Getting month's end data in python











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I am very new to Python.



I’m trying to figure out how to get the month’s end ‘Adj Close’ rows for each data set (aapl, intc, ebay and amzn).



Here’s what I have done:



import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from pandas.tseries.offsets import Day,MonthEnd

import pandas_datareader.data as web
import datetime
start = datetime.datetime(2013,10,28)
end = datetime.datetime(2018,10,28)
aapl = web.DataReader('AAPL','yahoo',start,end)
intc = web.DataReader('INTC','yahoo',start,end)
ebay = web.DataReader('EBAY','yahoo',start,end)
amzn = web.DataReader('AMZN','yahoo',start,end)


I put in the DataFrame



amazon = amzn
amzn = pd.DataFrame({'AMZN': amazon['Adj Close']})


I wanted the data to show only the month end’s data, so I did this, but it’s giving me an error:



amzn = amzn.loc[pd.date_range(start, end, freq='BM')]


How do I get to show only the month’s end?



I also wanted to create a table, with dates as the index, showing all stock’s adj close during the month’s end.



I tried this and didn’t work (it says that there are duplicate keys):



alldata = pd.merge(aapl,intc,ebay,amzn)


I know that ‘BM’ gives me month’s end, but I can’t seem to find a way to use it.



I’m scratching my head and have been looking; I can’t find the answer.










share|improve this question
























  • do you only want the days that are also months end days? you could do a join on the datetime index.
    – MattR
    Nov 19 at 21:20










  • I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
    – J Lee
    Nov 19 at 21:23










  • @davedwards oh I see... yes will do. Thanks!
    – J Lee
    Nov 19 at 22:32















up vote
2
down vote

favorite












I am very new to Python.



I’m trying to figure out how to get the month’s end ‘Adj Close’ rows for each data set (aapl, intc, ebay and amzn).



Here’s what I have done:



import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from pandas.tseries.offsets import Day,MonthEnd

import pandas_datareader.data as web
import datetime
start = datetime.datetime(2013,10,28)
end = datetime.datetime(2018,10,28)
aapl = web.DataReader('AAPL','yahoo',start,end)
intc = web.DataReader('INTC','yahoo',start,end)
ebay = web.DataReader('EBAY','yahoo',start,end)
amzn = web.DataReader('AMZN','yahoo',start,end)


I put in the DataFrame



amazon = amzn
amzn = pd.DataFrame({'AMZN': amazon['Adj Close']})


I wanted the data to show only the month end’s data, so I did this, but it’s giving me an error:



amzn = amzn.loc[pd.date_range(start, end, freq='BM')]


How do I get to show only the month’s end?



I also wanted to create a table, with dates as the index, showing all stock’s adj close during the month’s end.



I tried this and didn’t work (it says that there are duplicate keys):



alldata = pd.merge(aapl,intc,ebay,amzn)


I know that ‘BM’ gives me month’s end, but I can’t seem to find a way to use it.



I’m scratching my head and have been looking; I can’t find the answer.










share|improve this question
























  • do you only want the days that are also months end days? you could do a join on the datetime index.
    – MattR
    Nov 19 at 21:20










  • I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
    – J Lee
    Nov 19 at 21:23










  • @davedwards oh I see... yes will do. Thanks!
    – J Lee
    Nov 19 at 22:32













up vote
2
down vote

favorite









up vote
2
down vote

favorite











I am very new to Python.



I’m trying to figure out how to get the month’s end ‘Adj Close’ rows for each data set (aapl, intc, ebay and amzn).



Here’s what I have done:



import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from pandas.tseries.offsets import Day,MonthEnd

import pandas_datareader.data as web
import datetime
start = datetime.datetime(2013,10,28)
end = datetime.datetime(2018,10,28)
aapl = web.DataReader('AAPL','yahoo',start,end)
intc = web.DataReader('INTC','yahoo',start,end)
ebay = web.DataReader('EBAY','yahoo',start,end)
amzn = web.DataReader('AMZN','yahoo',start,end)


I put in the DataFrame



amazon = amzn
amzn = pd.DataFrame({'AMZN': amazon['Adj Close']})


I wanted the data to show only the month end’s data, so I did this, but it’s giving me an error:



amzn = amzn.loc[pd.date_range(start, end, freq='BM')]


How do I get to show only the month’s end?



