如何为列"start_date"中的每一行创建pandas.date_range()?和"end_date"列? [英] How to create pandas.date_range() for each row from column "start_date" and column "end_date"?

问题描述

我有一个df，例如:

id | start_date | end_date  | price
1  | 2020-10-01 | 2020-10-3 | 1
1  | 2020-10-03 | 2020-10-4 | 1
2  | 2020-10-04 | 2020-10-6 | 2
3  | 2020-10-05 | 2020-10-5 | 3

列开始日期"；和"end_date"是datetime64 [ns].

Columns "start_date" and "end_date" are datetime64[ns].

我想创建一个日期"日期范围内的列.

I want to create a "date" column from the date range.

最简单的方法是创建一个pandas.date_range(开始日期，结束日期，freq ="D")，然后使用.explode().

Easiest way is creating a pandas.date_range(start_date, end_date, freq="D"), then using .explode().

最终结果应如下:

id | start_date | end_date  | price | date
1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-01
1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-02
1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-03
1  | 2020-10-03 | 2020-10-4 | 1     | 2020-10-03
1  | 2020-10-03 | 2020-10-4 | 1     | 2020-10-04
2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-04
2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-05
2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-06
3  | 2020-10-05 | 2020-10-5 | 3     | 2020-10-05

到目前为止已尝试:

df["daterange"] = pd.date_range(df["start_date"], df["end_date"])

TypeError:无法转换输入[0 2020-10-012020年10月1日

TypeError: Cannot convert input [0 2020-10-01 1 2020-10-01

df.itertuples()中行的

for row in df.itertuples():
    df["daterange"] = pd.date_range(start=row.start_date, end=row.end_date)

ValueError:值(3)的长度与索引(9)的长度不匹配

ValueError: Length of values (3) does not match length of index (9)

Lambda，应用，融合等对于我的数据框大小来说太慢了，无法使用！

/编辑

到目前为止我发现的快速复制方法:

Fastet method I found so far:

https://github.com/Garve/scikit-bonus
skbonus.pandas.preprocessing.DateTimeExploder(
        "date",
        start_column="start_date",
        end_column="end_date",
        frequency="d",
        drop=False,
    )

推荐答案

到目前为止我发现的快速方法:

Fasted method I've found so far:

https://github.com/Garve/scikit-bonus
from skbonus.pandas.preprocessing import DateTimeExploder
df = DateTimeExploder(
        "date",
        start_column="start_date",
        end_column="end_date",
        frequency="d",
        drop=False,
    )

这篇关于如何为列"start_date"中的每一行创建pandas.date_range()?和"end_date"列?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！