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pythonpandaspandas-groupby

pandas dataframe filter to return True for ALL rows. how?

Hi I have a filter 'm' set that is flexible enough to change by me. Sometimes, I want to filter by Car or x_acft_body , or any of the various other fields, etc. Sometime I want to have all of the rows returned by commenting and uncommenting the required lines. But without changing the subsequent code, after the filter 'm' line.

How can I have a filter that will return true for ALL rows, when I don't want the filters applied? For e.g. something like 1==1 but i know this doesn't work.

I don't want to set dfdata.somefield.notnull() etc. as I will not be too sure if this field will be always not null or not. also I DO NOT want to change subsequent code to be like dfdata.groupby. i.e. without the [m]

# set filter if needed
m = (   1==1 #& return true at all times
#         (dfdata.Car == 'PG') #&
#         (dfdata.x_acft_body == 'N')# &
#         (dfdata.Car.isin(['PG', 'VJ', 'VZ']))
)


dft1 = dfdata[m].groupby(['FLD1']).agg({'FLD2': 'count'})
Solution

  • You can create bool constant and change final mask by it:

    #True for return all rows
m = (dfdata.Car == 'PG') | True

    And:

    #False for apply filter
m = (dfdata.Car == 'PG') | False

    First solutions:

    m = [True] * len(df.index)

    m = np.repeat(True, len(df.index))