pandas数值计算与排序

以下代码是基于python3.5.0编写的

import pandas food_info = pandas.read_csv("food_info.csv") # ---------------------特定列加减乘除------------------------- print(food_info["Iron_(mg)"]) div_1000 = food_info["Iron_(mg)"] / 1000 add_100 = food_info["Iron_(mg)"] + 100 sub_100 = food_info["Iron_(mg)"] - 100 mult_2 = food_info["Iron_(mg)"]*2 # ---------------------某两列相乘--------------------------- water_energy = food_info["Water_(g)"] * food_info["Energ_Kcal"] # ----------------------把某一列除1000，再添加新列---------------------------- iron_grams = food_info["Iron_(mg)"] / 1000 food_info["Iron_(g)"] = iron_grams #-------------------Score=2×(Protein_(g))−0.75×(Lipid_Tot_(g))-------------- weighted_protein = food_info["Protein_(g)"] * 2 weighted_fat = -0.75 * food_info["Lipid_Tot_(g)"] initial_rating = weighted_protein + weighted_fat #----------------------------数据归一化----------------------------------- max_calories = food_info["Energ_Kcal"].max() #找列最大值 normalized_calories = food_info["Energ_Kcal"] / max_calories normalized_protein = food_info["Protein_(g)"] / food_info["Protein_(g)"].max() normalized_fat = food_info["Lipid_Tot_(g)"] / food_info["Lipid_Tot_(g)"].max() food_info["Normalized_Protein"] = normalized_protein food_info["Normalized_Fat"] = normalized_fat # -------------------------------排序---------------------------------- food_info.sort_values("Sodium_(mg)", inplace=True) #升序，inplace=True表示不从建DataFrame print(food_info["Sodium_(mg)"]) food_info.sort_values("Sodium_(mg)", inplace=True, ascending=False) #降序，ascending=False表示降序 print(food_info["Sodium_(mg)"])