In python using pandas for slicing a column, where data is the dataset and 'pickup_latitude is a column following line will work
data = data[(data['pickup_latitude']<=90) & (data['pickup_latitude']>=-90)]
What will be the equivalent of the above in R and that also for multiple columns with different range of values ?
The same thing will work, but you need to add a comma at the end to show that you're indexing rows:
data = data[(data['pickup_latitude']<=90) & (data['pickup_latitude']>=-90), ]
For example, on the built-in mtcars data:
> mt = mtcars[mtcars['mpg'] <= 20 & mtcars['mpg'] >= 15, ]
> mt
mpg cyl disp hp drat wt qsec vs am gear carb
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
A bit of explanation: in R, data frames are lists of columns. If you use square brackets with a single argument, the assumption is you are subsetting columns, as in mtcars['mpg'] is the mpg column of mtcars and data['pickup_latitude'] is the pickup_latitude column of data. If you want to index rows, you need to arguments of the form data[rows, columns], but if either rows or columns is missing, all will be assumed. So mtcars[1:3, ] is the first three rows of mtcars, with all columns. mtcars[mtcars['mpg'] <= 20 & mtcars['mpg'] >= 15, ] is the rows of mtcars that meet the logical requirements, with all columns.
There are also convenience functions that let you avoid retyping data$ or data[, e.g., this will do the same thing:
subset(data, pickup_latitude <=90 & pickup_latitude >=-90)