pd.Series supported APIs#

The following table lists both implemented and not implemented methods. If you have need of an operation that is listed as not implemented, feel free to open an issue on the GitHub repository, or give a thumbs up to already created issues. Contributions are also welcome!

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 Modin for the method in the left column. Y stands for yes, N stands for no, P stands for partial (meaning some parameters may not be supported yet), and D stands for default to pandas. To learn more about the implementations that default to pandas, see the related section on Defaulting to pandas.

Note

Currently, the second column reflects implementation status for Ray and Dask engines. By default, support for a method in the HDK engine could be treated as D unless Notes column contains additional information. Similarly, by default Notes contains information about Ray and Dask engines unless Hdk is explicitly mentioned.

Series method

Modin Implementation? (Y/N/P/D)

Notes for Current implementation

abs

Y

add

Y

Hdk: P, support binary operations on scalars and projections of the same frame, otherwise D

add_prefix

Y

add_suffix

Y

agg

Y

aggregate

Y

align

D

all

Y

any

Y

append

Y

Hdk: Y but sort and ignore_index parameters ignored

apply

Y

argmax

Y

argmin

Y

argsort

D

array

D

asfreq

D

asobject

D

asof

Y

astype

Y

Hdk: P, int``<->``float supported

at

Y

at_time

Y

autocorr

Y

axes

Y

base

D

between

D

between_time

Y

bfill

Y

bool

Y

cat

D

clip

Y

combine

Y

combine_first

Y

compare

Y

compress

D

copy

Y

corr

Y

Correlation floating point precision may slightly differ from pandas. For now pearson method is available only. For other methods defaults to pandas.

count

Y

Hdk: P, only default params supported, otherwise D

cov

Y

Covariance floating point precision may slightly differ from pandas.

cummax

Y

cummin

Y

cumprod

Y

cumsum

Y

data

D

describe

Y

diff

Y

div

Y

See add

divide

Y

See add

divmod

Y

dot

Y

drop

Y

Hdk: D

drop_duplicates

Y

droplevel

Y

dropna

Y

Hdk: P since thresh and axis params unsupported

dt

Y

Hdk: P, only year, month, day and hour supported, otherwise D

dtype

Y

dtypes

Y

Hdk: Y

duplicated

Y

empty

Y

eq

Y

See add

equals

Y

ewm

D

expanding

D

explode

Y

factorize

D

ffill

Y

fillna

Y

Hdk: P, params limit, downcast and method unsupported. Also only axis = 0 supported for now

filter

Y

first

Y

first_valid_index

Y

flags

D

floordiv

Y

See add

from_array

D

ftype

Y

ge

Y

See add

get

Y

get_dtype_counts

Y

get_ftype_counts

Y

get_value

D

get_values

D

groupby

D

Hdk: P. count, sum, size supported, otherwise D

gt

Y

See add

hasnans

Y

head

Y

hist

D

iat

Y

idxmax

Y

idxmin

Y

iloc

Y

Hdk: P, read access fully supported, write access: no row and 2D assignments support

imag

D

index

Y

infer_objects

Y

Hdk: D

interpolate

D

is_monotonic

Y

is_monotonic_decreasing

Y

is_monotonic_increasing

Y

is_unique

Y

isin

Y

isna

Y

isnull

Y

item

Y

items

Y

itemsize

D

iteritems

Y

keys

Y

kurt

Y

kurtosis

Y

last

Y

last_valid_index

Y

le

Y

See add

loc

Y

Hdk: P, read access fully supported, write access: no row and 2D assignments support

lt

Y

See add

mad

Y

map

Y

mask

D

max

Y

Hdk: P, only default params supported, otherwise D

mean

P

Modin defaults to pandas if given the level param. Hdk: P. D for level, axis, skipna and numeric_only params

median

P

Modin defaults to pandas if given the level param.

memory_usage

Y

min

Y

Hdk: P, only default params supported, otherwise D

mod

Y

See add

mode

Y

mul

Y

See add

multiply

Y

See add

name

Y

nbytes

D

ndim

Y

ne

Y

See add

nlargest

Y

nonzero

Y

notna

Y

notnull

Y

nsmallest

Y

nunique

Y

Hdk: P, no support for axis!=0 and dropna=False

pct_change

D

pipe

Y

plot

D

pop

Y

pow

Y

See add; Hdk: D

prod

Y

product

Y

ptp

D

put

D

quantile

Y

radd

Y

See add

rank

Y

ravel

Y

rdiv

Y

See add; Hdk: D

rdivmod

Y

real

D

reindex

Y

reindex_like

Y

rename

Y

rename_axis

Y

reorder_levels

D

repeat

D

replace

Y

resample

Y

reset_index

P

Hdk: P. D for level parameter Ray and Dask: D when names or allow_duplicates is non-default

rfloordiv

Y

See add; Hdk: D

rmod

Y

See add; Hdk: D

rmul

Y

See add

rolling

Y

round

Y

rpow

Y

See add; Hdk: D

rsub

Y

See add; -Hdk: D

rtruediv

Y

See add; Hdk: D

sample

Y

searchsorted

Y

sem

P

Modin defaults to pandas if given the level param.

set_axis

Y

set_value

D

shape

Y

Hdk: Y

shift

Y

size

Y

skew

P

Modin defaults to pandas if given the level param.

slice_shift

Y

sort_index

Y

sort_values

D

Hdk: Y

sparse

Y

squeeze

Y

std

P

Modin defaults to pandas if given the level param.

str

Y

strides

D

sub

Y

See add

subtract

Y

See add; Hdk: D

sum

Y

Hdk: P, only default params supported, otherwise D

swapaxes

Y

swaplevel

Y

tail

Y

take

Y

to_clipboard

D

to_csv

D

to_dict

D

to_excel

D

to_frame

Y

to_hdf

D

to_json

D

to_latex

D

to_list

D

to_numpy

D

to_period

D

to_pickle

D

to_sql

Y

to_string

D

to_timestamp

D

to_xarray

D

tolist

D

transform

Y

transpose

Y

truediv

Y

See add

truncate

Y

tshift

Y

tz_convert

Y

tz_localize

Y

unique

Y

unstack

Y

update

Y

valid

D

value_counts

Y

The indices order of resulting object may differ from pandas. Hdk: Y except dropna param support

values

Y

var

P

Modin defaults to pandas if given the level param.

view

D

where

Y