以下代码是基于python3.5.0编写的
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import pandasfood_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)"] / 1000add_100 = food_info["Iron_(mg)"] + 100sub_100 = food_info["Iron_(mg)"] - 100mult_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)"] / 1000food_info["Iron_(g)"] = iron_grams#-------------------Score=2×(Protein_(g))−0.75×(Lipid_Tot_(g))--------------weighted_protein = food_info["Protein_(g)"] * 2weighted_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_caloriesnormalized_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_proteinfood_info["Normalized_Fat"] = normalized_fat# -------------------------------排序----------------------------------food_info.sort_values("Sodium_(mg)", inplace=True) #升序，inplace=True表示不从建DataFrameprint(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)"]) |
以上这篇pandas数值计算与排序方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/qq_32005671/article/details/61629873
