in [ ]city_data pd read_csv(filepath_or_buffer='simplemaps-worldcities-basic csv'in [ ]city_data head( = out[ ]city city_ascii lat lng pop country qal eh-ye now qal eh-ye afghanistan chaghcharan chaghcharan afghanistan lashkar gah lashkar gah afghanistan zaranj zaranj afghanistan tarin kowt tarin kowt afghanistan zareh sharan zareh sharan afghanistan asadabad asadabad afghanistan taloqan taloqan afghanistan mahmud- eraqi mahmud- eraqi afghanistan mehtar lam mehtar lam afghanistan iso iso province af afg badghis af afg ghor af afg hilmand af afg nimroz af afg uruzgan af afg paktika af afg kunar af afg takhar af afg kapisa af afg laghman as the file we supplied had header includedthose values were used as the name of the columns in the resultant dataframe this is very basic yet core usage of the function pandas read_csv the function comes with multitude of parameters that can be used to modify its behavior as required we will not cover