SparseFrame API

SparseFrame(data[, index, columns]) Two dimensional, size-mutable, homogenous tabular data structure with labeled axes (rows and columns).
SparseFrame.add(other[, how, fill_value]) Aligned addition.
SparseFrame.assign(**kwargs) Assign new columns.
SparseFrame.axes
SparseFrame.columns Return column labels
SparseFrame.concat(tables[, axis]) Concat a collection of SparseFrames along given axis.
SparseFrame.copy(*args[, deep]) Copy frame
SparseFrame.drop(labels[, axis]) Drop label(s) from given axis.
SparseFrame.dropna() Drop nans from index.
SparseFrame.fillna(value) Replace NaN values in explicitly stored data with value.
SparseFrame.groupby_agg([by, level, agg_func]) Aggregate data using callable.
SparseFrame.groupby_sum([by, level]) Optimized sparse groupby sum aggregation.
SparseFrame.head([n]) Return rows from the top of the table.
SparseFrame.index Return index labels
SparseFrame.join(other[, axis, how, level]) Join two tables along their indices.
SparseFrame.max(*args, **kwargs) Find maximum element(s).
SparseFrame.mean(*args, **kwargs) Calculate mean(s).
SparseFrame.min(*args, **kwargs) Find minimum element(s)
SparseFrame.multiply(other[, axis]) Multiply SparseFrame row-wise or column-wise.
SparseFrame.nnz() Get the count of explicitly stored values (nonzeros).
SparseFrame.read_npz(filename[, storage_options]) Read from numpy npz format.
SparseFrame.reindex([labels, index, …]) Conform SparseFrame to new index.
SparseFrame.reindex_axis(labels[, axis, …]) Conform SparseFrame to new index.
SparseFrame.rename(columns[, inplace]) Rename columns by applying a callable to every column name.
SparseFrame.set_index([column, idx, level, …]) Set index from array, column or existing multi-index level.
SparseFrame.sort_index() Sort table along index.
SparseFrame.sum(*args, **kwargs) Sum elements.
SparseFrame.take(idx[, axis]) Return data at integer locations.
SparseFrame.to_npz(filename[, block_size, …]) Save to numpy npz format.
SparseFrame.toarray() Return dense np.array representation.
SparseFrame.todense([pandas]) Return dense representation.
SparseFrame.values CSR Matrix represenation of frame
SparseFrame.vstack(frames) Vertical stacking given collection of SparseFrames.