微信公众号搜"智元新知"关注
微信扫一扫可直接关注哦!

pandas数值计算与排序方法

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)"])

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编程小技巧。

版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 [email protected] 举报,一经查实,本站将立刻删除。

相关推荐