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I have several dataframes that currently have all end-of-month data.
I now used following script to import Finance data:
import csv
import pandas as pd
import numpy as np
import urllib.request
urllib.request.urlretrieve(
'http://chart.finance.yahoo.com/table.csv?s=^GSPC&a=4&b=1&c=2013&d=5&e=1&f=2016&g=m&ignore=.csv',
'gspc.csv'
)
table = pd.read_csv('gspc.csv')
Date Open High Low Close Volume Adj Close
49 2012-05-01 1,398 1,415 1,292 1,310 4158095900 1,310
48 2012-06-01 1,310 1,363 1,267 1,362 4103472300 1,362
47 2012-07-02 1,362 1,392 1,325 1,379 3663113300 1,379
As I said, I need to get this data into end-of-month. I.e.
Date Open High Low Close Volume Adj Close
49 2012-05-31 1,398 1,415 1,292 1,310 4158095900 1,310
48 2012-06-30 1,310 1,363 1,267 1,362 4103472300 1,362
47 2012-07-31 1,362 1,392 1,325 1,379 3663113300 1,379
I tried
table['Date'] = pd.to_datetime(table['Date'])
table.set_index('Date').resample('M')
table
but weren't successful, though "M" should be "month end frequency".
855
Calculate the date at the end of the month There are a few ways to do this, but I've gone with the following: last_date = datetime(year, month + 1, 1) + timedelta(days=-1) . This will calculate the first date of the following month, then subtract 1 day from it to get the last date of the current month.
To get the last day of the month using Python, the easiest way is with the timerange() function from the calendar module to get the number of days in the month, and then create a new date.
This should be the thing you're looking for
table['Date'] = table['Date'] - pd.tseries.offsets.MonthEnd()
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