pandas核心数据结构series详解

import pandas as pdfrom pandas import Seriesimport numpy as npfandango = pd.read_csv('fandango_score_comparison.csv')series_film = fandango['FILM']# print(series_film[0:5])series_rt = fandango['RottenTomatoes']# print(series_rt[0:5])film_names = series_film.values# print(type(film_names))# print(film_names)rt_scores = series_rt.values# print(rt_scores)series_custom = Series(rt_scores , index=film_names)# print(series_custom[['Minions (2015)', 'Leviathan (2014)']])fiveten = series_custom[5:10]# print(fiveten)# ------------------------按索引进行排序----------------------original_index = series_custom.index.tolist()print(original_index)sorted_index = sorted(original_index)sorted_by_index = series_custom.reindex(sorted_index)print(sorted_by_index)# ------------------------按索引进行排序----------------------sc2 = series_custom.sort_index()print(sc2[0:10])# ------------------------按值进行排序----------------------sc3 = series_custom.sort_values()print(sc3[0:10])# ------------------------常用的数值计算---------------------------np.add(series_custom, series_custom)np.sin(series_custom)np.max(series_custom)# --------------------把大于50的值赋给series_greater_than_50----------------------series_greater_than_50 = series_custom[series_custom > 50]# --------------------把大于50且小于75的值赋给both_criteria----------------------criteria_one = series_custom > 50criteria_two = series_custom < 75both_criteria = series_custom[criteria_one & criteria_two]print(both_criteria)rt_critics = Series(fandango['RottenTomatoes'].values, index=fandango['FILM'])rt_users = Series(fandango['RottenTomatoes_User'].values, index=fandango['FILM'])rt_mean = (rt_critics + rt_users)/2