There seems to be no documentation on how to use hy on single column pandas operation such as the following. Would appreciate any help:
# simple instantiation to scalar
df['a'] = '2'
# the above can be done like so: (-> df (.assign :a "2")) but would appreciate any better ways
# cast a column to int
df['a'] = df['a'].astype(int)
# creating derived columns
df['c'] = df['a'] + df['b']
#subsetting by columns
dd = df[['a','b']]
#subsetting by criteria
dd = df[(df['a'] > 1) & (df['b'] < 2)]
pandas doesn't actually change the syntax or semantics of Python itself; it just uses operator overloading. So you can use the Hy equivalents of the same operators without issues, although helper macros can make pandas a lot more convenient.
; simple instantiation to scalar
(setv (get df "a") "2")
; cast a column to int
(setv (get df "a") (.astype (get df "a") int))
; creating derived columns
(setv (get df "c") (+ (get df "a") (get df "c")))
;subsetting by columns
(setv dd (get df ["a" "b"]))
;subsetting by criteria
(setv dd (get df (& (> (get df "a") 1) (< (get df "b") 2))))