Calling specific dates and values in stock prices

Question

How do i call data for the dates and values for any shares?

Example: I want to call the stock price and date for apple shares only for dec 2016, dec 2017.

Here is what I've tried:

import pandas as pd

pd.core.common.is_list_like = pd.api.types.is_list_like

import pandas_datareader.data as web

import numpy as np

from matplotlib import style

import matplotlib.pyplot as plt
import datetime as dt

start = dt.datetime(2013,10,1)

end= dt.datetime(2018,4,30)

AAPL_data=[]

AAPL= web.DataReader('AAPL','iex', start, end)
AAPL_data.append(AAPL)

Is this actually a Pandas question? Please add more details so we can help you. — Josh Friedlander, Aug 15 '18 at 14:01
import pandas_datareader.data as web import numpy as np from matplotlib import style import matplotlib.pyplot as plt import datetime as dt start = dt.datetime(2013,10,1) end= dt.datetime(2018,4,30) AAPL_data=[] AAPL= web.DataReader('AAPL','iex', start, end) AAPL_data.append(AAPL) — Aaron Oh, Aug 15 '18 at 14:08
Don't worry - we were all new once. Thanks for sharing the code, that's much better. Could you put it into your question using the edit function, and format it with `code` tags? — Josh Friedlander, Aug 15 '18 at 14:12

Josh Friedlander · Accepted Answer · 2018-08-15T15:17:32.003

0

AAPL.loc['2016-12-01':'2016-12-31']

AAPL.loc['2017-12-01':'2017-12-31']

both work for me, for December '16/'17 data respectively. Pandas datetime indexing is very flexible and intuitive, see more examples here.

Incidentally, if you're using the new release of pandas-datareader (0.7.0), you no longer need to insert pd.core.common.is_list_like = pd.api.types.is_list_like.

edited Aug 15 '18 at 15:17

answered Aug 15 '18 at 15:12

Josh Friedlander

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Calling specific dates and values in stock prices

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