mars.dataframe.Index¶
- class mars.dataframe.Index(data, **_)[source]¶
- __init__(data=None, dtype=None, copy=False, name=None, tupleize_cols=True, chunk_size=None, gpu=None, sparse=None, names=None, num_partitions=None, store_data=False)[source]¶
Methods
__init__([data, dtype, copy, name, …])agg([func, axis])aggregate([func, axis])all()any()astype(dtype[, copy])Create an Index with values cast to dtypes.
check_monotonic([decreasing, strict])Check if values in the object are monotonic increasing or decreasing.
copy()copy_from(obj)copy_to(target)drop(labels[, errors])Make new Index with passed list of labels deleted.
drop_duplicates([keep, method])Return Index with duplicate values removed.
dropna([how])Return Index without NA/NaN values.
duplicated([keep])Indicate duplicate index values.
execute([session])fillna([value, downcast])Fill NA/NaN values with the specified value.
isna()Detect missing values.
map(mapper[, na_action, dtype, memory_scale])Map values using input correspondence (a dict, Series, or function).
max([axis, skipna])memory_usage([deep])Memory usage of the values.
min([axis, skipna])notna()Detect existing (non-missing) values.
rebalance([factor, axis, num_partitions, …])Make Data more balanced across entire cluster.
rechunk(chunk_size[, threshold, …])rename(name[, inplace])Alter Index or MultiIndex name.
set_names(names[, level, inplace])Set Index or MultiIndex name.
tiles()to_frame([index, name])Create a DataFrame with a column containing the Index.
to_pandas([session])to_series([index, name])Create a Series with both index and values equal to the index keys.
value_counts([normalize, sort, ascending, …])Return a Series containing counts of unique values.
Attributes
dataReturn boolean scalar if values in the object are monotonic_increasing.
Return boolean scalar if values in the object are monotonic_decreasing.
Return boolean scalar if values in the object are monotonic_increasing.
shapetype_namevalues