Question

我想以10天为基准，以10天为一组（JAN / 01到JAN / 10）对AAPL.High的平均值进行平均。

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

代码的想法大约是：

df1['demand'] = df1.groupby(['supplier_name', 'date'])['difference'].transform('mean').fillna(0)

Answer 1

将索引定义为日期的简单情况，然后只需使用resample()

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
df.index = pd.to_datetime(df["Date"])
df.resample("10d").agg({"AAPL.High":np.mean})

输出

            AAPL.High
Date    
2015-02-17  130.657501
2015-02-27  129.675001
2015-03-09  126.661251
2015-03-19  127.134283
2015-03-29  126.533333
... ...
2017-01-07  119.532001
2017-01-17  120.841248
2017-01-27  125.740000
2017-02-06  133.172500
2017-02-16  135.899994

熊猫：X天组的平均值

1 个答案: