1.1. pandas.DataFrame supported APIsΒΆ

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.

DataFrame method Modin Implementation? (Y/N/P/D) Notes for Current implementation
T Y  
abs Y  
add Y Shuffles data in operations between DataFrames
add_prefix Y  
add_suffix Y  



  • Passing a dictionary for the func parameter

defaults to pandas - Passing the string name of a numpy operation for the func parameter defaults to pandas

align D  
all Y  
any Y  
append P Not fully optimized
apply Y See agg
applymap Y  
as_blocks D Becomes a non-parallel object
as_matrix D Becomes a non-parallel object
asfreq D  
asof D  
assign D  
astype Y  
at D  
at_time D  
axes Y  
between_time D  
bfill Y  
blocks D  
bool Y  
boxplot D  
clip Y  
clip_lower Y  
clip_upper Y  
combine D  
combine_first D  
compound D  
consolidate D  
copy Y  
corr D  
corrwith D  
count Y  
cov D  
cummax Y  
cummin Y  
cumprod Y  
cumsum Y  
describe Y  
diff Y  
div Y See add
divide Y See add
dot P  
drop Y  
drop_duplicates D  
dropna Y  
dtypes Y  
duplicated D  
empty Y  
eq Y See add
equals Y Requires shuffle, can be further optimized
eval Y  
ewm D  
expanding D  
`explode`_ N  
ffill Y  
fillna P value parameter of type DataFrame defaults to pandas
filter Y  
first D  
first_valid_index Y  
floordiv Y See add
from_dict Y  
from_items Y  
from_records Y  
ftypes Y  
ge Y See add
get Y  
get_dtype_counts Y  
get_ftype_counts Y  
get_value D  
get_values D  
groupby Y
  • Not yet optimized
  • by with a list of columns defaults to pandas
gt Y See add
head Y  
hist D  
iat Y  
idxmax Y  
idxmin Y  
iloc Y  
infer_objects D  
info D  
insert Y  
interpolate D  
is_copy D  
isin Y  
isna Y  
isnull Y  
items Y  
iteritems Y  
iterrows Y  
itertuples Y  
ix D  
join Y  
keys Y  
kurt D  
kurtosis D  
last D  
last_valid_index Y  
le Y See add
loc Y  
lookup D  
lt Y See add
mad D  
mask D  
max Y  
mean Y  
median Y  
melt D  
memory_usage Y  
merge P Only implemented for left_index=True and right_index=True, defaults to pandas otherwise
min Y  
mod Y  
mode Y  
mul Y See add
multiply Y See add
ndim Y  
ne Y See add
nlargest D  
notna Y  
notnull Y  
nsmallest D  
nunique Y  
pct_change D  
pipe Y  
pivot D  
pivot_table D  
plot D  
pop Y  
pow Y See add
prod Y  
product Y  
quantile Y  
query P Local variables not yet supported
radd Y See add
rank Y  
rdiv Y See add
reindex Y Shuffles data
reindex_like D  
rename Y  
rename_axis Y  
reorder_levels D  
replace D  
resample D  
reset_index Y  
rfloordiv Y See add
rmod Y See add
rmul Y See add
rolling D  
round Y  
rpow Y See add
rsub Y See add
rtruediv Y See add
sample Y  
select_dtypes Y  
sem D  
set_axis Y  
set_index Y  
set_value D  
shape Y  
shift D  
size Y  
skew Y  
slice_shift D  
sort_index Y  
sort_values Y Shuffles data
sortlevel D  
`sparse`_ N  
squeeze D  
stack D  
std Y  
style D  
sub Y See add
subtract Y See add
sum Y  
swapaxes D  
swaplevel D  
tail Y  
take D  
to_clipboard D  
to_csv D  
to_dense D  
to_dict D  
to_excel D  
to_feather D  
to_gbq D  
to_hdf D  
to_html D  
to_json D  
to_latex D  
to_msgpack D  
to_parquet D  
to_period D  
to_pickle D  
to_records D  
to_sparse D  
to_sql Y  
to_stata D  
to_string D  
to_timestamp D  
to_xarray D  
transform Y  
transpose Y  
truediv Y See add
truncate D  
tshift D  
tz_convert D  
tz_localize D  
unstack D  
update P raise_conflict=True not yet supported
values Y  
var Y  
where Y  
xs N Deprecated in pandas