I also wanted to create a table, with dates as the index, showing all stock’s adj close during the month’s end.



I tried this and didn’t work (it says that there are duplicate keys):



alldata = pd.merge(aapl,intc,ebay,amzn)


I know that ‘BM’ gives me month’s end, but I can’t seem to find a way to use it.



I’m scratching my head and have been looking; I can’t find the answer.










share|improve this question















I am very new to Python.



I’m trying to figure out how to get the month’s end ‘Adj Close’ rows for each data set (aapl, intc, ebay and amzn).



Here’s what I have done:



import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from pandas.tseries.offsets import Day,MonthEnd

import pandas_datareader.data as web
import datetime
start = datetime.datetime(2013,10,28)
end = datetime.datetime(2018,10,28)
aapl = web.DataReader('AAPL','yahoo',start,end)
intc = web.DataReader('INTC','yahoo',start,end)
ebay = web.DataReader('EBAY','yahoo',start,end)
amzn = web.DataReader('AMZN','yahoo',start,end)


I put in the DataFrame



amazon = amzn
amzn = pd.DataFrame({'AMZN': amazon['Adj Close']})


I wanted the data to show only the month end’s data, so I did this, but it’s giving me an error:



amzn = amzn.loc[pd.date_range(start, end, freq='BM')]


How do I get to show only the month’s end?



I also wanted to create a table, with dates as the index, showing all stock’s adj close during the month’s end.



I tried this and didn’t work (it says that there are duplicate keys):



alldata = pd.merge(aapl,intc,ebay,amzn)


I know that ‘BM’ gives me month’s end, but I can’t seem to find a way to use it.



I’m scratching my head and have been looking; I can’t find the answer.







python pandas






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share|improve this question













share|improve this question




share|improve this question








edited Nov 19 at 22:15









halfer

14.3k758107




14.3k758107










asked Nov 19 at 21:04









J Lee

111




111












  • do you only want the days that are also months end days? you could do a join on the datetime index.
    – MattR
    Nov 19 at 21:20










  • I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
    – J Lee
    Nov 19 at 21:23










  • @davedwards oh I see... yes will do. Thanks!
    – J Lee
    Nov 19 at 22:32


















  • do you only want the days that are also months end days? you could do a join on the datetime index.
    – MattR
    Nov 19 at 21:20










  • I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
    – J Lee
    Nov 19 at 21:23










  • @davedwards oh I see... yes will do. Thanks!
    – J Lee
    Nov 19 at 22:32
















do you only want the days that are also months end days? you could do a join on the datetime index.
– MattR
Nov 19 at 21:20




do you only want the days that are also months end days? you could do a join on the datetime index.
– MattR
Nov 19 at 21:20












I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
– J Lee
Nov 19 at 21:23




I want the latest day of the month that has values (Feb 28, 2015, March 30... ).
– J Lee
Nov 19 at 21:23












@davedwards oh I see... yes will do. Thanks!
– J Lee
Nov 19 at 22:32




@davedwards oh I see... yes will do. Thanks!
– J Lee
Nov 19 at 22:32












2 Answers
2






active

oldest

votes

















up vote
0
down vote













From your example, given a DataFrame:



data = pd.DataFrame({'AMZN': amzn['Adj Close']})


You could try using the is_month_end function:



data.loc[amzn['Adj Close'].index.is_month_end]


This will produce:



AMZN
Date
2013-10-31 364.029999
2013-12-31 398.790009
2014-01-31 358.690002
...


Notice that it is returning results for the last day of the month, if it has a value.



To get the latest day in the month with a value (but not necessarily the last day of the month), you might try:



data.reset_index().loc[d2['Date']
.groupby(pd.DatetimeIndex(data.index)
.to_period('M')).idxmax()]





share|improve this answer























  • Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
    – J Lee
    Nov 19 at 22:44


















up vote
0
down vote













If the date is your index and you want to subset your dataframe with the latest date in the month, try this: df[df.index.day == df.index.days_in_month]






share|improve this answer





















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    2 Answers
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    active

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    2 Answers
    2






    active

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    up vote
    0
    down vote













    From your example, given a DataFrame:



    data = pd.DataFrame({'AMZN': amzn['Adj Close']})


    You could try using the is_month_end function:



    data.loc[amzn['Adj Close'].index.is_month_end]


    This will produce:



    AMZN
    Date
    2013-10-31 364.029999
    2013-12-31 398.790009
    2014-01-31 358.690002
    ...


