pd.Series supported APIsΒΆ

The following table is structured as follows: The first column contains the method name. The second column is a flag for whether or not there is an implementation in Snowpark for the method in the left column.

Note

Y stands for yes, i.e., supports distributed implementation, N stands for no and API simply errors out, P stands for partial (meaning some parameters may not be supported yet), and D stands for defaults to single node pandas execution via UDF/Sproc.

Attributes

Series attribute

Snowpark implemented? (Y/N/P/D)

Notes for current implementation

T

Y

array

N

at

N

attrs

N

Reading attrs always returns an empty dict, and attempting to modify or set attrs will fail.

axes

Y

dtype

Y

dtypes

Y

empty

Y

flags

P

flags can only be read, and not set.

hasnans

Y

iat

N

iloc

Y

index

Y

is_monotonic_decreasing

N

is_monotonic_increasing

N

is_unique

Y

loc

P

N for set with MultiIndex

name

Y

nbytes

N

ndim

Y

shape

Y

size

Y

values

Y

Methods

Series method

Snowpark implemented? (Y/N/P/D)

Missing parameters

Notes for current implementation

abs

Y

add

P

level

add_prefix

Y

add_suffix

Y

agg

P

Y when function is one of count, mean, min, max, sum, median; std and var supported with ddof=0 or ddof=1; quantile is supported when q is the default value or a scalar.

aggregate

P

See agg

align

N

all

P

N for non-integer/boolean types

any

P

N for non-integer/boolean types

apply

P

convert_dtype is ignored

N if func is not callable.

argmax

N

argmin

N

argsort

N

asfreq

N

asof

N

astype

P

N: from string to datetime or errors == "ignore"

at_time

N

autocorr

N

axes

Y

backfill

N

between

N

between_time

N

bfill

N

bool

N

case_when

N

clip

N

combine

N

combine_first

N

compare

N

convert_dtypes

N

copy

Y

corr

N

count

Y

cov

N

cummax

Y

cummin

Y

cumprod

N

cumsum

P

Y if values are numeric, otherwise fails.

describe

Y

diff

Y

div

P

level

See truediv

divide

P

level

See truediv

divmod

N

dot

N

drop

Y

drop_duplicates

Y

droplevel

N

dropna

P

duplicated

Y

eq

P

level

equals

N

ewm

N

expanding

N

explode

N

factorize

N

ffill

P

N if parameter limit is set

fillna

P

See ffill

filter

N

first

Y

first_valid_index

Y

floordiv

P

level

Raises division by zero exception when the right hand side contains at least one zero. pandas allows division by zero for non-object type Series and returns +/-inf.

ge

P

level

get

Y

groupby

P

observed is ignored since Categoricals are not implemented yet

Y when axis == 0 and by is column label or Series from the current DataFrame; otherwise N; Note that supported functions are agg, count, cumcount, cummax, cummin, cumsum, max, mean, median, min, quantile, shift, std, sum, and var. Otherwise N

gt

P

level

head

Y

hist

N

idxmax

Y

idxmin

Y

infer_objects

N

info

D

Different Index types are used in pandas but not in Snowpark pandas

interpolate

N

isin

Y

Snowpark pandas deviates with respect to handling NA values

isna

Y

isnull

Y

item

N

items

N

keys

Y

kurt

N

kurtosis

N

last

Y

last_valid_index

Y

le

P

level

lt

P

level

map

P

See apply

mask

P

N if given axis or level parameters, N if cond or other is Callable

max

Y

mean

Y

median

Y

memory_usage

N

min

Y

mod

P

level

mode

N

mul

P

level

multiply

P

level

ne

P

level

nlargest

N

notna

Y

notnull

Y

nsmallest

N

nunique

Y

pad

P

See ffill

pct_change

N

pipe

N

pop

N

pow

P

level

prod

N

product

N

quantile

P

Y if values are numeric, and interpolation is "linear" or "nearest"; N if q is a DataFrame or Series

radd

P

level

rank

P

N if axis == 1

ravel

N

rdiv

P

level

See truediv

rdivmod

N

reindex

N

reindex_like

N

rename

P

copy is ignored

N if mapper is callable or the series has MultiIndex

rename_axis

Y

reorder_levels

N

repeat

N

replace

P

method, limit

resample

P

Only DatetimeIndex is supported and its freq will be lost

reset_index

Y

rfloordiv

P

level

See floordiv

rmod

P

level

rmul

P

level

rolling

P

Supports integer window, min_periods >= 1, and center

round

Y

rpow

P

level

rsub

P

level

rtruediv

P

level

See truediv

sample

P

weights, random_state

N if replace = True

searchsorted

N

sem

N

set_axis

Y

copy is ignored

shift

P

freq

No support for freq != None

skew

P

N if axis == 1 or skipna == False or numeric_only=False

sort_index

P

N if given the key param, or if inplace == True or MultiIndex

sort_values

P

N if given the key parameter

squeeze

Y

std

P

N if ddof is not 0 or 1

sub

P

level

subtract

P

level

sum

Y

swapaxes

N

swaplevel

N

tail

Y

take

Y

to_clipboard

N

to_csv

N

to_dict

Y

to_frame

Y

to_hdf

N

to_json

N

to_latex

N

to_list

Y

to_markdown

N

to_numpy

Y

copy is ignored

to_period

N

to_pickle

N

to_sql

N

to_string

N

to_timestamp

N

to_xarray

N

tolist

Y

transform

N

transpose

Y

truediv

P

level

Raises division by zero exception when right hand hand side contains at least one zero. pandas allows division by zero for non-object type Series and returns +/-inf.

truncate

N

tz_convert

N

tz_localize

N

unique

Y

unstack

N

update

Y

value_counts

P

bins

var

P

See std

view

N

where

P

See mask

xs

N
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