I am trying to import data from yahoo finance but the pandas seems to not read correctly the start date and the end day. Also is reporting me an error of pandas that I don't understand
this is the code I put :
import numpy as np
import pandas as pd
from pandas_datareader import data as wb
import matplotlib.pyplot as plt
and this is what appear in the screen but I can still using the pandas
/opt/anaconda3/lib/python3.7/site-packages/pandas_datareader/compat/__init__.py:7: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
from pandas.util.testing import assert_frame_equal.
then I ran this code
acciones=["PG","BEI.DE"]
datos= pd.DataFrame()
for t in acciones:
datos[t]=wb.DataReader(t,data_source="yahoo",start=2016-1-1,end=2019-1-1)["Adj Close"]
and when I check the output date is daelayed by two years I don't know why
datos.tail()
Date PG BEI.DE
2016-12-23 76.435783 78.406380
2016-12-27 76.111885 78.726517
2016-12-28 75.635086 78.600410
2016-12-29 75.886978 78.687721
2016-12-30 75.644073 78.192947
datos.head
Date PG BEI.DE
2014-01-02 65.854416 68.331200
2014-01-03 65.780823 68.686317
2014-01-06 65.936180 68.405960
2014-01-07 66.573967 68.592857
2014-01-08 65.609123 68.004128
You're getting a warning that FutureWarning: pandas.util.testing is deprecated so you can still run your code, but it may break in the future. This issue has been resolved here
Instead of using the import statement: from pandas.util.testing import assert_frame_equal use this one instead
from pandas.testing import assert_frame_equal
Also you should use the datetime library to create your start and end dates so that your dates are the correct type.
import datetime
import pandas as pd
import pandas_datareader.data as wb
start_date = datetime.datetime(2016,1,1)
end_date = datetime.datetime(2019,1,1)
acciones=["PG","BEI.DE"]
datos= pd.DataFrame()
for t in acciones:
datos[t]=wb.DataReader(t,data_source="yahoo",start=start_date,end=end_date)["Adj Close"]
Output:
>>> datos.head()
PG BEI.DE
Date
2016-01-04 68.264992 78.003090
2016-01-05 68.482758 78.849281
2016-01-06 67.820770 78.339645
2016-01-07 67.228455 76.426102
2016-01-08 66.174454 76.233788
>>> datos.tail()
PG BEI.DE
Date
2018-12-24 83.908928 NaN
2018-12-26 86.531075 NaN
2018-12-27 88.384834 89.214600
2018-12-28 87.578018 89.805695
2018-12-31 88.288788 NaN