    Notice that it is returning results for the last day of the month, if it has a value.



    To get the latest day in the month with a value (but not necessarily the last day of the month), you might try:



    data.reset_index().loc[d2['Date']
    .groupby(pd.DatetimeIndex(data.index)
    .to_period('M')).idxmax()]





    share|improve this answer























    • Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
      – J Lee
      Nov 19 at 22:44















    up vote
    0
    down vote













    From your example, given a DataFrame:



    data = pd.DataFrame({'AMZN': amzn['Adj Close']})


    You could try using the is_month_end function:



    data.loc[amzn['Adj Close'].index.is_month_end]


    This will produce:



    AMZN
    Date
    2013-10-31 364.029999
    2013-12-31 398.790009
    2014-01-31 358.690002
    ...


    Notice that it is returning results for the last day of the month, if it has a value.



    To get the latest day in the month with a value (but not necessarily the last day of the month), you might try:



    data.reset_index().loc[d2['Date']
    .groupby(pd.DatetimeIndex(data.index)
    .to_period('M')).idxmax()]





    share|improve this answer























    • Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
      – J Lee
      Nov 19 at 22:44













    up vote
    0
    down vote










    up vote
    0
    down vote









    From your example, given a DataFrame:



    data = pd.DataFrame({'AMZN': amzn['Adj Close']})


    You could try using the is_month_end function:



    data.loc[amzn['Adj Close'].index.is_month_end]


    This will produce:



    AMZN
    Date
    2013-10-31 364.029999
    2013-12-31 398.790009
    2014-01-31 358.690002
    ...


    Notice that it is returning results for the last day of the month, if it has a value.



    To get the latest day in the month with a value (but not necessarily the last day of the month), you might try:



    data.reset_index().loc[d2['Date']
    .groupby(pd.DatetimeIndex(data.index)
    .to_period('M')).idxmax()]





    share|improve this answer














    From your example, given a DataFrame:



    data = pd.DataFrame({'AMZN': amzn['Adj Close']})


    You could try using the is_month_end function:



    data.loc[amzn['Adj Close'].index.is_month_end]


    This will produce:



    AMZN
    Date
    2013-10-31 364.029999
    2013-12-31 398.790009
    2014-01-31 358.690002
    ...


    Notice that it is returning results for the last day of the month, if it has a value.



    To get the latest day in the month with a value (but not necessarily the last day of the month), you might try:



    data.reset_index().loc[d2['Date']
    .groupby(pd.DatetimeIndex(data.index)
    .to_period('M')).idxmax()]






    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 19 at 22:09

























    answered Nov 19 at 21:24









    Wes Doyle

    6801619




    6801619












    • Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
      – J Lee
      Nov 19 at 22:44


















    • Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
      – J Lee
      Nov 19 at 22:44
















    Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
    – J Lee
    Nov 19 at 22:44




    Thank you! This worked -> data = pd.DataFrame({'AMZN': amzn['Adj Close']}). I can't seem to make the date.reset_index to work. I'm still figuring it out :).
    – J Lee
    Nov 19 at 22:44












    up vote
    0
    down vote













    If the date is your index and you want to subset your dataframe with the latest date in the month, try this: df[df.index.day == df.index.days_in_month]






    share|improve this answer

























      up vote
      0
      down vote













      If the date is your index and you want to subset your dataframe with the latest date in the month, try this: df[df.index.day == df.index.days_in_month]






      share|improve this answer























        up vote
        0
        down vote










        up vote
        0
        down vote









        If the date is your index and you want to subset your dataframe with the latest date in the month, try this: df[df.index.day == df.index.days_in_month]






        share|improve this answer












        If the date is your index and you want to subset your dataframe with the latest date in the month, try this: df[df.index.day == df.index.days_in_month]







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 20 at 9:49









        Zanshin

        594421




        594421






























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