pandas数值计算与排序方法_Python

pandas数值计算与排序方法

2021-01-31 00:08数据阿伯 Python

下面小编就为大家分享一篇pandas数值计算与排序方法，具有很好的参考价值，希望对大家有所帮助。一起跟随小编过来看看吧

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)"])