Tables (datascience.tables)

Summary of methods for Table. Click a method to see its documentation.

One note about reading the method signatures for this page: each method is listed with its arguments. However, optional arguments are specified in brackets. That is, a method that’s documented like

Table.foo (first_arg, second_arg[, some_other_arg, fourth_arg])

means that the Table.foo method must be called with first_arg and second_arg and optionally some_other_arg and fourth_arg. That means the following are valid ways to call Table.foo:

some_table.foo(1, 2)
some_table.foo(1, 2, 'hello')
some_table.foo(1, 2, 'hello', 'world')
some_table.foo(1, 2, some_other_arg='hello')

But these are not valid:

some_table.foo(1) # Missing arg
some_table.foo(1, 2[, 'hi']) # SyntaxError
some_table.foo(1, 2[, 'hello', 'world']) # SyntaxError

If that syntax is confusing, you can click the method name itself to get to the details page for that method. That page will have a more straightforward syntax.

Creation

Table.__init__([labels, formatter])	Create an empty table with column labels.
Table.from_records(records)	Create a table from a sequence of records (dicts with fixed keys).
Table.from_columns_dict(columns)	Create a table from a mapping of column labels to column values.
Table.read_table(filepath_or_buffer, *args, ...)	Read a table from a file or web address.
Table.from_df(df[, keep_index])	Convert a Pandas DataFrame into a Table.
Table.from_array(arr)	Convert a structured NumPy array into a Table.

Extension (does not modify original table)

Table.with_column(label, values[, formatter])	Return a new table with an additional or replaced column.
Table.with_columns(*labels_and_values, ...)	Return a table with additional or replaced columns.
Table.with_row(row)	Return a table with an additional row.
Table.with_rows(rows)	Return a table with additional rows.
Table.relabeled(label, new_label)	Return a new table with label specifying column label(s) replaced by corresponding new_label.

Accessing values

Table.num_columns	Number of columns.
Table.columns	Return a tuple of columns, each with the values in that column.
Table.column(index_or_label)	Return the values of a column as an array.
Table.num_rows	Computes the number of rows in a table
Table.rows	Return a view of all rows.
Table.row(index)	Return a row.
Table.labels	Return a tuple of column labels.
Table.first(label)	Return the zeroth item in a column.
Table.last(label)	Return the last item in a column.
Table.values	Return data in self as a numpy array.
Table.column_index(label)	Return the index of a column by looking up its label.
Table.apply(fn, *column_or_columns)	Apply fn to each element or elements of column_or_columns.

Mutation (modifies table in place)

Table.set_format(column_or_columns, formatter)	Set the pretty print format of a column(s) and/or convert its values.
Table.move_to_start(column_label)	Move a column to be the first column.
Table.move_to_end(column_label)	Move a column to be the last column.
Table.append(row_or_table)	Append a row or all rows of a table in place.
Table.append_column(label, values[, formatter])	Appends a column to the table or replaces a column.
Table.relabel(column_label, new_label)	Changes the label(s) of column(s) specified by column_label to labels in new_label.
Table.remove(row_or_row_indices)	Removes a row or multiple rows of a table in place (row number is 0 indexed).

Transformation (creates a new table)

Table.copy(*[, shallow])	Return a copy of a table.
Table.select(*column_or_columns)	Return a table with only the columns in column_or_columns.
Table.drop(*column_or_columns)	Return a Table with only columns other than selected label or labels.
Table.take()	Return a new Table with selected rows taken by index.
Table.exclude()	Return a new Table without a sequence of rows excluded by number.
Table.move_column(label, index)	Returns a new table with specified column moved to the specified column index.
Table.where(column_or_label[, ...])	Return a new Table containing rows where value_or_predicate returns True for values in column_or_label.
Table.sort(column_or_label[, descending, ...])	Return a Table of rows sorted according to the values in a column.
Table.group(column_or_label[, collect])	Group rows by unique values in a column; count or aggregate others.
Table.groups(labels[, collect])	Group rows by multiple columns, count or aggregate others.
Table.pivot(columns, rows[, values, ...])	Generate a table with a column for each unique value in columns, with rows for each unique value in rows.
Table.stack(key[, labels])	Takes k original columns and returns two columns, with col.
Table.join(column_label, other[, other_label])	Creates a new table with the columns of self and other, containing rows for all values of a column that appear in both tables.
Table.stats([ops])	Compute statistics for each column and place them in a table.
Table.percentile(p)	Return a new table with one row containing the pth percentile for each column.
Table.sample([k, with_replacement, weights])	Return a new table where k rows are randomly sampled from the original table.
Table.shuffle()	Return a new table where all the rows are randomly shuffled from the original table.
Table.sample_from_distribution(distribution, k)	Return a new table with the same number of rows and a new column.
Table.split(k)	Return a tuple of two tables where the first table contains k rows randomly sampled and the second contains the remaining rows.
Table.bin(*columns, **vargs)	Group values by bin and compute counts per bin by column.
Table.pivot_bin(pivot_columns, value_column)	Form a table with columns formed by the unique tuples in pivot_columns containing counts per bin of the values associated with each tuple in the value_column.
Table.relabeled(label, new_label)	Return a new table with label specifying column label(s) replaced by corresponding new_label.
Table.with_row(row)	Return a table with an additional row.
Table.with_rows(rows)	Return a table with additional rows.
Table.with_column(label, values[, formatter])	Return a new table with an additional or replaced column.
Table.with_columns(*labels_and_values, ...)	Return a table with additional or replaced columns.

Exporting / Displaying

Table.show([max_rows])	Display the table.
Table.as_text([max_rows, sep])	Format table as text
Table.as_html([max_rows])	Format table as HTML
Table.index_by(column_or_label)	Return a dict keyed by values in a column that contains lists of
Table.to_array()	Convert the table to a structured NumPy array.
Table.to_df()	Convert the table to a Pandas DataFrame.
Table.to_csv(filename)	Creates a CSV file with the provided filename.

Visualizations

Table.plot([column_for_xticks, select, ...])	Plot line charts for the table.
Table.bar([column_for_categories, select, ...])	Plot bar charts for the table.
Table.group_bar(column_label, **vargs)	Plot a bar chart for the table.
Table.barh([column_for_categories, select, ...])	Plot horizontal bar charts for the table.
Table.group_barh(column_label, **vargs)	Plot a horizontal bar chart for the table.
Table.pivot_hist(pivot_column_label, ...[, ...])	Draw histograms of each category in a column.
Table.hist(*columns[, overlay, bins, ...])	Plots one histogram for each column in columns.
Table.hist_of_counts(*columns[, overlay, ...])	Plots one count-based histogram for each column in columns.
Table.scatter(column_for_x[, select, ...])	Creates scatterplots, optionally adding a line of best fit.
Table.scatter3d(column_for_x, column_for_y)	Convenience wrapper for Table#iscatter3d
Table.boxplot(**vargs)	Plots a boxplot for the table.
Table.interactive_plots()	Redirects plot, barh, hist, and scatter to their plotly equivalents
Table.static_plots()	Turns off redirection of plot, barh, hist, and scatter to their plotly equivalents