non-null values dtypesfloat ( )object( in [ ]frame['tz'][: out[ ] america/new_york america/denver america/new_york america/sao_paulo america/new_york america/new_york europe/warsaw nametz the output shown for the frame is the summary viewshown for large dataframe objects the series object returned by frame['tz'has method value_counts that gives us what we're looking forin [ ]tz_counts frame['tz'value_counts(in [ ]tz_counts[: out[ ]america/new_york america/chicago america/los_angeles america/denver europe/london asia/tokyo pacific/honolulu europe/madrid america/sao_paulo thenwe might want to make plot of this data using plotting librarymatplotlib you can do bit of munging to fill in substitute value for unknown and missing time zone data in the records the fillna function can replace missing (navalues and unknown (empty stringsvalues can be replaced by boolean array indexingin [ ]clean_tz frame['tz'fillna('missing'in [ ]clean_tz[clean_tz ='''unknownin [ ]tz_counts clean_tz value_counts(in [ ]tz_counts[: out[ ]america/new_york unknown america/chicago america/los_angeles america/denver missing introductory examples www it-ebooks info