mars.dataframe.
Index
__init__
Initialize self. See help(type(self)) for accurate signature.
Methods
__init__([data, dtype, copy, name, …])
Initialize self.
agg([func, axis])
agg
aggregate([func, axis])
aggregate
all()
all
any()
any
astype(dtype[, copy])
astype
Create an Index with values cast to dtypes.
copy()
copy
copy_from(obj)
copy_from
copy_to(target)
copy_to
drop(labels[, errors])
drop
Make new Index with passed list of labels deleted.
drop_duplicates([keep, method])
drop_duplicates
Return Index with duplicate values removed.
dropna([how])
dropna
Return Index without NA/NaN values.
execute([session])
execute
fillna([value, downcast])
fillna
Fill NA/NaN values with the specified value.
isna()
isna
Detect missing values.
map(mapper[, na_action, dtype, memory_scale])
map
Map values using input correspondence (a dict, Series, or function).
max([axis, skipna])
max
memory_usage([deep])
memory_usage
Memory usage of the values.
min([axis, skipna])
min
notna()
notna
Detect existing (non-missing) values.
rebalance([factor, axis, num_partitions, …])
rebalance
Make Data more balanced across entire cluster.
rechunk(chunk_size[, threshold, …])
rechunk
rename(name[, inplace])
rename
Alter Index or MultiIndex name.
set_names(names[, level, inplace])
set_names
Set Index or MultiIndex name.
tiles()
tiles
to_frame([index, name])
to_frame
Create a DataFrame with a column containing the Index.
to_pandas([session])
to_pandas
to_series([index, name])
to_series
Create a Series with both index and values equal to the index keys.
value_counts([normalize, sort, ascending, …])
value_counts
Return a Series containing counts of unique values.
Attributes
data
name
names
ndim
shape
size