DataFrame boolean indexing using .loc

Question

I have a series (business_day) which was generated via isin in order to create the series with dtype: bool:

Series: 0 True
1 True
2 True
...
563 False
566 False
Name: Date, dtpye: bool

I then tried to update another array by using:

myArray.ix[business_day]

and

myArray.loc[business_day]

where

myArray:
DataFrame: Date Epoch Value
0 2016-05-17 2016-05-17 11:30:00 12345
1 2016-05-17 2016-05-17 11:31:00 6789.7
2 2016-05-17 2016-05-17 11:32:00 123.45

The aim is to modify only myArray whereby the lines are "True" as per the business_day series. However the code used above has no effect. Where am I going wrong here?

What do you mean by no effect (assuming you did assign the result of myArray.loc[business_day] to some variables as it doesn't work in_place)? if you print myArray.loc[business_day], does it show the same number of rows as before? — Stefan
– Stefan, Commented Jun 17, 2016 at 15:26
Exactly: the same number of rows therefore the line of code above (myArray.loc[business_day]) made no difference. — pymat
– pymat, Commented Jun 17, 2016 at 15:33

Stefan · Accepted Answer · 2016-06-17 15:49:36Z

1

Assign the result as it doesn't modify the original DataFrame:

myarray = myarray.loc[business_day]

edited Jun 17, 2016 at 15:49

answered Jun 17, 2016 at 15:33

Stefan

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3 Comments

pymat Over a year ago

Such a dumb mistake...yes it did the trick! Thanks, enjoy the weekend.

Stefan Over a year ago

Which one? The .values shouldn't be necessary.

Stefan Over a year ago

Ok added back to the answer for completeness. glad it was helpful.

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