pandas 每月滚动作业 [英] Pandas monthly rolling operation

问题描述

我最终在写出这个问题的时候就弄清楚了，所以无论如何我都会发表并回答我自己的问题，以防其他人需要一点帮助.

I ended up figuring it out while writing out this question so I'll just post anyway and answer my own question in case someone else needs a little help.

假设我们有一个DataFrame，df，其中包含此数据.

Suppose we have a DataFrame, df, containing this data.

import pandas as pd
from io import StringIO

data = StringIO(
"""\
date          spendings  category
2014-03-25    10         A
2014-04-05    20         A
2014-04-15    10         A
2014-04-25    10         B
2014-05-05    10         B
2014-05-15    10         A
2014-05-25    10         A
"""
)

df = pd.read_csv(data,sep="\s+",parse_dates=True,index_col="date")

目标

对于每一行，将spendings加到一个月内的每一行，最好使用DataFrame.rolling，因为这是一种非常干净的语法.

Goal

For each row, sum the spendings over every row that is within one month of it, ideally using DataFrame.rolling as it's a very clean syntax.

df = df.rolling("M").sum()

但这会引发异常

ValueError: <MonthEnd> is a non-fixed frequency

版本:pandas==0.19.2

推荐答案

使用"D"偏移量而不是"M"，并专门使用"30D" 30天或大约一个月.

Use the "D" offset rather than "M" and specifically use "30D" for 30 days or approximately one month.

df = df.rolling("30D").sum()

起初，我凭直觉跳到使用"M"，因为我认为它可以使用一个月，但现在很清楚为什么不起作用.

Initially, I intuitively jumped to using "M" as I figured it stands for one month, but now it's clear why that doesn't work.

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