似乎没有关于如何在单列熊猫操作上使用hy的文档,例如以下内容。希望得到帮助:
# 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)]
答案 0 :(得分:0)
pandas实际上并没有改变Python本身的语法或语义。它只使用运算符重载。因此,尽管helper macros可以使熊猫更加方便,但您可以使用相同运算符的Hy等效项。
; 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))))