Working hard on learning the Pandas pivot tables function, pd.pivot_table.
Notably, several of the methods in McKinney's book are outdated and I've had to search for online documentation.
This has been a great site:
http://pandas.pydata.org/pandas-docs/stable/
And specifically for this page:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.pivot_table.html
Currently, looking to differentiate between "index" and "columns."
Here an example query on some data I am working with:
pd.pivot_table(my_data,values =["Number"],columns=["Accumulating Suburban Families", "Client"],aggfunc=[np.sum])
Notably, several of the methods in McKinney's book are outdated and I've had to search for online documentation.
This has been a great site:
http://pandas.pydata.org/pandas-docs/stable/
And specifically for this page:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.pivot_table.html
Currently, looking to differentiate between "index" and "columns."
Here an example query on some data I am working with:
pd.pivot_table(my_data,values =["Number"],columns=["Accumulating Suburban Families", "Client"],aggfunc=[np.sum])
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