解释多索引日期时间

Interpreting Multiindex datetime(解释多索引日期时间)

本文介绍了解释多索引日期时间的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我有以下代码:

import pandas as pd
from pandas import DataFrame as df
import matplotlib
from pandas_datareader import data as web
import matplotlib.pyplot as plt
import datetime
import warnings
warnings.filterwarnings("ignore")

start = datetime.date(2020,1,1)
end = datetime.date.today()

stock =  'fb'

data = web.DataReader(stock, 'yahoo', start, end)
data.index = pd.to_datetime(data.index, format ='%Y-%m-%d')
data = data[~data.index.duplicated(keep='first')]
data['year'] = data.index.year
data['month'] = data.index.month
data['week'] = data.index.week
data['day'] = data.index.day
data.set_index('year', append=True, inplace =True)
data.set_index('month',append=True,inplace=True)
data.set_index('week',append=True,inplace=True)
data.set_index('day',append=True,inplace=True)

fig, ax = plt.subplots(dpi=300, figsize =(30,4))
data.plot(y='Close', ax=ax, xlabel= 'Date')

plt.show()

要以更易读的年和月格式将多索引日期解释为x轴,我可以做些什么?例如以类似strftime('%y -%m')格式。这里也提出了类似的问题:Renaming months from number to name in pandas 但我不知道如何使用它来重命名x轴。如有任何帮助,我们将不胜感激。

推荐答案

可以使用matplotlib中的日期。有关更多详细信息,请参阅以下链接:

https://matplotlib.org/stable/api/dates_api.html#matplotlib.dates.ConciseDateFormatter

以下是修改后的代码:

import pandas as pd
from pandas import DataFrame as df
import matplotlib
from pandas_datareader import data as web
import matplotlib.pyplot as plt
import datetime
import warnings
warnings.filterwarnings("ignore")

from matplotlib import dates as mdates

start = datetime.date(2020,1,1)
end = datetime.date.today()

stock =  'fb'

data = web.DataReader(stock, 'yahoo', start, end)
data.index = pd.to_datetime(data.index, format ='%Y-%m-%d')
data = data[~data.index.duplicated(keep='first')]
data['year'] = data.index.year
data['month'] = data.index.month
data['week'] = data.index.week
data['day'] = data.index.day
data.set_index('year', append=True, inplace =True)
data.set_index('month',append=True,inplace=True)
data.set_index('week',append=True,inplace=True)
data.set_index('day',append=True,inplace=True)

fig, ax = plt.subplots(dpi=300, figsize =(15,4))
plt.plot(data.index.get_level_values('Date'), data['Close'])

#--------------------------------------
#Feel free to try different options
#--------------------------------------
#locator = mdates.AutoDateLocator()
locator = mdates.MonthLocator()

formatter = mdates.ConciseDateFormatter(locator)
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)

plt.show()

这里是 output。

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