pandas数值计算与排序方法
以下代码是基于python3.5.0编写的
importpandas
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)"])
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