Pandas 可以绘制日期的直方图吗? [英] Can Pandas plot a histogram of dates?

问题描述

我已经将我的系列强制转换为 dtype=datetime64[ns] 的日期时间列(尽管只需要日期分辨率...不知道如何更改).

I've taken my Series and coerced it to a datetime column of dtype=datetime64[ns] (though only need day resolution...not sure how to change).

import pandas as pd
df = pd.read_csv('somefile.csv')
column = df['date']
column = pd.to_datetime(column, coerce=True)

但绘图不起作用:

ipdb> column.plot(kind='hist')
*** TypeError: ufunc add cannot use operands with types dtype('<M8[ns]') and dtype('float64')

我想绘制一个仅按周、月或年显示日期计数的直方图.

I'd like to plot a histogram that just shows the count of dates by week, month, or year.

在 pandas 中肯定有办法做到这一点吗?

Surely there is a way to do this in pandas?

推荐答案

鉴于此 df:

        date
0 2001-08-10
1 2002-08-31
2 2003-08-29
3 2006-06-21
4 2002-03-27
5 2003-07-14
6 2004-06-15
7 2003-08-14
8 2003-07-29

而且，如果还不是这样:

and, if it's not already the case:

df["date"] = df["date"].astype("datetime64")

按月显示日期计数:

df.groupby(df["date"].dt.month).count().plot(kind="bar")

.dt 允许您访问日期时间属性.

.dt allows you to access the datetime properties.

哪个会给你:

您可以按年、日等替换月.

You can replace month by year, day, etc..

例如，如果您想区分年份和月份，只需执行以下操作:

If you want to distinguish year and month for instance, just do:

df.groupby([df["date"].dt.year, df["date"].dt.month]).count().plot(kind="bar")

给出:

这是你想要的吗?清楚了吗?

Was it what you wanted ? Is this clear ?

希望这有帮助！

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