On 15/06/2015 22:01, Sebastian M Cheung via Python-list wrote:
On Monday, June 15, 2015 at 11:19:48 AM UTC+1, Mark Lawrence wrote:
On 15/06/2015 11:12, Sebastian M Cheung via Python-list wrote:
How to do financial data cleaning ? Say I assume a list of 1000 finance series
data in myList = Open, High, Low and Close. For missing Close Price data, What
is best practice to clean data in Python
http://pandas.pydata.org/
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My fellow Pythonistas, ask not what our language can do for you, ask
what you can do for our language.
Mark Lawrence
Hi Mark,
Below I read in DirtyData (financial data) from Excel and then find the number
of NaN missing Closed Pricing data:
xls = pd.ExcelFile('DirtyData.xlsm')
df = xls.parse('Dirty Data', index_col=None, na_values=['NA'])
print(df.isnull().astype(int).sum())
So if I were to clean missing Open Price data, I could copy from previous or
row's Close Price data, but how would I implement it? Thanks
I'm sorry but my knowledge of pandas is limited, I just know it's pretty
much best of breed. Try stackoverflow or
https://groups.google.com/forum/#!forum/pydata which is gated to
gmane.comp.python.pydata
--
My fellow Pythonistas, ask not what our language can do for you, ask
what you can do for our language.
Mark Lawrence
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