如何按价值索引，按

发布于 2025-01-23 22:56:20 字数 914 浏览 0 评论 0原文

我正在尝试分析与健康个体的糖尿病不同诊断中的高血压率。我要获得的输出是：

0     0.371132
8     0.752674
64    0.629022

我需要的输出是

Diabetes_012    average HBP occurence
0               0.371132
2               0.752674
1               0.629022

输出索引是糖尿病类型，值是糖尿病的平均出现。

这是此处的完整代码

import csv
import pandas as pd
import seaborn as sns
df = pd.read_csv ('diabetes_012_health_indicators_BRFSS2015.csv') 
df2=df.copy
pd.set_option('display.max_columns', None)
df
import matplotlib.pyplot as plt
grouped=df.groupby(['Diabetes_012'])['HighBP'].transform('mean').drop_duplicates()
print(grouped)

是指向数据集的链接： https：/> https：/ /www.kaggle.com/datasets/alexteboul/diabetes-health-indicators-dataset

原文

I am trying analyze the rates of high blood pressure in different diagnosis of diabetes with that of healthy individuals.
The output I am getting is this:

0     0.371132
8     0.752674
64    0.629022

The output I need is this

Diabetes_012    average HBP occurence
0               0.371132
2               0.752674
1               0.629022

Where the output index is the diabetes types and the value is the average occurrence of diabetes.

Here is the full code

import csv
import pandas as pd
import seaborn as sns
df = pd.read_csv ('diabetes_012_health_indicators_BRFSS2015.csv') 
df2=df.copy
pd.set_option('display.max_columns', None)
df
import matplotlib.pyplot as plt
grouped=df.groupby(['Diabetes_012'])['HighBP'].transform('mean').drop_duplicates()
print(grouped)

Here is the link to the dataset: https://www.kaggle.com/datasets/alexteboul/diabetes-health-indicators-dataset

分享到QQ

分享到微博

如果你对这篇内容有疑问，欢迎到本站社区发帖提问参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。

发布评论

需要登录才能够评论，你可以免费注册一个本站的账号。

初熏 2025-01-30 22:56:20

不要使用.transform，只需抓住要执行均值的列（或列）：

In [3]: df.groupby("Diabetes_012")[["HighBP"]].mean()
Out[3]:
                HighBP
Diabetes_012
0.0           0.371132
1.0           0.629022
2.0           0.752674

带有多个列的示例：

In [4]: df.groupby("Diabetes_012")[["HighBP", "BMI"]].mean()
Out[4]:
                HighBP        BMI
Diabetes_012
0.0           0.371132  27.742521
1.0           0.629022  30.724466
2.0           0.752674  31.944011

Don't use .transform, just grab the column (or columns) on which you want to perform the mean:

In [3]: df.groupby("Diabetes_012")[["HighBP"]].mean()
Out[3]:
                HighBP
Diabetes_012
0.0           0.371132
1.0           0.629022
2.0           0.752674

Example with multiple columns:

In [4]: df.groupby("Diabetes_012")[["HighBP", "BMI"]].mean()
Out[4]:
                HighBP        BMI
Diabetes_012
0.0           0.371132  27.742521
1.0           0.629022  30.724466
2.0           0.752674  31.944011

回复收藏 0 原文

~没有更多了~